Add OSS and commercial workspace boundaries

* feat(vector): add Valkey Search vector database backend

Add a new opt-in VectorDatabase backend backed by the Valkey Search module
(valkey/valkey-bundle), accessed via the official valkey-glide client's native
ft command namespace.

- Implements the full VectorDatabase ABC: VECTOR, FULL_TEXT and HYBRID search,
  all 8 metadata filter operators, and pagination with exact totals.
- HYBRID uses filter-then-KNN (no app-side weighted fusion); vector_weight is
  accepted for interface parity but NOT honored (docstring + one-time warning +
  docs caveat).
- Lazy connect so a down Valkey never blocks boot; mandatory
  client_name=langbot_vector_client; optional auth + TLS (never logged).
- Registered via a single elif branch in vector/mgr.py; disabled by default
  (vdb.use stays chroma) for toC compatibility.
- Adds valkey-glide>=2.4.1,<3.0.0; no protobuf/pydantic downgrade; no ORM
  change so no Alembic migration.
- Unit tests (fast lane, no server) + slow-gated integration tests
  (TEST_VALKEY_URL, valkey/valkey-bundle:9.1.0) + integration doc.

* fix(vector): paginate Valkey Search deletes and guard delete_by_filter

Address self-review follow-ups for the Valkey Search VDB backend:

- _search_keys now paginates through the full result set in batches of
  _DELETE_SCAN_BATCH instead of capping at a single hard-coded 10000-key
  page, so delete_by_file_id / delete_by_filter fully remove files and
  filters that match more than one page of chunks (no orphaned vectors).
- Add unit regression tests for the delete_by_filter mass-deletion guard:
  a filter referencing only non-indexed fields must skip and return 0
  (never fall back to match-all), and a supported filter still deletes
  matching keys.

* refactor(vector): harden Valkey Search backend and add adversarial tests

Address the self-review NICE-TO-HAVE items for the Valkey Search VDB backend:
- Guard the username-without-password credential edge (skip auth + warn
  instead of building ServerCredentials(password=None, ...), which glide
  rejects).
- Add an async close() teardown that closes the glide client and resets
  cached state (re-init is safe via the existing None guard).
- Hoist 'import json' to module top (was imported inside three methods).
- Document the FT TAG literal-brace limitation in _escape_tag (fails closed,
  never widens).

Tests:
- Add an adversarial-input integration test proving crafted file_id /
  query_text cannot break out of or widen a query (fail-closed on braces).
- Add unit tests for close() and the credential-build guard.

Signed-off-by: Daria Korenieva <daric2612@gmail.com>

* fix(vector): make Valkey Search file_id TAG support arbitrary characters

Valkey Search's FT TAG query parser cannot handle '{', '}' or '*' even when
backslash-escaped, so a file_id containing those characters previously
produced an unparseable query (it failed closed / raised). Percent-encode
exactly those FT-unsafe characters (plus '%' for reversibility) in the
file_id TAG value, applied identically at write time and query time, so an
arbitrary file_id round-trips. For normal UUID/hash ids this is a no-op and
the stored value is unchanged; the original file_id is always preserved
verbatim in metadata_json.

Strengthen the adversarial integration test to assert a brace/star-bearing
file_id matches and deletes exactly its own row (no widening, no raise), and
add unit tests for _encode_file_id and the filter encoding.

Signed-off-by: Daria Korenieva <daric2612@gmail.com>

* refactor(vector): address Valkey Search review feedback

- Add configurable request_timeout (default 5000ms; glide default 250ms is
  too low for KNN); expose in config.yaml + docs table
- Validate embedding dimension consistency in add_embeddings (fail fast on
  mixed lengths to avoid silent KNN corruption)
- Use ft.info (O(1)) instead of ft.list (O(n)) for index existence checks in
  the query hot path; also closes the check-then-create TOCTOU window
- Pipeline HSETs via a non-atomic Batch instead of N sequential awaits
- Extract shared _iter_reply_docs to deduplicate reply parsing between
  _reply_to_chroma and list_by_filter
- Parenthesize multi-condition pre-filters before the => KNN clause
- Fail closed when a username is configured without a password
- Catch only RequestError on ft.dropindex (let connection/auth errors surface)
- Bound the delete_collection SCAN loop with a safety cap
- Add VectorDatabase.close() (no-op default) + VectorDBManager.shutdown()
- Simplify _MATCH_ALL literal; normalize typing to builtin generics

* fix(vector/valkey_search): address round-2 review feedback

- Serialize lazy client creation with an asyncio.Lock (double-checked) so
  concurrent first-use callers don't construct and leak duplicate clients.
- Make the filter operator chain exhaustive: raise on an unhandled op rather
  than silently dropping the condition (which could widen delete_by_filter).
- Cast numeric range (///) values to float, failing closed on
  non-numeric input and pre-empting a future NUMERIC-field injection surface.

* refactor(vector): remove shutdown/close from base ABC per maintainer feedback Per maintainer request, interface changes to VectorDatabase ABC and VectorDBManager should be in a separate PR with implementation across all backends. The ValkeySearchVectorDatabase.close() method remains but does not override an ABC method.

Signed-off-by: Daria Korenieva <daric2612@gmail.com>

* docs(test): list valkey_search in vdb coverage exclusions Add valkey_search to the documented vector/vdbs/ coverage-exclusion list, matching the existing chroma/milvus/pgvector/qdrant/seekdb entries. These adapters require a live database instance and are covered by env-gated integration tests instead of unit tests.

Signed-off-by: Daria Korenieva <daric2612@gmail.com>

---------

Signed-off-by: Daria Korenieva <daric2612@gmail.com>

.gitignore

@@ -48,6 +48,7 @@ coverage.xml
 .coverage
 src/langbot/web/
 testsdk/
+.qa/
 
 # Build artifacts
 /dist

AGENTS.md

@@ -1,160 +1,105 @@
 # AGENTS.md
 
-This file guides code agents (Claude Code, GitHub Copilot, OpenAI Codex, etc.) working in the LangBot project. `CLAUDE.md` is a symlink to this file.
+This file guides code agents working in the LangBot main repository. `CLAUDE.md` is a symlink to this file.
 
-## Project Overview
+Read `ARCHITECTURE.md` before non-trivial backend, frontend, runtime, plugin, Box, MCP, persistence, or cross-repo SDK changes. This file is the working checklist; `ARCHITECTURE.md` is the system map.
 
-LangBot is an open-source, LLM-native instant-messaging bot development platform. It aims to provide an out-of-the-box IM bot development experience with Agent, RAG, MCP and other LLM application capabilities, supporting mainstream global IM platforms and exposing rich APIs for custom development.
+## Quick Facts
 
-LangBot has a comprehensive web frontend — almost every operation can be performed through it.
+- Python backend: `>=3.11,<4.0`, dependencies managed by `uv`.
+- Frontend: `web/` is Vite + React Router 7 + shadcn/ui + Tailwind, managed by `pnpm`.
+- Backend framework: Quart served by Hypercorn on `api.port`, default `5300`.
+- Frontend dev server: `web/` on `3000`, with `VITE_API_BASE_URL` pointing at the backend.
+- Plugin/Box/runtime contracts live in sibling repo `langbot-plugin-sdk`, pinned as `langbot-plugin` in `pyproject.toml`.
 
-- **Python**: `>=3.11,<4.0`, dependencies managed by `uv`. Package version is in `pyproject.toml`.
+## Essential Commands
-- **Frontend**: `web/` is a **Vite + React Router 7 + shadcn/ui + Tailwind CSS** SPA, managed by `pnpm`. (Note: this is NOT Next.js — the `dev` script is `vite`.)
-- **Backend framework**: Quart (the async flavour of Flask). The HTTP API and the pre-built web UI are both served by the backend on `http://127.0.0.1:5300`.
-
-## Repository Layout
-
-```
-LangBot/
-├── main.py                     # Entrypoint shim -> langbot.__main__.main()
-├── pyproject.toml              # Python project + deps (uv), pins langbot-plugin==<x.y.z>
-├── src/langbot/
-│   ├── __main__.py             # Real entrypoint, CLI args (--standalone-runtime, --standalone-box, --debug)
-│   ├── pkg/                    # Core backend package
-│   │   ├── api/                # HTTP API controllers + services (Quart)
-│   │   ├── core/               # App bootstrap, stages, task manager
-│   │   ├── platform/           # IM platform adapters, bot managers, session managers
-│   │   ├── provider/           # LLM providers, requesters, tool providers
-│   │   ├── pipeline/           # Pipelines, stages, query pool
-│   │   ├── plugin/             # Bridge connecting LangBot to the plugin runtime (see below)
-│   │   ├── box/                # Code-sandbox subsystem (Docker / nsjail / E2B backends)
-│   │   ├── skill/              # Skill subsystem
-│   │   ├── rag/ , vector/      # RAG + vector store
-│   │   ├── command/            # Built-in commands
-│   │   ├── persistence/        # ORM models + Alembic migrations (SQLite & PostgreSQL)
-│   │   ├── storage/            # Object/file storage abstractions
-│   │   ├── config/, entity/, discover/, utils/, telemetry/, survey/
-│   ├── libs/                   # Vendored SDKs (qq_official_api, wecom_api, etc.)
-│   └── templates/              # Config/component templates (e.g. templates/config.yaml)
-├── web/                        # Frontend SPA (Vite + React Router 7 + shadcn + Tailwind)
-└── docker/                     # docker-compose deployment files
-```
-
-## Development Environment Setup
-
-Full guide lives in the wiki: **["开发配置" / Dev Config](https://docs.langbot.app/zh/develop/dev-config)**. Summary:
-
-### Backend
-
-```bash
-pip install uv
-uv sync --dev          # uv creates a .venv/ for you; point your editor's interpreter at it
-uv run main.py         # serves API + web UI on http://127.0.0.1:5300
-```
-
-On first run the config file is generated at `data/config.yaml`. DB is SQLite by default (zero setup); PostgreSQL is supported. Migrations run automatically on startup.
-
-### Frontend
-
-Requires Node.js + [pnpm](https://pnpm.io/installation).
-
-```bash
-cd web
-cp .env.example .env   # Windows: copy .env.example .env
-pnpm install
-pnpm dev               # http://127.0.0.1:3000  (npm install / npm run dev also work)
-```
-
-`pnpm dev` reads `VITE_API_BASE_URL` from `web/.env` so the dev frontend can reach the backend on port `5300`. In production the frontend is pre-built into static files served by the backend on the same origin.
-
-### Code formatting
-
-The repo runs lint + format checks in CI. Install the pre-commit hooks so the same checks run locally before each commit:
 
 ```bash
+uv sync --dev
+uv run main.py
 uv run pre-commit install
+
+cd web
+pnpm install
+pnpm dev
+pnpm build
 ```
 
-## Plugin System
+Useful focused tests:
-
-LangBot's plugin system (Plugin SDK, CLI `lbp`, Plugin Runtime, and the shared entity/API definitions) lives in a **separate repository**: [`langbot-plugin-sdk`](https://github.com/langbot-app/langbot-plugin-sdk). LangBot depends on it via the pinned `langbot-plugin` package in `pyproject.toml`.
-
-### Architecture (what to know inside this repo)
-
-- Plugins run as independent processes managed by the **Plugin Runtime**. The Runtime supports two control transports: `stdio` and `websocket`.
-- When LangBot is started directly by a user (not in a container), it spawns and connects to the Runtime over **stdio** (lightweight/personal use).
-- When LangBot runs in a container, it connects to a standalone Runtime over **WebSocket** (production).
-- The bridge code lives in `src/langbot/pkg/plugin/` (`connector.py`, `handler.py`).
-- Relevant config (`data/config.yaml`): `plugin.runtime_ws_url` (e.g. `ws://langbot_plugin_runtime:5400/control/ws`). Start LangBot with `--standalone-runtime` to make it connect to an externally-launched Runtime over WebSocket instead of spawning one over stdio.
-
-### Debugging the Plugin Runtime / CLI / SDK
-
-This is documented in detail in the **SDK repo's `AGENTS.md`** and in the wiki page **["调试插件运行时、CLI、SDK" / Plugin Runtime](https://docs.langbot.app/zh/develop/plugin-runtime)**. The short version:
-
-- Clone `LangBot` and `langbot-plugin-sdk` as siblings under one parent dir so the editor resolves shared entities.
-- Start a standalone Runtime from the SDK repo: `uv run --no-sync lbp rt` (control port `5400`, debug port `5401`).
-- To make LangBot use a locally-modified SDK: from the SDK dir, with LangBot's `.venv` active, run `uv pip install .`, then launch LangBot with `uv run --no-sync main.py --standalone-runtime` (keep `--no-sync` so your local SDK isn't overwritten).
-
-### Debugging the Box (sandbox) runtime
-
-The Box subsystem (`src/langbot/pkg/box/`) is the code sandbox. It picks the first available backend among **Docker / nsjail / E2B**. The standalone Box runtime is launched via the SDK CLI: `lbp box`. Backend selection details, the `lbp box` flags, and the SDK-side architecture are documented in the SDK repo's `AGENTS.md`.
-
-Relevant config (`data/config.yaml`, `box:` section): `box.enabled` (master switch — disabling it also disables the native sandbox tools, skill add/edit, and stdio-mode MCP servers), `box.backend` (`'local'` = Docker/nsjail auto-pick, or `'docker'` / `'nsjail'` / `'e2b'`; also settable via `BOX__BACKEND`), and `box.runtime.endpoint` (external Box runtime base URL, e.g. `ws://127.0.0.1:5410`; empty = local auto-managed runtime). Like the plugin runtime, LangBot can connect to an externally-launched Box runtime by setting that endpoint and starting with `--standalone-box`.
-
-> A common false "No supported sandbox backend (Docker / nsjail / E2B) is available" comes from Docker being installed and running but the current user not being in the `docker` group → `docker info` gets `permission denied` on the socket. Fix: `sudo usermod -aG docker <user>` and restart the backend in a shell that has the new group.
-
-## Development Standards
-
-- LangBot is a global project: **all code comments and docstrings must be in English**, and every user-facing string must support **i18n** (`en_US` + `zh_Hans` at minimum, plus `ja_JP` where the repo already has it).
-- LangBot is adopted in both toC and toB scenarios — always consider compatibility and security.
-- **Commit message format**: `<type>(<scope>): <subject>`
-  - `type`: one of `feat`, `fix`, `docs`, `style`, `refactor`, `perf`, `test`, `chore`, etc.
-  - `scope`: the affected package/module/file/class.
-  - `subject`: concise description of the change.
-
-### Database migrations (Alembic)
-
-LangBot uses [Alembic](https://alembic.sqlalchemy.org/) for migrations, supporting both SQLite and PostgreSQL from a single set of scripts. Migration files live in `src/langbot/pkg/persistence/alembic/versions/`.
-
-If you change ORM model definitions, generate a migration:
 
 ```bash
-# Run from the project root (requires data/config.yaml to exist)
+uv run pytest tests/unit_tests -q
-uv run python -m langbot.pkg.persistence.alembic_runner autogenerate "description of your change"
+uv run pytest tests/integration -q
+uv run pytest tests/integration/persistence -q
+uv run pytest tests/manual/mcp_smoke.py
+
+cd web
+pnpm lint
+pnpm test:e2e
 ```
 
-Review and edit the generated script before committing. Migrations execute automatically on startup. `autogenerate` detects schema changes (add/drop columns, tables, type changes) but **data migrations** (e.g. mutating JSON field contents) must be hand-written into the generated script. `env.py` sets `render_as_batch=True`, so SQLite's ALTER TABLE limits are handled automatically — no need to branch per database. More in the wiki ["开发配置"](https://docs.langbot.app/zh/develop/dev-config#数据库迁移).
+Run the narrowest useful test first, then broader checks when confidence is needed.
 
-When writing a migration, follow these rules:
+## Where to Look
 
-- **Revision id ≤ 32 characters.** PostgreSQL stores `alembic_version.version_num` as `varchar(32)`; a longer id raises `StringDataRightTruncationError` at runtime. Prefer short, descriptive ids like `0005_add_llm_context_length`.
+- Architecture map: `ARCHITECTURE.md`.
-- **Guard every operation against missing tables/columns.** Fresh installs build the schema via `create_all()` and then stamp the Alembic baseline, so a migration may run against a table that already has the change — or, in tests, against an empty database. Check `inspector.get_table_names()` / `inspector.get_columns(...)` before `add_column` / `drop_column`, mirroring the existing migrations.
+- Dev environment guide: https://docs.langbot.app/zh/develop/dev-config.
-- **Keep a single linear head.** Chain `down_revision` to the current head; do not create branches. Run the migration tests after adding one: `uv run pytest tests/integration/persistence/ -q` (the PostgreSQL test needs a running PG via `TEST_POSTGRES_URL`).
+- Plugin runtime / CLI / SDK debugging: https://docs.langbot.app/zh/develop/plugin-runtime.
+- API-key auth: `docs/API_KEY_AUTH.md`.
+- Box deep-dive notes: `docs/review/box-architecture.md` and related files.
+- In-repo skills: `skills/` is the single source of truth for LangBot agent skills.
+- SDK repo: `../langbot-plugin-sdk/` when changing shared entities, plugin APIs, action protocol, `lbp rt`, or `lbp box`.
 
-> **Legacy migration system (deprecated — do not extend).** The old 3.x migration system under `src/langbot/pkg/persistence/migrations/` (`DBMigration` subclasses in `dbmXXX_*.py`, run from `pkg/persistence/mgr.py`) is **frozen**. Do **not** add new `dbmXXX_*.py` files. The chain is capped at `required_database_version = 25` (`pkg/utils/constants.py`); those files only exist to upgrade pre-existing 3.x databases up to the Alembic baseline and are kept read-only. All new schema changes go through Alembic.
+## Cross-Repo SDK Work
 
-## Agent-Facing Surfaces (MCP + Skills)
+When changing SDK contracts used by LangBot:
 
-LangBot is built to be **agent-friendly**. Three surfaces let AI agents work
+```bash
-with LangBot, and they MUST be kept in lockstep with the HTTP API:
+# from langbot-plugin-sdk, with LangBot's .venv active
+uv pip install .
 
-1. **MCP server** — `src/langbot/pkg/api/mcp/` exposes a curated subset of the
+# from LangBot, preserve the locally installed SDK
-   API as MCP tools at `/mcp` (API-key authenticated, including the
+uv run --no-sync main.py
-   `api.global_api_key` from config.yaml). `server.py` defines the tools (they
+```
-   call the service layer directly); `mount.py` is the ASGI dispatcher.
-2. **In-repo skills** — `skills/` is the **single source of truth** for agent
-   skills (plugin/core/deploy/e2e/MCP-ops). Docs and the landing page link here
-   rather than embedding their own copies.
-3. **API-key auth** — `api.global_api_key` (config.yaml) authenticates the API
-   and MCP without a login session; see `docs/API_KEY_AUTH.md`.
 
-> **Maintenance rule (important).** When you add, remove, or change an HTTP API
+For standalone runtime debugging:
-> endpoint that should be agent-accessible, you MUST update **both** the matching
-> MCP tool in `src/langbot/pkg/api/mcp/server.py` **and** the relevant skill under
-> `skills/` (especially `skills/skills/langbot-mcp-ops`). The API, the MCP tool
-> surface, and the skills are one system — drift between them is a bug.
 
-## Some Principles
+```bash
+# in langbot-plugin-sdk
+uv run --no-sync lbp rt
+uv run --no-sync lbp box
+
+# in LangBot
+uv run --no-sync main.py --standalone-runtime
+uv run --no-sync main.py --standalone-box
+```
+
+Config keys to verify in `data/config.yaml` / `src/langbot/templates/config.yaml`:
+
+- Plugin runtime: `plugin.runtime_ws_url`, default Docker host `langbot_plugin_runtime:5400/control/ws`.
+- Box runtime: `box.enabled`, `box.backend`, `box.runtime.endpoint`, Docker host `langbot_box:5410`.
+- API/MCP auth: `api.global_api_key`.
+
+## Change Rules
+
+- HTTP API changes that should be agent-accessible must update the matching MCP tool in `src/langbot/pkg/api/mcp/server.py` and the relevant skill under `skills/` in the same pass.
+- New schema changes use Alembic under `src/langbot/pkg/persistence/alembic/versions/`; do not add legacy `dbmXXX` migrations.
+- New platform behavior belongs in platform adapters only for platform translation; pipeline/business logic belongs in `pkg/pipeline/` or services.
+- User-facing strings must support i18n (`en_US`, `zh_Hans`; include `ja_JP` where the repo already does).
+- Code comments and docstrings must be English.
+- Keep compatibility and security in mind; LangBot is used in both self-hosted/community and toB deployments.
+- Commit message format: `<type>(<scope>): <subject>`.
+
+## Runtime Pitfalls
+
+- Local stdio Plugin Runtime disconnects do not auto-reconnect; restart LangBot if that path breaks.
+- Orphan runtime processes on `5400`/`5401` commonly break plugin debugging.
+- Use `uv run --no-sync` after locally installing the SDK, or `uv` may restore the pinned package.
+- A false Box “no backend” often means Docker is running but the current user lacks Docker socket permission.
+- Do not confuse external MCP servers LangBot connects to (`pkg/provider/tools/loaders/mcp.py`) with LangBot's own `/mcp` server (`pkg/api/mcp/`).
+- `CLAUDE.md` is a symlink to this file; edit `AGENTS.md`, not the symlink.
+
+## Principles
 
 - Keep it simple, stupid.
 - Entities should not be multiplied unnecessarily.

ARCHITECTURE.md

@@ -0,0 +1,250 @@
+# Architecture
+
+This document is a map of LangBot's moving parts. It is intentionally more stable than a feature guide and more concrete than the README: when you need to change behavior, start here, then follow the file references into the code.
+
+For agent-specific working rules, see `AGENTS.md`. For plugin-runtime and Box-runtime implementation details, also read the sibling SDK repo: [`langbot-plugin-sdk`](https://github.com/langbot-app/langbot-plugin-sdk).
+
+## What LangBot Is
+
+LangBot is an open-source platform for building production IM bots backed by LLMs, agents, RAG, plugins, MCP tools, and a web management panel.
+
+At runtime, one LangBot process owns:
+
+- a Quart/Hypercorn HTTP service and the built web UI on `:5300`;
+- messaging-platform adapters such as Discord, Telegram, Slack, WeChat, QQ, WeCom, Lark, DingTalk, KOOK, LINE, Satori, Matrix, and HTTP/WebSocket bots;
+- a pipeline engine that turns inbound platform messages into LLM/tool/plugin work and replies;
+- persistence, storage, vector database, telemetry, monitoring, and configuration managers;
+- bridges to the Plugin Runtime and Box Runtime provided by `langbot-plugin-sdk`;
+- an MCP server at `/mcp` exposing a curated agent-facing subset of the service layer.
+
+## Repository Boundary
+
+LangBot is not a single-repo system.
+
+- `LangBot/` is the main product: backend, web UI, platform adapters, pipeline engine, HTTP API, MCP server, RAG, persistence, skills integration, and the bridge code that talks to runtimes.
+- `langbot-plugin-sdk/` is published as `langbot-plugin` and pinned in `LangBot/pyproject.toml`. It contains plugin developer APIs, shared entities, `lbp`, the Plugin Runtime (`lbp rt`), and the Box Runtime (`lbp box`).
+- Plugins import SDK APIs from `langbot_plugin.*`; the LangBot main process imports the same package for shared entities and runtime protocols.
+
+This split matters. If a change modifies SDK entities, component APIs, action protocols, `lbp rt`, or `lbp box`, verify the sibling SDK repo and install the local SDK into LangBot's virtualenv when testing cross-repo behavior.
+
+## Startup Path
+
+The process entrypoint is small and layered:
+
+1. `main.py` delegates to `langbot.__main__.main()`.
+2. `src/langbot/__main__.py` parses `--standalone-runtime`, `--standalone-box`, and `--debug`, checks dependencies, generates missing config/data files, and calls `pkg.core.boot.main()`.
+3. `pkg/core/boot.py` executes startup stages in order: `LoadConfigStage`, `GenKeysStage`, `SetupLoggerStage`, `BuildAppStage`, `ShowNotesStage`.
+4. `BuildAppStage` constructs the `Application` object by wiring managers, services, runtime connectors, and controllers.
+5. `Application.run()` starts the platform manager, query controller, HTTP controller, telemetry/cleanup loops, and plugin initialization.
+
+The central runtime object is `pkg/core/app.py::Application`. It is a service locator for long-lived managers. That is not elegant, but it is the current architectural center; most subsystems receive `ap: Application` and collaborate through it.
+
+## Top-Level Layout
+
+```text
+LangBot/
+├── main.py                         # Entrypoint shim
+├── pyproject.toml                  # Python package, deps, pinned langbot-plugin
+├── src/langbot/
+│   ├── __main__.py                 # CLI entrypoint and boot handoff
+│   ├── pkg/
+│   │   ├── core/                   # Application, boot stages, task manager
+│   │   ├── api/                    # HTTP API + MCP server mount
+│   │   ├── platform/               # IM adapters and runtime bot manager
+│   │   ├── pipeline/               # Message routing and pipeline stages
+│   │   ├── provider/               # LLM runners, model manager, tools
+│   │   ├── plugin/                 # LangBot-side Plugin Runtime connector/handler
+│   │   ├── box/                    # LangBot-side Box service/connector
+│   │   ├── skill/                  # Skill metadata/activation integration
+│   │   ├── rag/ , vector/          # Knowledge-base and vector DB integration
+│   │   ├── persistence/            # SQLAlchemy/SQLModel, Alembic, legacy migrations
+│   │   ├── storage/                # Local/S3 file storage abstraction
+│   │   └── config/, entity/, utils/, telemetry/, survey/
+│   ├── libs/                       # Vendored third-party platform SDKs
+│   └── templates/                  # Default config and component metadata
+├── web/                            # Vite + React Router + shadcn/ui + Tailwind SPA
+├── docker/                         # Deployment manifests
+├── skills/                         # In-repo agent skills, single source of truth
+└── tests/                          # Unit/integration/e2e/manual tests
+```
+
+## The Runtime Graph
+
+The most useful mental model is this graph:
+
+```text
+Platform adapter
+  → RuntimeBot
+  → MessageAggregator
+  → QueryPool
+  → Controller
+  → RuntimePipeline
+  → PipelineStage chain
+  → RequestRunner / ToolManager / PluginRuntimeConnector / BoxService
+  → response via adapter
+```
+
+The HTTP and MCP surfaces are parallel entrypoints into the same service layer:
+
+```text
+HTTP client / Web UI
+  → Quart route group
+  → api/http/service/*
+  → Application managers / persistence / runtime connectors
+
+MCP client
+  → /mcp mount
+  → api/mcp/server.py tools
+  → the same service layer directly
+```
+
+## Message Flow
+
+Inbound platform messages enter through adapter-specific SDK callbacks. The common path is:
+
+1. A platform adapter under `pkg/platform/sources/` converts platform-specific events into SDK message/event entities.
+2. `RuntimeBot` in `pkg/platform/botmgr.py` applies pipeline routing rules and either discards the message, pushes it to webhooks, or sends it to the message aggregator.
+3. `MessageAggregator` batches/normalizes messages before adding a `Query` to `QueryPool`.
+4. `Controller` in `pkg/pipeline/controller.py` selects queries subject to global pipeline concurrency and per-session concurrency.
+5. `RuntimePipeline` in `pkg/pipeline/pipelinemgr.py` runs configured pipeline stages using a responsibility-chain style executor that supports generator stages.
+6. The chat stage emits plugin events, calls a configured `RequestRunner`, handles streaming/non-streaming responses, records telemetry, and appends conversation history.
+7. Output stages send text, cards, chunks, files, or error notices back through the original platform adapter.
+
+Pipeline components are registered by decorators and package import side effects. When adding a new stage, loader, runner, or adapter, check the corresponding preregistration mechanism instead of inventing a second registry.
+
+## Platform Layer
+
+Platform code lives under `pkg/platform/`.
+
+- `botmgr.py` owns runtime bots, routing rules, event logging, webhook pushing, and adapter lifecycle.
+- `sources/` contains adapter implementations. Each adapter subclasses `langbot_plugin.api.definition.abstract.platform.adapter.AbstractMessagePlatformAdapter` from the SDK.
+- Platform entities such as `MessageChain`, `Image`, `At`, `Voice`, and events come from `langbot-plugin-sdk`, not from this repo.
+
+The platform layer should translate between external platform APIs and LangBot's shared message/event model. It should not contain LLM-provider logic or pipeline business logic.
+
+## Pipeline Layer
+
+Pipeline code lives under `pkg/pipeline/`.
+
+Important pieces:
+
+- `pool.py::QueryPool` stores pending queries and cached in-flight queries for plugin backward-compatible calls.
+- `controller.py::Controller` schedules query processing and enforces concurrency.
+- `pipelinemgr.py::RuntimePipeline` materializes database pipeline config into a runtime stage chain.
+- `process/handlers/chat.py::ChatMessageHandler` is the main LLM conversation handler.
+- Stage families include response rules, banned sessions, content filters, preprocessors, rate limits, message truncation, long text handling, response-back, command handling, and wrappers.
+
+Pipelines are configuration-driven. Prefer adding a stage or extending an existing stage family over hard-coding behavior in platform adapters.
+
+## Provider, RAG, and Tools
+
+Provider code lives under `pkg/provider/`.
+
+- `modelmgr/` manages configured model providers and requesters.
+- `runners/` implements request runners such as the local agent runner and external workflow integrations.
+- `tools/toolmgr.py` aggregates tools from native tools, plugin tools, external MCP servers, and skill-authoring tools.
+- `tools/loaders/mcp.py` is the MCP client side: external MCP servers that LangBot connects to for agent tools.
+- RAG lives across `pkg/rag/`, `pkg/vector/`, model services, and plugin KnowledgeEngine actions.
+
+Do not confuse LangBot's MCP client side with LangBot's own MCP server at `/mcp`; they are different surfaces.
+
+## Plugin System
+
+The plugin system crosses the repo boundary.
+
+In this repo:
+
+- `pkg/plugin/connector.py` connects LangBot to the Plugin Runtime over stdio or WebSocket.
+- `pkg/plugin/handler.py` exposes LangBot actions to the runtime and calls runtime actions for plugin operations.
+- `pkg/provider/tools/loaders/plugin.py` exposes plugin Tool components to LLM runners.
+- Pipeline handlers emit SDK events such as normal-message events and prompt-processing events.
+
+In `langbot-plugin-sdk`:
+
+- `src/langbot_plugin/api/` defines `BasePlugin`, component base classes, message/event entities, contexts, proxies, and manifests.
+- `src/langbot_plugin/runtime/` implements `lbp rt`, plugin discovery, dependency installation, process launching, and control/debug connections.
+- `src/langbot_plugin/entities/io/` defines the action protocol shared by LangBot, runtime, and plugin processes.
+
+The Plugin Runtime supports stdio and WebSocket control transports. Direct local LangBot runs usually spawn the runtime over stdio. Containerized/standalone deployments connect over WebSocket using `plugin.runtime_ws_url` and `--standalone-runtime`.
+
+## Box Runtime and Skills
+
+Box is the sandbox subsystem used by native agent tools, stdio MCP servers, skill authoring, and managed processes.
+
+In this repo:
+
+- `pkg/box/service.py` is the application-facing facade for exec, sessions, managed processes, skill CRUD, status, reconnects, quotas, mounts, and sandbox profiles.
+- `pkg/box/connector.py` connects to the Box Runtime over stdio, Windows subprocess+WebSocket, or remote WebSocket.
+- `pkg/provider/tools/loaders/native.py`, `mcp_stdio.py`, and skill loaders depend on Box availability.
+- `pkg/skill/manager.py` loads skills from the Box runtime, falling back to local `data/skills` when needed.
+
+In `langbot-plugin-sdk`:
+
+- `src/langbot_plugin/box/server.py` implements `lbp box` and the WebSocket endpoints on `:5410`.
+- `src/langbot_plugin/box/runtime.py` owns sandbox sessions and managed processes.
+- `backend.py`, `nsjail_backend.py`, and `e2b_backend.py` implement sandbox backends.
+- `skill_store.py` manages skill packages from the Box side.
+
+Important config keys live under `box:` in `src/langbot/templates/config.yaml`: `box.enabled`, `box.backend`, `box.runtime.endpoint`, and `box.local.*`. Start LangBot with `--standalone-box` when connecting to an externally launched Box runtime.
+
+## HTTP API, Web UI, and MCP Server
+
+`pkg/api/http/controller/main.py` builds a Quart app, registers route groups, serves the built SPA, and wraps the ASGI app with the MCP dispatcher.
+
+- HTTP route groups live under `pkg/api/http/controller/groups/`.
+- Service-layer logic lives under `pkg/api/http/service/`.
+- The built web UI is served from the frontend build path with SPA fallback.
+- The MCP server lives under `pkg/api/mcp/` and is mounted at `/mcp`.
+
+The MCP server intentionally exposes a curated subset of the API. Tools call service classes directly rather than making HTTP requests back into LangBot.
+
+Maintenance rule: when adding, removing, or changing an HTTP endpoint that should be agent-accessible, update the matching MCP tool and the relevant in-repo skill under `skills/` in the same pass.
+
+## Persistence and Configuration
+
+Persistence is centered on `pkg/persistence/mgr.py`.
+
+- SQLite is the default database; PostgreSQL is supported.
+- Models live under `pkg/entity/persistence/`.
+- Fresh schemas are created from metadata, then legacy migrations run up to the frozen 3.x baseline, then Alembic migrations run to head.
+- New schema changes should use Alembic under `pkg/persistence/alembic/versions/`; do not extend the frozen legacy migration chain.
+
+Configuration starts from `src/langbot/templates/config.yaml` and is generated into `data/config.yaml` on first run. Most long-lived managers read from `ap.instance_config.data`.
+
+## Frontend
+
+The frontend lives in `web/` and is a Vite SPA using React Router 7, shadcn/ui, Tailwind CSS, and pnpm. It is not Next.js, despite some historical filenames.
+
+In development, `pnpm dev` serves the UI on `:3000` and reads `VITE_API_BASE_URL` to call the backend on `:5300`. In production, the built frontend is packaged into the Python distribution and served by the backend.
+
+Keep frontend API behavior aligned with `pkg/api/http/service/` and route groups. User-facing strings must go through the existing i18n setup.
+
+## Agent-Facing Surfaces
+
+LangBot is deliberately agent-friendly. The agent-facing surfaces are part of the architecture, not extra docs.
+
+- `skills/` is the single source of truth for in-repo skills.
+- `pkg/api/mcp/server.py` exposes the LangBot MCP server at `/mcp`.
+- `api.global_api_key` authenticates API/MCP access without a browser login.
+- `AGENTS.md` and `ARCHITECTURE.md` tell coding agents how the repo works.
+
+When one of these changes, update the others if the behavior or contract changed. API, MCP tools, and skills are one system; drift is a bug.
+
+## Where to Change Things
+
+- New HTTP API: add/adjust a service in `pkg/api/http/service/`, a route group in `pkg/api/http/controller/groups/`, tests, and MCP/skills if agent-accessible.
+- New platform adapter: add a `pkg/platform/sources/*` adapter, component metadata/templates as needed, i18n, docs, and tests/smoke coverage.
+- New pipeline behavior: add or extend a pipeline stage family under `pkg/pipeline/`; avoid putting pipeline rules in adapters.
+- New LLM provider/requester: work under `pkg/provider/modelmgr/` and related service/UI surfaces.
+- New LLM tool source: extend `pkg/provider/tools/loaders/` and `ToolManager` intentionally.
+- New plugin component/API/protocol: change `langbot-plugin-sdk` first or in lockstep, then update LangBot bridge code.
+- New Box capability: change both `pkg/box/` and `langbot-plugin-sdk/src/langbot_plugin/box/`, plus config and tests.
+- New database schema: add an Alembic migration, not a legacy `dbmXXX` migration.
+
+## Design Biases
+
+- Keep platform translation, pipeline orchestration, provider execution, and runtime protocols separate.
+- Reuse existing registries and service layers instead of adding parallel paths.
+- Prefer small, explicit agent surfaces over exposing every internal API.
+- Treat cross-repo contracts with the SDK as public interfaces.
+- Test behavior at the narrowest useful layer first, then add integration/e2e coverage for runtime or platform changes.

README.md

@@ -5,7 +5,7 @@
 
 <div align="center">
 
-<a href="https://www.producthunt.com/products/langbot?utm_source=badge-follow&utm_medium=badge&utm_source=badge-langbot" target="_blank"><img src="https://api.producthunt.com/widgets/embed-image/v1/follow.svg?product_id=1077185&theme=light" alt="LangBot - Production&#0045;grade&#0032;IM&#0032;bot&#0032;made&#0032;easy&#0046; | Product Hunt" style="width: 250px; height: 54px;" width="250" height="54" /></a>
+<a href="https://www.producthunt.com/products/langbot/launches/langbot?embed=true&amp;utm_source=badge-featured&amp;utm_medium=badge&amp;utm_campaign=badge-langbot" target="_blank" rel="noopener noreferrer"><img alt="LangBot - Easy-to-use global IM bot platform designed for the LLM era | Product Hunt" width="250" height="54" src="https://api.producthunt.com/widgets/embed-image/v1/featured.svg?post_id=979554&amp;theme=light&amp;t=1782822143403"></a>
 
 <h3>Production-grade platform for building agentic IM bots.</h3>
 <h4>Quickly build, debug, and ship AI bots to Slack, Discord, Telegram, WeChat, and more.</h4>
@@ -51,7 +51,7 @@ LangBot is an **open-source, production-grade platform** for building AI-powered
 
 [→ Learn more about all features](https://link.langbot.app/en/docs/features)
 
-📍 Practical guides: [deploy a multi-platform AI bot in 5 minutes](https://blog.langbot.app/en/blog/deploy-ai-bot-in-5-minutes/), [connect DeepSeek to WeChat, Discord, and Telegram](https://blog.langbot.app/en/blog/connect-deepseek-to-wechat/), [run a Dify Agent in Discord, Telegram, and Slack](https://blog.langbot.app/en/blog/dify-agent-discord-telegram-slack/), and [build an n8n-powered chatbot](https://blog.langbot.app/en/blog/n8n-multi-platform-ai-chatbot/).
+📍 Practical guides: [deploy a multi-platform AI bot in 5 minutes](https://langbot.app/en/blog/deploy-ai-bot-in-5-minutes/), [connect DeepSeek to WeChat, Discord, and Telegram](https://langbot.app/en/blog/connect-deepseek-to-wechat/), [run a Dify Agent in Discord, Telegram, and Slack](https://langbot.app/en/blog/dify-agent-discord-telegram-slack/), and [build an n8n-powered chatbot](https://langbot.app/en/blog/n8n-multi-platform-ai-chatbot/).
 
 ---
 
@@ -136,7 +136,7 @@ docker compose --profile all up -d
 | [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot)                             | GPU Platform | ✅     |
 | [ShengSuanYun](https://www.shengsuanyun.com/?from=CH_KYIPP758)                                                    | GPU Platform | ✅     |
 | [接口 AI](https://jiekou.ai/)                                                                                     | Gateway      | ✅     |
-| [302.AI](https://share.302.ai/SuTG99)                                                                             | Gateway      | ✅     |
+| [302.AI](https://share.302ai.cn/SuTG99)                                                                             | Gateway      | ✅     |
 | [Qiniu](https://www.qiniu.com/ai/agent)                                                                           | Gateway      | ✅     |
 
 [→ View all integrations](https://link.langbot.app/en/docs/features)

README_CN.md

@@ -51,7 +51,7 @@ LangBot 是一个**开源的生产级平台**，用于构建 AI 驱动的即时
 
 [→ 了解更多功能特性](https://link.langbot.app/zh/docs/features)
 
-📍 实践指南：[5 分钟部署多平台 AI 机器人](https://blog.langbot.app/zh/blog/deploy-ai-bot-in-5-minutes/)、[将 DeepSeek 接入微信、企业微信与 Discord](https://blog.langbot.app/zh/blog/connect-deepseek-to-wechat/)、[让 Dify Agent 跑在 Discord、Telegram 和 Slack 上](https://blog.langbot.app/zh/blog/dify-agent-discord-telegram-slack/)，以及[用 n8n 构建多平台 AI 聊天机器人](https://blog.langbot.app/zh/blog/n8n-multi-platform-ai-chatbot/)。
+📍 实践指南：[5 分钟部署多平台 AI 机器人](https://langbot.app/zh/blog/deploy-ai-bot-in-5-minutes/)、[将 DeepSeek 接入微信、企业微信与 Discord](https://langbot.app/zh/blog/connect-deepseek-to-wechat/)、[让 Dify Agent 跑在 Discord、Telegram 和 Slack 上](https://langbot.app/zh/blog/dify-agent-discord-telegram-slack/)，以及[用 n8n 构建多平台 AI 聊天机器人](https://langbot.app/zh/blog/n8n-multi-platform-ai-chatbot/)。
 
 ---
 
@@ -136,7 +136,7 @@ docker compose --profile all up -d
 | [优云智算](https://www.compshare.cn/?ytag=GPU_YY-gh_langbot) | GPU 平台 | ✅ |
 | [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | GPU 平台 | ✅ |
 | [接口 AI](https://jiekou.ai/) | 聚合平台 | ✅ |
-| [302.AI](https://share.302.ai/SuTG99) | 聚合平台 | ✅ |
+| [302.AI](https://share.302ai.cn/SuTG99) | 聚合平台 | ✅ |
 | [小马算力](https://www.tokenpony.cn/453z1) | 聚合平台 | ✅ |
 | [百宝箱Tbox](https://www.tbox.cn/open) | 智能体平台 | ✅ |
 | [七牛云Qiniu](https://www.qiniu.com/ai/agent) | 聚合平台 | ✅ |

README_ES.md

@@ -5,7 +5,7 @@
 
 <div align="center">
 
-<a href="https://www.producthunt.com/products/langbot?utm_source=badge-follow&utm_medium=badge&utm_source=badge-langbot" target="_blank"><img src="https://api.producthunt.com/widgets/embed-image/v1/follow.svg?product_id=1077185&theme=light" alt="LangBot - Production&#0045;grade&#0032;IM&#0032;bot&#0032;made&#0032;easy&#0046; | Product Hunt" style="width: 250px; height: 54px;" width="250" height="54" /></a>
+<a href="https://www.producthunt.com/products/langbot/launches/langbot?embed=true&amp;utm_source=badge-featured&amp;utm_medium=badge&amp;utm_campaign=badge-langbot" target="_blank" rel="noopener noreferrer"><img alt="LangBot - Easy-to-use global IM bot platform designed for the LLM era | Product Hunt" width="250" height="54" src="https://api.producthunt.com/widgets/embed-image/v1/featured.svg?post_id=979554&amp;theme=light&amp;t=1782822143403"></a>
 
 <h3>Plataforma de grado de producción para construir bots de mensajería instantánea con agentes de IA.</h3>
 <h4>Construya, depure y despliegue bots de IA rápidamente en Slack, Discord, Telegram, WeChat y más.</h4>
@@ -50,7 +50,7 @@ LangBot es una **plataforma de código abierto y grado de producción** para con
 
 [→ Conocer más sobre todas las funcionalidades](https://link.langbot.app/en/docs/features)
 
-📍 Guías prácticas: [desplegar un bot de IA multiplataforma en 5 minutos](https://blog.langbot.app/en/blog/deploy-ai-bot-in-5-minutes/), [conectar DeepSeek a WeChat, Discord y Telegram](https://blog.langbot.app/en/blog/connect-deepseek-to-wechat/), [ejecutar un Dify Agent en Discord, Telegram y Slack](https://blog.langbot.app/en/blog/dify-agent-discord-telegram-slack/) y [crear un chatbot con n8n](https://blog.langbot.app/en/blog/n8n-multi-platform-ai-chatbot/).
+📍 Guías prácticas: [desplegar un bot de IA multiplataforma en 5 minutos](https://langbot.app/en/blog/deploy-ai-bot-in-5-minutes/), [conectar DeepSeek a WeChat, Discord y Telegram](https://langbot.app/en/blog/connect-deepseek-to-wechat/), [ejecutar un Dify Agent en Discord, Telegram y Slack](https://langbot.app/en/blog/dify-agent-discord-telegram-slack/) y [crear un chatbot con n8n](https://langbot.app/en/blog/n8n-multi-platform-ai-chatbot/).
 
 ---
 
@@ -135,7 +135,7 @@ docker compose --profile all up -d
 | [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | Plataforma GPU | ✅ |
 | [ShengSuanYun](https://www.shengsuanyun.com/?from=CH_KYIPP758) | Plataforma GPU | ✅ |
 | [接口 AI](https://jiekou.ai/) | Pasarela | ✅ |
-| [302.AI](https://share.302.ai/SuTG99) | Pasarela | ✅ |
+| [302.AI](https://share.302ai.cn/SuTG99) | Pasarela | ✅ |
 | [Qiniu](https://www.qiniu.com/ai/agent) | Pasarela | ✅ |
 
 [→ Ver todas las integraciones](https://link.langbot.app/en/docs/features)

README_FR.md

@@ -5,7 +5,7 @@
 
 <div align="center">
 
-<a href="https://www.producthunt.com/products/langbot?utm_source=badge-follow&utm_medium=badge&utm_source=badge-langbot" target="_blank"><img src="https://api.producthunt.com/widgets/embed-image/v1/follow.svg?product_id=1077185&theme=light" alt="LangBot - Production&#0045;grade&#0032;IM&#0032;bot&#0032;made&#0032;easy&#0046; | Product Hunt" style="width: 250px; height: 54px;" width="250" height="54" /></a>
+<a href="https://www.producthunt.com/products/langbot/launches/langbot?embed=true&amp;utm_source=badge-featured&amp;utm_medium=badge&amp;utm_campaign=badge-langbot" target="_blank" rel="noopener noreferrer"><img alt="LangBot - Easy-to-use global IM bot platform designed for the LLM era | Product Hunt" width="250" height="54" src="https://api.producthunt.com/widgets/embed-image/v1/featured.svg?post_id=979554&amp;theme=light&amp;t=1782822143403"></a>
 
 <h3>Plateforme de niveau production pour construire des bots de messagerie instantanée avec agents IA.</h3>
 <h4>Créez, déboguez et déployez rapidement des bots IA sur Slack, Discord, Telegram, WeChat et plus.</h4>
@@ -50,7 +50,7 @@ LangBot est une **plateforme open-source de niveau production** pour créer des
 
 [→ En savoir plus sur toutes les fonctionnalités](https://link.langbot.app/en/docs/features)
 
-📍 Guides pratiques : [déployer un bot IA multiplateforme en 5 minutes](https://blog.langbot.app/en/blog/deploy-ai-bot-in-5-minutes/), [connecter DeepSeek à WeChat, Discord et Telegram](https://blog.langbot.app/en/blog/connect-deepseek-to-wechat/), [exécuter un Dify Agent dans Discord, Telegram et Slack](https://blog.langbot.app/en/blog/dify-agent-discord-telegram-slack/) et [créer un chatbot avec n8n](https://blog.langbot.app/en/blog/n8n-multi-platform-ai-chatbot/).
+📍 Guides pratiques : [déployer un bot IA multiplateforme en 5 minutes](https://langbot.app/en/blog/deploy-ai-bot-in-5-minutes/), [connecter DeepSeek à WeChat, Discord et Telegram](https://langbot.app/en/blog/connect-deepseek-to-wechat/), [exécuter un Dify Agent dans Discord, Telegram et Slack](https://langbot.app/en/blog/dify-agent-discord-telegram-slack/) et [créer un chatbot avec n8n](https://langbot.app/en/blog/n8n-multi-platform-ai-chatbot/).
 
 ---
 
@@ -132,7 +132,7 @@ docker compose --profile all up -d
 | [ModelScope](https://modelscope.cn/docs/model-service/API-Inference/intro) | Passerelle | ✅ |
 | [GiteeAI](https://ai.gitee.com/) | Passerelle | ✅ |
 | [接口 AI](https://jiekou.ai/) | Passerelle | ✅ |
-| [302.AI](https://share.302.ai/SuTG99) | Passerelle | ✅ |
+| [302.AI](https://share.302ai.cn/SuTG99) | Passerelle | ✅ |
 | [CompShare](https://www.compshare.cn/?ytag=GPU_YY-gh_langbot) | Plateforme GPU | ✅ |
 | [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | Plateforme GPU | ✅ |
 | [ShengSuanYun](https://www.shengsuanyun.com/?from=CH_KYIPP758) | Plateforme GPU | ✅ |

README_JP.md

@@ -5,7 +5,7 @@
 
 <div align="center">
 
-<a href="https://www.producthunt.com/products/langbot?utm_source=badge-follow&utm_medium=badge&utm_source=badge-langbot" target="_blank"><img src="https://api.producthunt.com/widgets/embed-image/v1/follow.svg?product_id=1077185&theme=light" alt="LangBot - Production&#0045;grade&#0032;IM&#0032;bot&#0032;made&#0032;easy&#0046; | Product Hunt" style="width: 250px; height: 54px;" width="250" height="54" /></a>
+<a href="https://www.producthunt.com/products/langbot/launches/langbot?embed=true&amp;utm_source=badge-featured&amp;utm_medium=badge&amp;utm_campaign=badge-langbot" target="_blank" rel="noopener noreferrer"><img alt="LangBot - Easy-to-use global IM bot platform designed for the LLM era | Product Hunt" width="250" height="54" src="https://api.producthunt.com/widgets/embed-image/v1/featured.svg?post_id=979554&amp;theme=light&amp;t=1782822143403"></a>
 
 <h3>AIエージェント搭載IMボットを構築するための本番グレードプラットフォーム。</h3>
 <h4>Slack、Discord、Telegram、WeChat などに AI ボットを素早く構築、デバッグ、デプロイ。</h4>
@@ -50,7 +50,7 @@ LangBot は、AI搭載のインスタントメッセージングボットを構
 
 [→ すべての機能について詳しく見る](https://link.langbot.app/ja/docs/features)
 
-📍 実践ガイド: [5分でマルチプラットフォームAIボットをデプロイ](https://blog.langbot.app/en/blog/deploy-ai-bot-in-5-minutes/)、[DeepSeekをWeChat・Discord・Telegramに接続](https://blog.langbot.app/en/blog/connect-deepseek-to-wechat/)、[Dify AgentをDiscord・Telegram・Slackで動かす](https://blog.langbot.app/en/blog/dify-agent-discord-telegram-slack/)、[n8n連携チャットボットを構築](https://blog.langbot.app/en/blog/n8n-multi-platform-ai-chatbot/)。
+📍 実践ガイド: [5分でマルチプラットフォームAIボットをデプロイ](https://langbot.app/en/blog/deploy-ai-bot-in-5-minutes/)、[DeepSeekをWeChat・Discord・Telegramに接続](https://langbot.app/en/blog/connect-deepseek-to-wechat/)、[Dify AgentをDiscord・Telegram・Slackで動かす](https://langbot.app/en/blog/dify-agent-discord-telegram-slack/)、[n8n連携チャットボットを構築](https://langbot.app/en/blog/n8n-multi-platform-ai-chatbot/)。
 
 ---
 
@@ -135,7 +135,7 @@ docker compose --profile all up -d
 | [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | GPUプラットフォーム | ✅ |
 | [ShengSuanYun](https://www.shengsuanyun.com/?from=CH_KYIPP758) | GPUプラットフォーム | ✅ |
 | [接口 AI](https://jiekou.ai/) | ゲートウェイ | ✅ |
-| [302.AI](https://share.302.ai/SuTG99) | ゲートウェイ | ✅ |
+| [302.AI](https://share.302ai.cn/SuTG99) | ゲートウェイ | ✅ |
 | [Qiniu](https://www.qiniu.com/ai/agent) | ゲートウェイ | ✅ |
 
 [→ すべての統合を表示](https://link.langbot.app/en/docs/features)

README_KO.md

@@ -5,7 +5,7 @@
 
 <div align="center">
 
-<a href="https://www.producthunt.com/products/langbot?utm_source=badge-follow&utm_medium=badge&utm_source=badge-langbot" target="_blank"><img src="https://api.producthunt.com/widgets/embed-image/v1/follow.svg?product_id=1077185&theme=light" alt="LangBot - Production&#0045;grade&#0032;IM&#0032;bot&#0032;made&#0032;easy&#0046; | Product Hunt" style="width: 250px; height: 54px;" width="250" height="54" /></a>
+<a href="https://www.producthunt.com/products/langbot/launches/langbot?embed=true&amp;utm_source=badge-featured&amp;utm_medium=badge&amp;utm_campaign=badge-langbot" target="_blank" rel="noopener noreferrer"><img alt="LangBot - Easy-to-use global IM bot platform designed for the LLM era | Product Hunt" width="250" height="54" src="https://api.producthunt.com/widgets/embed-image/v1/featured.svg?post_id=979554&amp;theme=light&amp;t=1782822143403"></a>
 
 <h3>AI 에이전트 IM 봇 구축을 위한 프로덕션 등급 플랫폼.</h3>
 <h4>Slack, Discord, Telegram, WeChat 등에 AI 봇을 빠르게 구축, 디버그 및 배포.</h4>
@@ -50,7 +50,7 @@ LangBot은 AI 기반 인스턴트 메시징 봇을 구축하기 위한 **오픈
 
 [→ 모든 기능 자세히 보기](https://link.langbot.app/en/docs/features)
 
-📍 실전 가이드: [5분 만에 멀티 플랫폼 AI 봇 배포하기](https://blog.langbot.app/en/blog/deploy-ai-bot-in-5-minutes/), [DeepSeek를 WeChat, Discord, Telegram에 연결하기](https://blog.langbot.app/en/blog/connect-deepseek-to-wechat/), [Dify Agent를 Discord, Telegram, Slack에서 실행하기](https://blog.langbot.app/en/blog/dify-agent-discord-telegram-slack/), [n8n 기반 챗봇 만들기](https://blog.langbot.app/en/blog/n8n-multi-platform-ai-chatbot/).
+📍 실전 가이드: [5분 만에 멀티 플랫폼 AI 봇 배포하기](https://langbot.app/en/blog/deploy-ai-bot-in-5-minutes/), [DeepSeek를 WeChat, Discord, Telegram에 연결하기](https://langbot.app/en/blog/connect-deepseek-to-wechat/), [Dify Agent를 Discord, Telegram, Slack에서 실행하기](https://langbot.app/en/blog/dify-agent-discord-telegram-slack/), [n8n 기반 챗봇 만들기](https://langbot.app/en/blog/n8n-multi-platform-ai-chatbot/).
 
 ---
 
@@ -135,7 +135,7 @@ docker compose --profile all up -d
 | [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | GPU 플랫폼 | ✅ |
 | [ShengSuanYun](https://www.shengsuanyun.com/?from=CH_KYIPP758) | GPU 플랫폼 | ✅ |
 | [接口 AI](https://jiekou.ai/) | 게이트웨이 | ✅ |
-| [302.AI](https://share.302.ai/SuTG99) | 게이트웨이 | ✅ |
+| [302.AI](https://share.302ai.cn/SuTG99) | 게이트웨이 | ✅ |
 | [Qiniu](https://www.qiniu.com/ai/agent) | 게이트웨이 | ✅ |
 
 [→ 모든 통합 보기](https://link.langbot.app/en/docs/features)

README_RU.md

@@ -5,7 +5,7 @@
 
 <div align="center">
 
-<a href="https://www.producthunt.com/products/langbot?utm_source=badge-follow&utm_medium=badge&utm_source=badge-langbot" target="_blank"><img src="https://api.producthunt.com/widgets/embed-image/v1/follow.svg?product_id=1077185&theme=light" alt="LangBot - Production&#0045;grade&#0032;IM&#0032;bot&#0032;made&#0032;easy&#0046; | Product Hunt" style="width: 250px; height: 54px;" width="250" height="54" /></a>
+<a href="https://www.producthunt.com/products/langbot/launches/langbot?embed=true&amp;utm_source=badge-featured&amp;utm_medium=badge&amp;utm_campaign=badge-langbot" target="_blank" rel="noopener noreferrer"><img alt="LangBot - Easy-to-use global IM bot platform designed for the LLM era | Product Hunt" width="250" height="54" src="https://api.producthunt.com/widgets/embed-image/v1/featured.svg?post_id=979554&amp;theme=light&amp;t=1782822143403"></a>
 
 <h3>Платформа производственного уровня для создания агентных IM-ботов.</h3>
 <h4>Быстро создавайте, отлаживайте и развертывайте ИИ-ботов в Slack, Discord, Telegram, WeChat и других платформах.</h4>
@@ -50,7 +50,7 @@ LangBot — это **платформа с открытым исходным к
 
 [→ Подробнее обо всех возможностях](https://link.langbot.app/en/docs/features)
 
-📍 Практические руководства: [развернуть мультиплатформенного ИИ-бота за 5 минут](https://blog.langbot.app/en/blog/deploy-ai-bot-in-5-minutes/), [подключить DeepSeek к WeChat, Discord и Telegram](https://blog.langbot.app/en/blog/connect-deepseek-to-wechat/), [запустить Dify Agent в Discord, Telegram и Slack](https://blog.langbot.app/en/blog/dify-agent-discord-telegram-slack/) и [создать чат-бота на n8n](https://blog.langbot.app/en/blog/n8n-multi-platform-ai-chatbot/).
+📍 Практические руководства: [развернуть мультиплатформенного ИИ-бота за 5 минут](https://langbot.app/en/blog/deploy-ai-bot-in-5-minutes/), [подключить DeepSeek к WeChat, Discord и Telegram](https://langbot.app/en/blog/connect-deepseek-to-wechat/), [запустить Dify Agent в Discord, Telegram и Slack](https://langbot.app/en/blog/dify-agent-discord-telegram-slack/) и [создать чат-бота на n8n](https://langbot.app/en/blog/n8n-multi-platform-ai-chatbot/).
 
 ---
 
@@ -131,7 +131,7 @@ docker compose --profile all up -d
 | [Volc Engine Ark](https://console.volcengine.com/ark/region:ark+cn-beijing/model?vendor=Bytedance&view=LIST_VIEW) | Шлюз | ✅ |
 | [ModelScope](https://modelscope.cn/docs/model-service/API-Inference/intro) | Шлюз | ✅ |
 | [GiteeAI](https://ai.gitee.com/) | Шлюз | ✅ |
-| [302.AI](https://share.302.ai/SuTG99) | Шлюз | ✅ |
+| [302.AI](https://share.302ai.cn/SuTG99) | Шлюз | ✅ |
 | [接口 AI](https://jiekou.ai/) | Шлюз | ✅ |
 | [CompShare](https://www.compshare.cn/?ytag=GPU_YY-gh_langbot) | Платформа GPU | ✅ |
 | [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | Платформа GPU | ✅ |

README_TW.md

@@ -52,7 +52,7 @@ LangBot 是一個**開源的生產級平台**，用於建構 AI 驅動的即時
 
 [→ 了解更多功能特性](https://link.langbot.app/zh/docs/features)
 
-📍 實踐指南：[5 分鐘部署多平台 AI 機器人](https://blog.langbot.app/zh/blog/deploy-ai-bot-in-5-minutes/)、[將 DeepSeek 接入微信、企業微信與 Discord](https://blog.langbot.app/zh/blog/connect-deepseek-to-wechat/)、[讓 Dify Agent 跑在 Discord、Telegram 和 Slack 上](https://blog.langbot.app/zh/blog/dify-agent-discord-telegram-slack/)，以及[用 n8n 建構多平台 AI 聊天機器人](https://blog.langbot.app/zh/blog/n8n-multi-platform-ai-chatbot/)。
+📍 實踐指南：[5 分鐘部署多平台 AI 機器人](https://langbot.app/zh/blog/deploy-ai-bot-in-5-minutes/)、[將 DeepSeek 接入微信、企業微信與 Discord](https://langbot.app/zh/blog/connect-deepseek-to-wechat/)、[讓 Dify Agent 跑在 Discord、Telegram 和 Slack 上](https://langbot.app/zh/blog/dify-agent-discord-telegram-slack/)，以及[用 n8n 建構多平台 AI 聊天機器人](https://langbot.app/zh/blog/n8n-multi-platform-ai-chatbot/)。
 
 ---
 
@@ -137,7 +137,7 @@ docker compose --profile all up -d
 | [優雲智算](https://www.compshare.cn/?ytag=GPU_YY-gh_langbot) | GPU 平台 | ✅ |
 | [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | GPU 平台 | ✅ |
 | [接口 AI](https://jiekou.ai/) | 聚合平台 | ✅ |
-| [302.AI](https://share.302.ai/SuTG99) | 聚合平台 | ✅ |
+| [302.AI](https://share.302ai.cn/SuTG99) | 聚合平台 | ✅ |
 | [Qiniu](https://www.qiniu.com/ai/agent) | 聚合平台 | ✅ |
 
 ### TTS（語音合成）

README_VI.md

@@ -5,7 +5,7 @@
 
 <div align="center">
 
-<a href="https://www.producthunt.com/products/langbot?utm_source=badge-follow&utm_medium=badge&utm_source=badge-langbot" target="_blank"><img src="https://api.producthunt.com/widgets/embed-image/v1/follow.svg?product_id=1077185&theme=light" alt="LangBot - Production&#0045;grade&#0032;IM&#0032;bot&#0032;made&#0032;easy&#0046; | Product Hunt" style="width: 250px; height: 54px;" width="250" height="54" /></a>
+<a href="https://www.producthunt.com/products/langbot/launches/langbot?embed=true&amp;utm_source=badge-featured&amp;utm_medium=badge&amp;utm_campaign=badge-langbot" target="_blank" rel="noopener noreferrer"><img alt="LangBot - Easy-to-use global IM bot platform designed for the LLM era | Product Hunt" width="250" height="54" src="https://api.producthunt.com/widgets/embed-image/v1/featured.svg?post_id=979554&amp;theme=light&amp;t=1782822143403"></a>
 
 <h3>Nền tảng cấp sản xuất để xây dựng bot IM với AI agent.</h3>
 <h4>Xây dựng, gỡ lỗi và triển khai bot AI nhanh chóng trên Slack, Discord, Telegram, WeChat và nhiều nền tảng khác.</h4>
@@ -50,7 +50,7 @@ LangBot là một **nền tảng mã nguồn mở, cấp sản xuất** để x
 
 [→ Tìm hiểu thêm về tất cả tính năng](https://link.langbot.app/en/docs/features)
 
-📍 Hướng dẫn thực hành: [triển khai bot AI đa nền tảng trong 5 phút](https://blog.langbot.app/en/blog/deploy-ai-bot-in-5-minutes/), [kết nối DeepSeek với WeChat, Discord và Telegram](https://blog.langbot.app/en/blog/connect-deepseek-to-wechat/), [chạy Dify Agent trên Discord, Telegram và Slack](https://blog.langbot.app/en/blog/dify-agent-discord-telegram-slack/) và [xây dựng chatbot với n8n](https://blog.langbot.app/en/blog/n8n-multi-platform-ai-chatbot/).
+📍 Hướng dẫn thực hành: [triển khai bot AI đa nền tảng trong 5 phút](https://langbot.app/en/blog/deploy-ai-bot-in-5-minutes/), [kết nối DeepSeek với WeChat, Discord và Telegram](https://langbot.app/en/blog/connect-deepseek-to-wechat/), [chạy Dify Agent trên Discord, Telegram và Slack](https://langbot.app/en/blog/dify-agent-discord-telegram-slack/) và [xây dựng chatbot với n8n](https://langbot.app/en/blog/n8n-multi-platform-ai-chatbot/).
 
 ---
 
@@ -135,7 +135,7 @@ docker compose --profile all up -d
 | [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | Nền tảng GPU | ✅ |
 | [ShengSuanYun](https://www.shengsuanyun.com/?from=CH_KYIPP758) | Nền tảng GPU | ✅ |
 | [接口 AI](https://jiekou.ai/) | Cổng | ✅ |
-| [302.AI](https://share.302.ai/SuTG99) | Cổng | ✅ |
+| [302.AI](https://share.302ai.cn/SuTG99) | Cổng | ✅ |
 | [Qiniu](https://www.qiniu.com/ai/agent) | Cổng | ✅ |
 
 [→ Xem tất cả tích hợp](https://link.langbot.app/en/docs/features)

docker/docker-compose.yaml

@@ -62,11 +62,12 @@ services:
       - TZ=Asia/Shanghai
       # Unified env-override convention: SECTION__SUBSECTION__KEY overrides the
       # matching config.yaml field (see LoadConfigStage). These map onto
-      # box.local.* and are forwarded to the Box runtime via INIT RPC.
+      # box.* and are forwarded to the Box runtime via INIT RPC.
       - BOX__LOCAL__HOST_ROOT=${LANGBOT_BOX_ROOT:-${PWD}/data/box}
       - BOX__LOCAL__DEFAULT_WORKSPACE=default
       - BOX__LOCAL__SKILLS_ROOT=skills
       - BOX__LOCAL__ALLOWED_MOUNT_ROOTS=${LANGBOT_BOX_ROOT:-${PWD}/data/box}
+      - BOX__DOCKER__CPU_LIMIT_ENABLED=${LANGBOT_BOX_DOCKER_CPU_LIMIT_ENABLED:-true}
     ports:
       - 5300:5300  # For web ui and webhook callback
       - 2280-2285:2280-2285  # For platform reverse connection

docs/VALKEY_SEARCH_INTEGRATION.md

@@ -0,0 +1,169 @@
+# Valkey Search Vector Database Integration
+
+This document describes how to use **Valkey Search** (the search/vector module bundled in
+`valkey/valkey-bundle`) as the vector database backend for LangBot's knowledge base (RAG)
+feature.
+
+## What is Valkey Search?
+
+**Valkey Search** is a module that adds vector similarity search and full-text search to
+[Valkey](https://valkey.io/), the open-source, BSD-licensed in-memory data store forked from
+Redis OSS. It is distributed in the `valkey/valkey-bundle` image alongside other modules
+(JSON, Bloom, LDAP).
+
+LangBot talks to Valkey through the official [`valkey-glide`](https://pypi.org/project/valkey-glide/)
+client (Rust core + async Python wrapper), using its native `ft` (search) command namespace.
+
+### Key Features
+
+- **Vector search**: ANN via HNSW or exact via FLAT, with COSINE / L2 / IP distance metrics
+- **Full-text search**: term, prefix and phrase matching over indexed text fields
+- **Hybrid search**: a metadata/text filter pre-selects candidates, then KNN ranks them
+- **In-memory speed**: vectors and documents are stored as Valkey HASH keys
+- **Auth + TLS**: optional username/password and TLS for production (toB / SaaS) deployments
+
+### Licensing
+
+- Valkey core and the Search module are **BSD-3-Clause**.
+- The `valkey-glide` client is **Apache-2.0**.
+
+Both are compatible with LangBot.
+
+## Installation
+
+Valkey Search support is included when you install LangBot — the `valkey-glide` dependency is
+declared in `pyproject.toml`. To install manually:
+
+```bash
+pip install 'valkey-glide>=2.4.1,<3.0.0'
+```
+
+You also need a running Valkey server with the Search module loaded. The simplest way is the
+bundled image:
+
+```bash
+# Run valkey-bundle (includes the Search module) on host port 6380
+podman run -d --name valkey-test-langbot -p 6380:6379 valkey/valkey-bundle:9.1.0
+# (docker run ... works identically)
+```
+
+`valkey-bundle` ships multi-arch images (linux/amd64 + linux/arm64), so it runs on both CI
+(x86_64) and Apple-silicon dev machines.
+
+## Configuration
+
+Valkey Search is **opt-in and disabled by default** — the default `vdb.use` stays `chroma`,
+so existing single-process deployments are unaffected. To enable it, edit your `config.yaml`:
+
+```yaml
+vdb:
+  use: valkey_search
+  valkey_search:
+    host: 'localhost'
+    port: 6379            # use 6380 if you started the container as shown above
+    db: 0
+    password: ''          # optional (ACL / requirepass) — never logged
+    username: ''          # optional (ACL user)
+    tls: false            # optional (toB / SaaS)
+    index_algorithm: 'HNSW'   # HNSW | FLAT
+    distance_metric: 'COSINE' # COSINE | L2 | IP
+    request_timeout: 5000     # per-request timeout in ms
+```
+
+| Option | Default | Description |
+|--------|---------|-------------|
+| `host` | `localhost` | Valkey host |
+| `port` | `6379` | Valkey port |
+| `db` | `0` | Logical database id |
+| `password` | `''` | Optional auth password (empty = no auth). Never logged. |
+| `username` | `''` | Optional ACL username. Configuring a username without a password fails closed (raises) rather than connecting unauthenticated. |
+| `tls` | `false` | Enable TLS for the connection |
+| `index_algorithm` | `HNSW` | `HNSW` (approximate) or `FLAT` (exact) |
+| `distance_metric` | `COSINE` | `COSINE`, `L2`, or `IP` |
+| `request_timeout` | `5000` | Per-request timeout in milliseconds. The valkey-glide default (250ms) is too low for vector KNN under load; raise it further for remote/cross-AZ Valkey. |
+
+### Connection behavior
+
+The backend uses a **lazy** connection (`lazy_connect=True`): the client is created on first
+use and the connection is deferred to the first command. A misconfigured or unreachable Valkey
+server therefore does **not** block LangBot from booting — knowledge-base operations will error
+at call time instead, and you can recover by switching `vdb.use` back to another backend.
+
+The connection sets a fixed `client_name` of `langbot_vector_client` so it is identifiable in
+`CLIENT LIST` and monitoring dashboards.
+
+## Supported search types
+
+| Type | Behavior |
+|------|----------|
+| `vector` | Pure KNN over the embedding field |
+| `full_text` | Term/phrase match over the indexed `document` text field |
+| `hybrid` | Metadata/text filter **pre-selects** candidates, then KNN ranks them |
+
+### ⚠️ Important: `vector_weight` is NOT honored
+
+Valkey Search hybrid queries follow a **filter-then-KNN** model: the filter (and/or full-text
+clause) narrows the candidate set, and the KNN stage ranks the survivors by vector distance.
+There is **no native weighted score fusion** (unlike, e.g., SeekDB's RRF boost).
+
+For interface compatibility the backend still accepts a `vector_weight` argument, but it is
+**ignored** — passing different weights does not change result ordering. The first time a
+non-default weight is supplied, the backend logs a one-time warning.
+
+If weighted hybrid ranking is needed in the future, it can be added **application-side** (run
+vector KNN and full-text search separately and blend the scores). That is intentionally out of
+scope for this integration.
+
+## Metadata & filtering
+
+Documents are stored as Valkey HASH keys under the prefix `kb:{collection}:{id}` with fields:
+
+- `vector` — the embedding, packed as little-endian FLOAT32
+- `document` — the raw text (indexed as TEXT for full-text/hybrid search)
+- `file_id` — promoted to an indexed TAG field so it is filterable
+- `metadata_json` — the full metadata dict, preserved verbatim as JSON
+
+Only **indexed** fields are filterable. Currently that is `file_id`. Filters referencing
+non-indexed metadata keys are dropped with a warning (the same pragmatism used by the Milvus
+and pgvector backends). All other metadata still round-trips intact via `metadata_json`.
+
+Supported filter operators (canonical Chroma-style `where` syntax): `$eq`, `$ne`, `$gt`,
+`$gte`, `$lt`, `$lte`, `$in`, `$nin`. Multiple top-level keys are AND-ed.
+
+## Testing
+
+Unit tests (filter mapping, float32 packing, reply parsing, import guard) run in the fast lane
+with no server:
+
+```bash
+uv run pytest tests/unit_tests/vector/test_valkey_search_filter.py -q
+```
+
+Integration tests are **slow-gated** on `TEST_VALKEY_URL` and require a running server:
+
+```bash
+podman run -d --name valkey-test-langbot -p 6380:6379 valkey/valkey-bundle:9.1.0
+TEST_VALKEY_URL=valkey://localhost:6380 \
+    uv run pytest tests/integration/vector/test_valkey_search.py -m slow -q
+```
+
+The default upstream fast CI lane (`-m "not slow"`) skips these, matching the existing
+PostgreSQL migration-test precedent.
+
+## Troubleshooting
+
+| Symptom | Cause / fix |
+|---------|-------------|
+| Tests skip with "Valkey Search module not available" | The server is plain Valkey without the Search module. Use the `valkey/valkey-bundle` image. |
+| `ConnectionError` at call time | Check `host`/`port`/auth; remember `lazy_connect` defers errors to first use. |
+| Empty search results right after insert | The Search indexer is asynchronous; results become visible within a short delay. The integration tests poll/retry to account for this. |
+| Hybrid ranking ignores `vector_weight` | Expected — see the caveat above. |
+
+## Production considerations
+
+- **Cluster mode**: Valkey Search in cluster mode uses an additional coordination port. This
+  integration targets standalone mode; cluster support is a future consideration.
+- **Persistence**: configure Valkey RDB/AOF persistence if the knowledge base must survive
+  restarts; otherwise an in-memory store is ephemeral.
+- **Security**: set `password`/`username` and `tls: true` for any non-local deployment.
+  Credentials are never written to logs.

docs/multi-tenant/workspace-multi-user-architecture.md

@@ -0,0 +1,858 @@
+# LangBot 多租户与多用户改造方案
+
+## 目标
+
+本方案面向 LangBot 从“单实例单管理员”演进到 SaaS 友好的“多 workspace、多账户、多权限”架构。
+
+核心定义：
+
+- Account：登录主体。一个自然人或服务账号，可加入多个 workspace。
+- Workspace：租户边界。一个 workspace 内可拥有多个用户、机器人、流水线、模型、知识库、扩展、监控数据与 API Key。
+- Membership：账户与 workspace 的关系，承载角色与权限。
+- Role/Permission：workspace 内权限，不再用“是否是当前唯一用户”来决定访问能力。
+
+目标体验：
+
+- 新用户登录后可以创建 workspace、加入 workspace、切换 workspace。
+- 同一个账户可加入多个 workspace，每个 workspace 权限不同。
+- 一个 workspace 可邀请多个用户协作，并分别设置 owner/admin/editor/viewer 等权限。
+- 所有业务资源默认属于某个 workspace，所有 API 默认在当前 workspace 下工作。
+- Plugin SDK、MCP、知识库、模型调用、监控日志都能拿到稳定的 workspace 上下文，并且不跨租户泄露数据。
+
+## 调研结论
+
+### 当前 LangBot 的单用户假设
+
+LangBot 现在已经有 `users` 表和 JWT 登录，但仍是单用户/单租户模型：
+
+- `src/langbot/pkg/entity/persistence/user.py` 的 `User` 只保存 `user/password/account_type/space_*`，没有角色、状态、workspace 关系。
+- `src/langbot/pkg/api/http/service/user.py` 通过 `is_initialized()` 判断系统是否已有用户；`create_or_update_space_user()` 在系统已初始化且邮箱不匹配时拒绝新用户，这直接限制了多用户登录。
+- `src/langbot/pkg/api/http/controller/group.py` 的 `AuthType.USER_TOKEN` 验证后只向 handler 注入 `user_email`；JWT payload 也只有 `user`，没有 `account_id`、`workspace_id`、`role`、`permissions`。
+- `src/langbot/pkg/api/http/service/apikey.py` 的 API Key 只验证 key 是否存在，没有 owner、scope、workspace。
+- `web/src/app/infra/http/BaseHttpClient.ts` 从 `localStorage.token` 读取单个 token，并在所有请求上加 `Authorization`；前端没有 workspace selector，也没有当前 workspace 上下文。
+
+当前登录流程更像“初始化一个本地管理账号”，而不是 SaaS 账户体系。要支持多用户，必须把“初始化状态”和“首个 workspace 创建”拆开。
+
+### 业务资源当前都是全局资源
+
+主要持久化表没有租户字段：
+
+- Bot：`bots`
+- Pipeline：`legacy_pipelines`、`pipeline_run_records`
+- Model：`model_providers`、`llm_models`、`embedding_models`、`rerank_models`
+- Plugin：`plugin_settings`
+- MCP：`mcp_servers`
+- RAG：`knowledge_bases`、`knowledge_base_files`、`knowledge_base_chunks`
+- Monitoring：`monitoring_messages`、`monitoring_llm_calls`、`monitoring_sessions`、`monitoring_errors`、`monitoring_embedding_calls`、`monitoring_feedback`
+- API Key：`api_keys`
+- Webhook：`webhooks`
+- Metadata：`metadata`
+- Binary storage：`binary_storages`
+
+对应服务也直接 select 全表，例如：
+
+- `BotService.get_bots()` 返回所有 bot。
+- `PipelineService.get_pipelines()` 返回所有 pipeline。
+- `ModelProviderService.get_providers()` 返回所有 provider。
+- `MCPService.get_mcp_servers()` 返回所有 MCP server。
+- 插件和二进制存储没有 workspace 维度，插件 workspace storage 在 SDK 里还硬编码为 `default`。
+
+所以改造重点不是只给用户表加字段，而是给资源访问层统一加入 workspace scope。
+
+### 运行时也存在全局单例假设
+
+`src/langbot/pkg/core/stages/build_app.py` 初始化的是一个全局 `Application`，其中包含单例：
+
+- `platform_mgr`
+- `pipeline_mgr`
+- `model_mgr`
+- `tool_mgr`
+- `plugin_connector`
+- `sess_mgr`
+- `rag_mgr`
+- `vector_db_mgr`
+
+当前运行时把所有 bot、pipeline、model、plugin、MCP 都加载到同一套内存管理器。多租户改造需要决定：是共享运行时并在对象上带 workspace 过滤，还是每个 workspace 拆 runtime shard。第一阶段建议共享进程、强制 workspace-aware；等规模变大后再演进为按 workspace 分片。
+
+### Plugin SDK 对 workspace 的假设
+
+SDK 当前只认识 bot/pipeline/query/session，不认识租户：
+
+- `src/langbot_plugin/api/entities/builtin/pipeline/query.py` 的 `Query` 有 `query_id/launcher_type/launcher_id/sender_id/bot_uuid/pipeline_uuid`，没有 `workspace_id/account_id`。
+- `src/langbot_plugin/api/entities/builtin/provider/session.py` 的 `Session` 只按 `launcher_type + launcher_id` 表达会话。
+- `src/langbot_plugin/api/proxies/langbot_api.py` 暴露 `get_bots/get_llm_models/invoke_llm/list_tools/vector_*` 等 Host API，都是全局语义。
+- `src/langbot_plugin/runtime/io/handlers/plugin.py` 的 `set_workspace_storage/get_workspace_storage` 把 `owner_type` 设为 `workspace`，但 `owner` 固定为 `default`。
+- LangBot 侧 `src/langbot/pkg/plugin/handler.py` 处理插件请求时，会把 `GET_BOTS`、`GET_LLM_MODELS`、`VECTOR_*` 等转到全局服务。
+
+这意味着多租户落地时，不能只在 Web API 层过滤；插件可以通过 Host API 访问全局资源，所以 SDK/Runtime 通信也必须传递 workspace context。
+
+## 开源版与商业版产品边界
+
+LangBot 是开源软件，但多 workspace 能力本质上是 SaaS 控制面能力。如果把完整多 workspace、成员协作、订阅权益和配额代码都放进开源仓库，只靠本地 feature flag 或本地 license check，无法有效避免第三方 fork 后自建 SaaS。因此建议采用 open-core 架构：开源版保留单 workspace 执行能力，账户、订阅、权益和多 workspace 协作能力放到 LangBot Space/Cloud Control Plane 和商业模块中。
+
+### 版本边界
+
+推荐拆成三层：
+
+- `LangBot Core OSS`：开源，自托管，默认只有一个隐式 `default workspace`。它可以在数据结构上兼容 workspace，但产品能力上不提供创建多个 workspace、切换 workspace、成员邀请、成员权限管理、审计和多租户配额。
+- `LangBot Space / Cloud Control Plane`：托管控制面，负责 account、workspace、membership、subscription、billing、entitlement、license token、workspace quota、marketplace 权益等能力。
+- `LangBot Commercial Module`：商业闭源或私有包，承载多 workspace、团队协作、RBAC、自定义角色、审计日志、SAML/SSO、企业私有化授权等能力。
+
+企业私有化版本可以采用 `LangBot Core + Commercial Module + License Token` 的形式交付。开源 Core 仍然可独立运行，但只能作为单 workspace 自托管产品，不提供 SaaS 多租户控制面。
+
+### OSS 中如何保留兼容但不开放多 workspace
+
+为了让后续商业版复用同一套资源隔离模型，OSS 代码里可以保留 `workspace_uuid` 相关字段和默认 workspace 迁移，但应限制为单 workspace：
+
+- 首次初始化时创建一个 `Default Workspace`。
+- 所有资源自动归属这个 default workspace。
+- 不暴露 `POST /api/v1/workspaces`。
+- 不暴露 workspace switcher。
+- 不暴露成员邀请和成员角色管理。
+- 不支持一个 account 加入多个 workspace。
+- 不支持 workspace 数量大于 1。
+- 前端不展示 workspace selector。
+- API 层如果收到非 default workspace 的 `X-Workspace-Id`，直接拒绝。
+
+也就是说，OSS 可以是 workspace-aware，但不是 multi-workspace-enabled。这样做的价值是：代码结构提前适配租户隔离，未来商业版不用重写所有资源模型；同时开源版用户无法直接通过 UI/API 获得 SaaS 型多租户能力。
+
+### 账户、订阅和权益抽到 Space
+
+账户和订阅体系建议从 LangBot Core 中抽出，交给 Space 控制面：
+
+```text
+LangBot Space
+  -> Account
+  -> Workspace
+  -> Membership
+  -> Subscription
+  -> Entitlement
+  -> License Token
+
+LangBot Core
+  -> Validate entitlement / license
+  -> Run bots, pipelines, plugins, MCP, RAG
+  -> Enforce local resource scope
+  -> Report usage
+```
+
+这样做有几个原因：
+
+- 账号体系如果完全在本地，第三方容易直接改库创建 workspace/membership。
+- 订阅、配额和商业权益如果完全在本地，容易绕过。
+- Space 可以统一处理 OAuth、组织、邀请、付款、发票、套餐、权益、Marketplace 分发权限。
+- LangBot Core 只作为执行面消费 Space 下发的 entitlement，减少商业规则暴露。
+
+### Entitlement 设计
+
+Space 向 LangBot Core 下发签名权益，可以是在线校验，也可以为企业版提供短期/长期离线 license token。
+
+示例：
+
+```json
+{
+  "edition": "oss",
+  "workspace_limit": 1,
+  "member_limit": 1,
+  "multi_workspace": false,
+  "rbac": false,
+  "audit_log": false,
+  "custom_roles": false,
+  "sso": false,
+  "commercial_use": false,
+  "expires_at": 1893456000
+}
+```
+
+OSS 默认权益：
+
+- `workspace_limit = 1`
+- `member_limit = 1`
+- `multi_workspace = false`
+- `rbac = false`
+- `audit_log = false`
+- `sso = false`
+
+Cloud/Pro/Enterprise 权益：
+
+- `workspace_limit > 1`
+- `member_limit > 1`
+- `multi_workspace = true`
+- `rbac = true`
+- 可按套餐打开 audit、custom roles、SSO、usage reporting、enterprise support 等能力。
+
+Core 执行面需要在关键入口强制校验 entitlement：
+
+- 创建 workspace。
+- 邀请成员。
+- 修改成员角色。
+- 切换 workspace。
+- 创建超过 quota 的资源。
+- 开启商业模块功能。
+
+### 商业模块边界
+
+以下能力不建议进入 OSS 仓库的完整实现：
+
+- 多 workspace 创建和切换。
+- Workspace 成员邀请。
+- Workspace RBAC 和自定义角色。
+- Workspace 审计日志。
+- Workspace 级用量和配额管理。
+- 订阅、账单、发票。
+- 企业 SSO/SAML/OIDC。
+- 在线/离线 license 管理。
+- 多租户 SaaS 运营控制台。
+
+OSS 仓库可以保留接口占位、默认 workspace 兼容和必要的数据隔离字段，但完整交互、管理 UI、权益校验器和多 workspace policy engine 应由 Space 或商业模块提供。
+
+### 防自建 SaaS 的现实边界
+
+技术上无法 100% 阻止别人 fork 开源代码后自行改造。更可靠的策略是组合：
+
+- 不把完整商业多 workspace 实现放进 OSS。
+- Space 控制面提供账号、订阅、权益、Marketplace 和官方托管能力。
+- 商业模块闭源或私有分发。
+- 使用商标、云服务条款和商业 license 限制“自称官方 LangBot SaaS”或未经授权商用托管。
+- 如果当前开源 license 对托管商用限制不足，需要单独评估 license 策略，必要时引入 open-core license 或新增商业附加条款。具体 license 调整需要法律评审。
+
+结论：多 workspace 的底层 schema 可以在 OSS 中以 default workspace 兼容方式铺路，但多 workspace 产品能力、账户订阅权益、协作管理和 SaaS 控制面应放到 Space/商业模块，不作为开源版可直接使用的能力。
+
+## 推荐总体架构
+
+采用“单实例多 workspace，资源行级隔离，运行时上下文隔离”的架构：
+
+```mermaid
+flowchart TD
+    A["Account"] --> B["WorkspaceMembership"]
+    B --> C["Workspace"]
+    C --> D["Bots"]
+    C --> E["Pipelines"]
+    C --> F["Models & Providers"]
+    C --> G["Knowledge Bases"]
+    C --> H["Extensions: Plugins / MCP"]
+    C --> I["API Keys & Webhooks"]
+    C --> J["Monitoring"]
+    D --> K["Runtime Query"]
+    E --> K
+    K --> L["Plugin Runtime"]
+    K --> M["MCP Runtime"]
+    L --> N["Workspace-scoped Host APIs"]
+```
+
+原则：
+
+- 账户全局唯一，workspace 是所有业务资源的归属边界。
+- 所有 HTTP handler 在进入业务服务前解析出 `RequestContext(account, workspace, membership, permissions)`。
+- 所有 service 方法显式接收 `ctx` 或 `workspace_id`，禁止在业务服务里无条件 select 全表。
+- 运行时对象的 key 从 `uuid` 扩展为 `(workspace_id, uuid)` 或使用全局唯一 uuid 但必须记录 workspace_id 并校验。
+- 插件/MCP/知识库/模型调用都按 query 所属 workspace 过滤可用资源。
+
+## 数据模型设计
+
+### Account
+
+替代现有 `users` 的语义，建议保留表名但升级字段，避免过大迁移：
+
+字段建议：
+
+- `id`
+- `uuid`
+- `email`
+- `password_hash`
+- `display_name`
+- `avatar_url`
+- `account_type`: `local | space`
+- `status`: `active | disabled | deleted`
+- `space_account_uuid`
+- `space_access_token`
+- `space_refresh_token`
+- `space_access_token_expires_at`
+- `space_api_key`
+- `created_at`
+- `updated_at`
+
+兼容策略：
+
+- 旧字段 `user` 迁移为 `email`，可以短期保留 alias。
+- 旧 `password` 迁移为 `password_hash`，也可先保持列名不变，service 层改命名。
+- JWT 中不要继续只放 email，应放 `sub=account_uuid`。
+
+### Workspace
+
+新增 `workspaces`：
+
+- `uuid`
+- `name`
+- `slug`
+- `avatar_url`
+- `type`: `personal | team`
+- `status`: `active | suspended | deleted`
+- `default_language`
+- `created_by_account_uuid`
+- `created_at`
+- `updated_at`
+
+每个账户首次登录时自动创建一个 personal workspace。旧单用户实例迁移时创建一个 `Default Workspace`。
+
+### WorkspaceMembership
+
+新增 `workspace_memberships`：
+
+- `workspace_uuid`
+- `account_uuid`
+- `role`: `owner | admin | developer | operator | viewer`
+- `status`: `active | invited | disabled`
+- `invited_by_account_uuid`
+- `joined_at`
+- `created_at`
+- `updated_at`
+
+唯一索引：
+
+- `(workspace_uuid, account_uuid)`
+
+### WorkspaceInvitation
+
+新增 `workspace_invitations`：
+
+- `uuid`
+- `workspace_uuid`
+- `email`
+- `role`
+- `token_hash`
+- `expires_at`
+- `accepted_at`
+- `created_by_account_uuid`
+- `created_at`
+
+用于邀请外部用户加入 workspace。Space OAuth 登录时可以根据 email 自动匹配未接受邀请。
+
+### Role 与 Permission
+
+先用固定角色，后续再做自定义角色。
+
+建议权限：
+
+- `workspace.manage`
+- `member.view`
+- `member.invite`
+- `member.update_role`
+- `member.remove`
+- `bot.view`
+- `bot.manage`
+- `pipeline.view`
+- `pipeline.manage`
+- `model.view`
+- `model.manage`
+- `knowledge.view`
+- `knowledge.manage`
+- `extension.view`
+- `extension.manage`
+- `monitoring.view`
+- `apikey.manage`
+- `webhook.manage`
+- `billing.view`
+- `billing.manage`
+
+角色映射：
+
+| Role | 说明 | 权限 |
+| --- | --- | --- |
+| owner | workspace 拥有者 | 全部权限；可转让 owner；不可被其他角色移除 |
+| admin | 管理员 | 除 owner 转让和删除 workspace 外的全部权限 |
+| developer | 构建者 | 管理 bot、pipeline、model、knowledge、extension、webhook，可看监控 |
+| operator | 运营者 | 查看和启停 bot、查看监控、查看配置，不可改密钥和删除资源 |
+| viewer | 只读成员 | 只读资源和监控 |
+
+### 业务资源加 workspace_uuid
+
+以下表需要新增 `workspace_uuid`：
+
+- `bots`
+- `legacy_pipelines`
+- `pipeline_run_records`
+- `model_providers`
+- `llm_models`
+- `embedding_models`
+- `rerank_models`
+- `plugin_settings`
+- `mcp_servers`
+- `knowledge_bases`
+- `knowledge_base_files`
+- `knowledge_base_chunks`
+- `monitoring_*`
+- `api_keys`
+- `webhooks`
+- `binary_storages`
+- `metadata`
+
+索引建议：
+
+- 所有资源表加 `(workspace_uuid, created_at)` 或 `(workspace_uuid, updated_at)`。
+- 资源唯一键从单列改为 workspace 复合唯一：
+  - `bots.uuid` 可保持全局唯一，但查询仍必须带 workspace。
+  - `plugin_settings` 主键从 `(plugin_author, plugin_name)` 改为 `(workspace_uuid, plugin_author, plugin_name)`。
+  - `mcp_servers.name` 如果未来要求唯一，必须是 `(workspace_uuid, name)`。
+  - `metadata.key` 改为 `(workspace_uuid, key)`，系统级 metadata 单独放 `system_metadata` 或使用 `workspace_uuid=NULL`。
+  - `binary_storages.unique_key` 建议改为 `workspace_uuid + owner_type + owner + key` 的 hash。
+
+### API Key
+
+API Key 必须归属于 workspace：
+
+- `workspace_uuid`
+- `created_by_account_uuid`
+- `scopes`
+- `expires_at`
+- `last_used_at`
+- `status`
+
+验证 API Key 后生成 `RequestContext`：
+
+- `account_uuid=None` 或 service account uuid
+- `workspace_uuid=key.workspace_uuid`
+- `permissions=key.scopes`
+
+这样 `/api/v1/platform/bots/<uuid>/send_message` 之类接口不会跨 workspace 操作 bot。
+
+## 后端改造方案
+
+### RequestContext
+
+新增统一上下文对象，例如：
+
+```python
+class RequestContext:
+    account_uuid: str | None
+    workspace_uuid: str
+    role: str | None
+    permissions: set[str]
+    auth_type: Literal["user_token", "api_key"]
+```
+
+改造 `RouterGroup.route()`：
+
+- `USER_TOKEN`：验证 JWT，读取 `account_uuid`，再从 header/query/cookie 中解析 current workspace。
+- `API_KEY`：验证 API Key，直接得到 workspace。
+- `USER_TOKEN_OR_API_KEY`：两者都返回同一种 `RequestContext`。
+- handler 参数从可选 `user_email` 升级为可选 `ctx`；兼容期同时支持 `user_email`。
+
+当前 workspace 传递方式：
+
+- 推荐 header：`X-Workspace-Id: <workspace_uuid>`
+- Web 前端同时把当前 workspace 存在 localStorage。
+- 如果未传，后端用账户最近使用 workspace 或第一个 active membership。
+
+JWT payload：
+
+```json
+{
+  "sub": "account_uuid",
+  "email": "user@example.com",
+  "iss": "LangBot-...",
+  "exp": 1234567890
+}
+```
+
+不要把 workspace 写死在 JWT 里，否则切换 workspace 需要刷新 token。可以额外支持短 TTL workspace token，但第一阶段不必。
+
+### 服务层改造模式
+
+所有 service 方法增加 `ctx` 或 `workspace_uuid`：
+
+```python
+async def get_bots(self, ctx: RequestContext, include_secret: bool = True):
+    require(ctx, "bot.view")
+    query = sqlalchemy.select(Bot).where(Bot.workspace_uuid == ctx.workspace_uuid)
+```
+
+需要改造的服务：
+
+- `UserService`：拆成 AccountService + WorkspaceService 更清晰。
+- `ApiKeyService`：按 workspace 管理 key。
+- `BotService`：所有 bot 查询/创建/更新/删除按 workspace。
+- `PipelineService`：所有 pipeline 查询/默认 pipeline 按 workspace。
+- `ModelProviderService` 和 model services：按 workspace 隔离 provider 和 model。
+- `MCPService`：按 workspace 管理 MCP server，运行时按 workspace host。
+- `KnowledgeService/RAGRuntimeService`：按 workspace 管理 KB、文件、collection。
+- `MonitoringService`：记录和查询都带 workspace。
+- `WebhookService`：按 workspace 管理 webhook。
+- `PluginRuntimeConnector`：插件安装、设置、配置按 workspace。
+
+### HTTP API 形态
+
+保留现有路径，靠 `X-Workspace-Id` 表示当前 workspace，可减少前端和 SDK 破坏：
+
+- `GET /api/v1/workspaces`
+- `POST /api/v1/workspaces`
+- `GET /api/v1/workspaces/current`
+- `PUT /api/v1/workspaces/current`
+- `GET /api/v1/workspaces/<workspace_uuid>/members`
+- `POST /api/v1/workspaces/<workspace_uuid>/invitations`
+- `PUT /api/v1/workspaces/<workspace_uuid>/members/<account_uuid>`
+- `DELETE /api/v1/workspaces/<workspace_uuid>/members/<account_uuid>`
+
+现有资源 API：
+
+- `/api/v1/platform/bots`
+- `/api/v1/pipelines`
+- `/api/v1/provider/*`
+- `/api/v1/plugins`
+- `/api/v1/mcp`
+- `/api/v1/knowledge`
+
+继续保留，但必须从 `RequestContext.workspace_uuid` 过滤。
+
+对外 API Key 也使用相同路径，只是由 key 决定 workspace。
+
+### 初始化流程
+
+现有 `/api/v1/user/init` 含义改为“创建首个账号和首个 workspace”：
+
+1. 如果系统没有任何 account：
+   - 创建 account。
+   - 创建 personal/team workspace。
+   - 创建 owner membership。
+   - 创建默认 pipeline。
+   - 标记 wizard status 到该 workspace metadata。
+2. 如果系统已有 account：
+   - 禁止无邀请注册，除非配置允许公开注册。
+   - Space OAuth 登录后，如果没有 membership，引导创建 workspace 或接受邀请。
+
+`/api/v1/user/account-info` 不应再只返回 first user，应返回：
+
+- `initialized`
+- `registration_mode`
+- `space_enabled`
+- `default_login_methods`
+
+登录成功后前端调用 `/api/v1/workspaces` 选择 workspace。
+
+### 运行时隔离
+
+第一阶段采用共享进程 + workspace-aware runtime：
+
+- `RuntimeBot` 增加 `workspace_uuid`。
+- `RuntimePipeline` 增加 `workspace_uuid`。
+- `Query` 增加 `workspace_uuid`，从 bot/pipeline 派生。
+- `SessionManager.get_session()` key 从 `(launcher_type, launcher_id)` 改为 `(workspace_uuid, bot_uuid, launcher_type, launcher_id)`。
+- `PipelineManager.pipeline_dict` key 可保持 pipeline uuid，但所有 load/get 都校验 workspace；如果 uuid 不是全局唯一则改为 `(workspace_uuid, pipeline_uuid)`。
+- `ModelManager` provider/model 加 workspace 过滤；`get_model_by_uuid` 必须确保 query workspace 可访问。
+- `ToolManager` 中 MCP tools、plugin tools 按 query workspace 过滤。
+
+后续规模化时可演进：
+
+- workspace runtime shard：每个 workspace 一套 plugin runtime/MCP runtime。
+- 大客户独立进程或独立数据库。
+
+## Plugin SDK 与 Runtime 改造
+
+### Query/Event 增加 workspace context
+
+SDK `Query` 增加：
+
+- `workspace_uuid: str`
+- `workspace_slug: str | None`
+- `account_uuid: str | None`，仅 Web/API 触发时可能有，聊天平台消息通常为空。
+
+Event 模型通过 `event.query.workspace_uuid` 可拿到租户上下文；序列化时也应包含这些字段。
+
+向后兼容：
+
+- 字段可选，默认 `None`。
+- 老插件不感知这些字段也能跑。
+- 新插件可通过 `ctx.event.query.workspace_uuid` 或新增 `ctx.get_workspace()` 访问。
+
+### Host API 默认按当前 workspace 限制
+
+`LangBotAPIProxy` 的以下方法必须由 Host 端按 workspace 过滤：
+
+- `get_bots`
+- `get_bot_info`
+- `send_message`
+- `get_llm_models`
+- `invoke_llm`
+- `list_plugins_manifest`
+- `list_commands`
+- `list_tools`
+- `call_tool`
+- `invoke_embedding`
+- `vector_*`
+- `list_knowledge_bases`
+- `retrieve_knowledge`
+
+建议新增显式方法：
+
+- `get_workspace_info()`
+- `get_current_account()`
+- `get_workspace_storage(...)`
+
+但不要让插件传入任意 workspace id 来越权访问。插件请求的 workspace 应由 Runtime 根据当前 query/plugin connection 填充。
+
+### Workspace storage 修复
+
+当前 SDK runtime 中：
+
+```python
+data["owner_type"] = "workspace"
+data["owner"] = "default"
+```
+
+必须改为：
+
+- 如果请求来自 query/event：owner 为 `workspace_uuid`。
+- 如果请求来自后台插件任务：owner 为 plugin 安装所属 workspace。
+- Host 侧 `binary_storages` 加 `workspace_uuid`，并在 unique key 中包含 workspace。
+
+Plugin storage 建议也同时加 workspace：
+
+- 现在 plugin storage owner 是 `author/name`，这会导致同一插件在不同 workspace 的私有数据冲突。
+- 应改为 `(workspace_uuid, plugin_id, key)`。
+
+### 插件安装与配置
+
+`plugin_settings` 从全局变为 workspace-scoped：
+
+- 同一个插件可安装到多个 workspace。
+- 每个 workspace 有自己的 enabled、priority、config、install_source、install_info。
+- 插件 runtime 列表需要能按 workspace 过滤。
+
+实现路线有两种：
+
+1. 共享插件进程，插件代码只加载一份，设置和调用时附带 workspace。
+2. 每个 workspace 一个插件容器实例，隔离最彻底但资源占用更高。
+
+推荐第一阶段采用方案 1，但要求：
+
+- 所有 RuntimeToLangBot/PluginToRuntime action 都能携带 `workspace_uuid`。
+- 插件 config 获取时按 workspace 返回。
+- 插件 page API 请求必须校验当前用户在该 workspace 有访问权限。
+
+### MCP
+
+MCP server 是租户资源：
+
+- `mcp_servers.workspace_uuid`。
+- MCP session key 从 `server_name` 改为 `(workspace_uuid, server_name)` 或使用全局 uuid。
+- Pipeline extension preferences 中绑定 MCP server uuid 时，只能绑定同 workspace 的 server。
+- MCP tool 列表在 query 执行时按 query.workspace_uuid + pipeline 绑定关系过滤。
+
+## 前端改造
+
+### Workspace selector
+
+Home layout 顶部或 sidebar 增加 workspace selector：
+
+- 当前 workspace 名称和头像。
+- 切换 workspace 后写入 `localStorage.currentWorkspaceId`。
+- 所有请求自动带 `X-Workspace-Id`。
+- 切换后刷新 sidebar 数据和页面缓存。
+
+`BaseHttpClient` request interceptor 增加：
+
+```ts
+const workspaceId = localStorage.getItem("currentWorkspaceId");
+if (workspaceId) config.headers["X-Workspace-Id"] = workspaceId;
+```
+
+### 用户与成员管理页面
+
+新增页面：
+
+- `/home/workspace/settings`
+- `/home/workspace/members`
+- `/home/workspace/invitations`
+
+能力：
+
+- owner/admin 邀请成员。
+- owner/admin 修改成员角色。
+- owner 移除成员、转让 owner。
+- 所有人可切换 workspace。
+- viewer/operator 在 UI 上隐藏不可操作按钮，但后端仍做权限校验。
+
+### 登录与注册
+
+登录后流程：
+
+1. `authUser` 拿 token。
+2. `initializeUserInfo()` 获取 account info。
+3. `GET /api/v1/workspaces`。
+4. 如果没有 workspace：进入创建 workspace 向导。
+5. 如果有多个 workspace：默认进入最近使用 workspace，可切换。
+
+注册页不再表达“初始化管理员账号”，而是：
+
+- 首次系统启动：创建首个 owner + default workspace。
+- 后续：根据配置允许公开注册，或只能接受邀请。
+
+### 旧页面影响
+
+需要逐个检查这些页面的数据加载是否都依赖当前 workspace：
+
+- Bots
+- Pipelines
+- Plugins/Market/MCP
+- Knowledge
+- Monitoring
+- Models dialog
+- API integration dialog
+- Wizard
+
+## 迁移方案
+
+### 迁移阶段 0：准备
+
+- 引入 `workspaces`、`workspace_memberships`、`workspace_invitations`。
+- 给 `users` 增加 `uuid/status/display_name` 等字段。
+- 创建 `RequestContext`，但先不强制所有服务改完。
+
+### 迁移阶段 1：默认 workspace
+
+对现有实例执行迁移：
+
+1. 创建 `Default Workspace`。
+2. 找到现有第一个 user，设为 owner。
+3. 所有已有资源写入 `workspace_uuid=default_workspace_uuid`。
+4. `metadata` 迁入 default workspace；确实全局的配置放到 `system_metadata`。
+5. `binary_storages` 中 `owner_type=workspace, owner=default` 改为 owner 为 default workspace uuid。
+6. 插件 `plugin_settings` 归入 default workspace。
+
+### 迁移阶段 2：服务层强制 scope
+
+- 改所有 service 查询，必须要求 `workspace_uuid`。
+- API Key 迁移为 workspace key。
+- 所有写操作必须检查权限。
+- 监控和任务查询按 workspace 过滤。
+
+### 迁移阶段 3：运行时上下文
+
+- `Query`、`Session`、`RuntimeBot`、`RuntimePipeline` 增加 workspace。
+- Plugin/MCP/Model/RAG runtime 全部按 workspace 过滤。
+- 修复 SDK workspace storage。
+
+### 迁移阶段 4：前端多 workspace
+
+- 登录后 workspace 选择。
+- Header/sidebar workspace switcher。
+- 成员和邀请管理。
+- 所有 API 请求带 `X-Workspace-Id`。
+
+### 迁移阶段 5：安全收敛
+
+- 添加跨 workspace 越权测试。
+- 添加 API Key scope 测试。
+- 添加插件 Host API 过滤测试。
+- 添加 MCP 和 RAG 隔离测试。
+
+## 安全边界
+
+必须防的场景：
+
+- 用户 A 修改 URL 中 bot uuid，访问用户 B workspace 的 bot。
+- API Key 来自 workspace A，但调用 workspace B 的 bot。
+- 插件通过 `get_bots()` 枚举所有 workspace 的 bot。
+- 插件通过 `workspace_storage` 读取其它 workspace 的数据。
+- MCP server 名称相同导致 session 复用。
+- monitoring session_id 相同导致数据串租户。
+- Space OAuth 登录时，同 email 账户被错误绑定到已有本地 account。
+
+建议策略：
+
+- 所有资源访问都使用 `workspace_uuid + resource_id`。
+- 所有 service 方法入口做权限检查。
+- 插件 Host API 的 workspace 不信任插件入参，只信任 query/runtime connection 上下文。
+- API Key 只授予最小 scope，默认不允许成员管理。
+- owner 角色不能被普通 admin 移除或降权。
+
+## 实施优先级
+
+### P0：基础租户骨架
+
+- Account uuid/status。
+- Workspace / Membership / Invitation。
+- RequestContext。
+- JWT 改为 account uuid。
+- 前端 current workspace header。
+
+### P1：资源行级隔离
+
+- Bots、Pipelines、Models、MCP、Plugins、Knowledge、Monitoring、API Keys 全部加 workspace_uuid。
+- service 查询统一加 workspace filter。
+- 权限矩阵落地。
+
+### P2：运行时隔离
+
+- Query、Session、RuntimeBot、RuntimePipeline 加 workspace。
+- Plugin Host API 和 MCP tools 按 workspace 过滤。
+- SDK workspace storage 从 `default` 改为真实 workspace。
+
+### P3：协作体验
+
+- 邀请成员。
+- 成员列表和角色管理。
+- workspace switcher。
+- 最近使用 workspace。
+
+### P4：SaaS 运维增强
+
+- Workspace 级用量统计。
+- Workspace 级限额：max_bots/max_pipelines/max_extensions/tokens/storage。
+- 审计日志。
+- workspace suspend/delete。
+- 可选自定义角色。
+
+## 测试计划
+
+后端测试：
+
+- 账户可加入多个 workspace。
+- 同账户在不同 workspace 权限不同。
+- viewer 不能创建/修改资源。
+- API Key 只能访问所属 workspace。
+- 所有资源 list/get/update/delete 都不能跨 workspace。
+- 默认 workspace 迁移后旧数据可用。
+
+运行时测试：
+
+- 两个 workspace 使用相同 `launcher_id` 不共享 session。
+- 两个 workspace 使用相同 MCP server name 不共享 MCP session。
+- 插件 `get_bots()` 只能看到当前 workspace bot。
+- 插件 `workspace_storage` 在不同 workspace 读写隔离。
+- Pipeline 只调用当前 workspace 绑定的插件和 MCP tools。
+
+前端测试：
+
+- 登录后自动进入最近 workspace。
+- 切换 workspace 后列表数据变化。
+- 无权限按钮隐藏，直接调用 API 也被后端拒绝。
+- 邀请成员流程完整。
+
+迁移测试：
+
+- SQLite 老实例迁移。
+- PostgreSQL 老实例迁移。
+- 已有 local account 迁移为 default workspace owner。
+- 已有 Space account token 和 Space model provider API key 不丢失。
+
+## 关键实现注意事项
+
+- 不建议在第一版做数据库 schema-per-tenant。LangBot 当前 ORM 和运行时均以单库单表为主，先做 shared schema + workspace_uuid 成本更低。
+- 不建议每个 workspace 立即启动独立 plugin runtime。先共享 runtime，强制 action 带 workspace；大客户隔离可作为后续部署形态。
+- 不要只在前端过滤 workspace。插件、API Key、MCP、RAG 都能绕过前端，必须在后端和运行时层过滤。
+- `metadata` 要拆清楚：wizard status 属于 workspace，系统版本/迁移信息属于 system。
+- `users.user` 用 email 当主键语义不稳，应尽快引入 `account_uuid` 并让 JWT 以 uuid 为准。
+- `plugin_settings` 当前主键没有 workspace，改造时要先改主键/唯一约束，否则同插件无法在多个 workspace 配不同配置。
+
+## 建议落地顺序
+
+1. 新增 workspace/account/membership 表和 RequestContext。
+2. 迁移旧数据到 default workspace。
+3. 改 auth 和前端请求头，让每个请求都有 current workspace。
+4. 从最核心资源开始逐个加 scope：bot -> pipeline -> provider/model -> plugin/MCP -> knowledge -> monitoring。
+5. 改 SDK Query/Event 和 runtime storage。
+6. 上成员管理 UI 和邀请。
+7. 做越权测试和迁移测试。
+
+这个顺序的好处是可以较早让主 UI 在一个 workspace 下继续工作，同时把最危险的跨租户泄露面逐步收紧。

docs/review/mcp-resources-pr-2215-review.md

@@ -0,0 +1,196 @@
+# MCP Resources PR #2215 Review
+
+> 更新日期: 2026-06-29
+> 分支: `mcp_resources`
+> PR: langbot-app/LangBot#2215
+> 主题: MCP Resources 在 LangBot 中的产品价值、AgentRunner 集成方式与后续架构方向
+
+## 结论
+
+PR #2215 对 LangBot 有明确价值：它补齐了 MCP 协议中 Resources 这一重要能力，让 MCP server 不再只暴露 tools，也可以暴露文档、代码片段、配置、日志、图片等上下文资源。管理端可以发现和预览资源，Agent 也可以通过当前实现按需列出和读取资源。
+
+但当前 AgentRunner 层的接入方式更接近一个可用的第一阶段方案，而不是最终架构。现在 MCP Resources 被包装成两个 synthetic tools：
+
+- `langbot_mcp_list_resources`
+- `langbot_mcp_read_resource`
+
+这让模型可以通过 function calling 主动探索资源，落地成本低，也复用了已有 `ToolManager` / `LocalAgentRunner` 的工具调用链路。不过从 MCP 规范和主流实现来看，Resources 更适合作为一种一等上下文来源，而不是长期隐藏在工具列表里。
+
+建议保留当前 synthetic tools 作为探索能力，同时把后续主线设计调整为：MCP Resources 是 pipeline / conversation / message 级别可选择、可固定、可审计的上下文输入。
+
+## 当前实现判断
+
+当前 AgentRunner 集成路径如下：
+
+```text
+Pipeline 绑定 MCP server
+  -> query.variables['_pipeline_bound_mcp_servers']
+  -> Preproc 为 local-agent 加载工具
+  -> ToolManager.get_all_tools()
+  -> MCPLoader 注入 synthetic resource tools
+  -> LocalAgentRunner 将工具 schema 传给模型
+  -> 模型发起 list/read tool call
+  -> ToolManager.execute_func_call()
+  -> MCPLoader 调 MCP session.list_resources/read_resource
+  -> tool result 回灌给模型
+```
+
+这个路径的优点是：
+
+- 复用现有工具调用机制，改动范围小。
+- Agent 可以按需探索资源，不需要每轮预先读取所有资源。
+- 可以沿用 pipeline 绑定的 MCP server 范围，避免越权读取未绑定 server。
+- 对已有 MCP tools 行为影响较小。
+
+主要问题是：
+
+- Resources 在语义上被降级成 tools，和 MCP 规范里的 resource primitive 不完全一致。
+- 模型必须先理解并主动调用 `list/read`，资源不会自然成为上下文。
+- pipeline 不能配置“默认携带某些资源”或“本轮附加某些资源”。
+- UI 资源 tab 目前是管理端预览能力，和 Agent 上下文选择没有打通。
+- 对 blob、图片、大文件、结构化资源的处理还比较粗糙。
+- 缺少 resource templates、订阅更新、缓存、chunk、token budget、trace 与审计策略。
+
+## 主流项目做法
+
+### MCP 官方规范
+
+MCP Resources 是 server 暴露上下文数据的协议能力。规范没有要求 resources 必须以 tool call 形式给模型使用，而是把如何选择、过滤、读取和纳入上下文交给 Host application。
+
+这意味着比较正统的集成方式是：LangBot 作为 Host，在 pipeline、会话或消息层决定哪些 resources 进入模型上下文。
+
+参考: https://modelcontextprotocol.io/specification/2025-06-18/server/resources
+
+### VS Code Copilot
+
+VS Code 把 MCP Resources 做成 chat context 的一部分。用户可以通过 `Add Context > MCP Resources` 或命令浏览 MCP resources，并把选中的资源附加到一次 chat request。
+
+这是目前最值得 LangBot 参考的产品形态：资源不是模型工具，而是用户和 Host 可控的上下文附件。
+
+参考: https://code.visualstudio.com/docs/agent-customization/mcp-servers
+
+### Anthropic SDK
+
+Anthropic 的 client-side MCP helpers 提供资源读取和转换能力，例如把 MCP resource 转为 Claude message content 或 file。也就是说，应用先读取 resource，再显式放进模型消息。
+
+这同样是 application-owned context injection，而不是把 resource 伪装成模型工具。
+
+参考: https://platform.claude.com/docs/en/agents-and-tools/mcp-connector
+
+### LangChain MCP Adapters
+
+LangChain 把 MCP Resources 更像 data loader / document input 来处理，可以把资源加载成 `Blob`，再进入 LangChain 的文档、检索或上下文处理链路。
+
+这说明 Resources 很适合作为知识源、文档源或上下文源，而不只是即时工具调用。
+
+参考: https://docs.langchain.com/oss/python/langchain/mcp
+
+### OpenAI Agents SDK
+
+OpenAI Agents SDK 主路径仍偏向 MCP tools，但底层 MCP server API 已经有 `list_resources`、`list_resource_templates`、`read_resource` 等能力。当前形态说明 resources 是 client 能力，但并未默认变成 agent-visible tools。
+
+参考: https://openai.github.io/openai-agents-python/mcp/
+
+### Cline
+
+Cline 会拉取 MCP tools、resources、resourceTemplates、prompts，并通过类似 `access_mcp_resource` 的内置访问方式让模型读取资源。这个方向和 LangBot 当前 synthetic tools 比较接近。
+
+这种模式适合让 Agent 自主探索，但更像 Host 自定义的模型访问协议，不应成为唯一集成路径。
+
+参考: https://github.com/cline/cline/blob/main/src/services/mcp/McpHub.ts
+
+## 建议架构方向
+
+### 1. 保留探索型工具
+
+保留当前两个 synthetic tools：
+
+- `langbot_mcp_list_resources`
+- `langbot_mcp_read_resource`
+
+它们适合处理“用户没有显式选择资源，但 Agent 判断需要探索 MCP server 上下文”的场景。后续可以优化工具描述、返回格式、资源大小限制和错误信息。
+
+### 2. 增加一等 Resource Context
+
+新增一个 Host 层资源上下文概念，例如：
+
+```text
+PipelineResourceBinding
+ConversationResourceAttachment
+MessageResourceAttachment
+```
+
+Preproc 或独立的 `ResourceContextProvider` 在模型调用前读取这些资源，按 MIME 类型、大小、token budget 转为模型可消费的上下文。
+
+### 3. 打通 UI 与 Agent 上下文
+
+当前 MCP 详情页的 Resources tab 可以继续作为资源发现和预览入口。建议增加操作：
+
+- 添加到本轮上下文
+- 固定到当前 pipeline
+- 固定到当前 bot / conversation
+- 查看资源读取历史和错误
+
+这样 UI 资源管理能力才能真正影响 Agent 行为。
+
+### 4. 支持 resource templates
+
+MCP resource templates 允许 server 暴露参数化资源，例如：
+
+```text
+repo://{owner}/{repo}/file/{path}
+log://{service}/{date}
+```
+
+LangBot 后续应支持模板发现、参数填写、实例化和绑定。否则只能使用静态 resources，覆盖面会受限。
+
+### 5. 增加资源处理策略
+
+建议补齐：
+
+- 文本资源 token budget 与截断策略。
+- 大文件 chunk 与摘要策略。
+- 图片/blob 的模型能力判断与 fallback。
+- MIME 类型白名单与安全限制。
+- 缓存与过期策略。
+- `resources/listChanged` 或订阅更新。
+- resource read trace，便于审计 Agent 读取了什么上下文。
+
+## 推荐落地顺序
+
+### Phase 1: 完成当前 PR 可用性
+
+- 保留 synthetic tools。
+- 明确文档说明当前 Agent 集成是 tool-mediated。
+- 完善资源工具描述，降低模型误用概率。
+- 给 read/list 增加大小限制和更清晰的 MIME 处理。
+- 前端 Resources tab 与 Tools tab 分离，保持管理端清晰。
+
+### Phase 2: 做 Host-owned context attachments
+
+- 在 pipeline 或 conversation 层新增 resource attachment 配置。
+- Preproc 读取已绑定 resources，注入模型上下文。
+- UI 支持“添加到上下文 / 固定到 pipeline”。
+- 记录每轮实际注入的 resource URI 和 token 消耗。
+
+### Phase 3: 做完整 MCP Resources 能力
+
+- 支持 resource templates。
+- 支持资源订阅更新。
+- 支持 chunk、summary、RAG 化接入。
+- 为 DifyAgentRunner、LocalAgentRunner 等不同 runner 定义统一资源上下文接口。
+
+## 最终建议
+
+PR #2215 可以作为 MCP Resources 的第一阶段实现继续推进。它让 LangBot 快速拥有“资源发现、预览、按需读取”的闭环，也给 Agent 探索资源提供了可运行路径。
+
+但在正式设计上，不建议把 “Resources == Tools” 固化为长期抽象。LangBot 更应该把 MCP Resources 定位为上下文来源，与 tools、prompts、knowledge base 并列：
+
+```text
+Tools      -> Agent 可以执行的动作
+Resources  -> Host/用户/Agent 可以选择的上下文数据
+Prompts    -> 可复用的任务模板
+Knowledge  -> 可检索、可索引的长期知识
+```
+
+这样既尊重 MCP 协议语义，也能让 LangBot 在 Agent 工作流、企业知识接入和多 MCP server 管理上走得更稳。

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "langbot"
-version = "4.10.4"
+version = "4.10.5"
 description = "Production-grade platform for building agentic IM bots"
 readme = "README.md"
 license-files = ["LICENSE"]
@@ -70,7 +70,7 @@ dependencies = [
     "chromadb>=1.0.0,<2.0.0",
     "qdrant-client (>=1.15.1,<2.0.0)",
     "pyseekdb==1.1.0.post3",
-    "langbot-plugin==0.4.6",
+    "langbot-plugin==0.4.13",
     "asyncpg>=0.30.0",
     "line-bot-sdk>=3.19.0",
     "matrix-nio>=0.25.2",
@@ -80,6 +80,7 @@ dependencies = [
     "pgvector>=0.4.1",
     "botocore>=1.42.39",
     "litellm>=1.0.0",
+    "valkey-glide>=2.4.1,<3.0.0",
 ]
 keywords = [
     "bot",

skills/README.md

@@ -26,7 +26,7 @@ and LangBot's own Local Agent) working with the LangBot ecosystem.
 
 ## Quick start (for an AI agent)
 
-1. Read this README, `AGENTS.md`, and `qa-agent-docs/` to understand the layout.
+1. Read this README, `AGENTS.md`, and `docs/user-guide.md` to understand the layout.
 2. Read `skills/.env` for shared local defaults. On a new machine, copy
    `skills/.env.example` to `skills/.env.local` (gitignored) and override
    machine-specific values there. Never commit secrets.
@@ -48,6 +48,7 @@ bin/lbs env show     # inspect resolved env defaults (redacted)
 bin/lbs env doctor   # diagnose local environment readiness
 bin/lbs case list --ready
 bin/lbs test plan <case-id>
+bin/lbs suite plan langbot-debug-chat-load-gate
 ```
 
 ## Maintenance rule

skills/docs/user-guide.md

@@ -0,0 +1,171 @@
+# LangBot QA Skills User Guide
+
+Use this guide as the first operational path after reading `README.md` and
+`AGENTS.md`.
+
+## 1. Configure Local Inputs
+
+Read `skills/.env`, then create `skills/.env.local` for machine-local values.
+Do not commit `.env.local`, browser profiles, reports, tokens, API keys, OAuth
+state, or provider credentials.
+
+Minimum local fields for live browser QA:
+
+```bash
+LANGBOT_REPO=/path/to/LangBot
+LANGBOT_WEB_REPO=/path/to/LangBot/web
+LANGBOT_BACKEND_URL=http://127.0.0.1:5300
+LANGBOT_FRONTEND_URL=http://127.0.0.1:3000
+LANGBOT_DEV_FRONTEND_URL=http://127.0.0.1:3000
+LANGBOT_BROWSER_PROFILE=/path/to/langbot-browser-profile
+LANGBOT_CHROMIUM_EXECUTABLE=/path/to/chromium-or-playwright-chrome
+LANGBOT_E2E_LOGIN_USER=qa-local@example.com
+```
+
+`LANGBOT_E2E_LOGIN_USER` is a local QA account. The setup automation uses the
+LangBot recovery key from the active checkout to initialize or refresh that
+local account and write a browser `localStorage` token. It does not need the
+user's GitHub or Space credentials.
+
+## 2. Check Readiness
+
+From `skills/`:
+
+```bash
+bin/lbs env show
+bin/lbs env doctor
+bin/lbs validate
+bin/lbs index --check
+```
+
+`env doctor` should report reachable backend and frontend URLs before live
+browser cases are run. Missing Space provider credentials are not a LangBot
+product pass; classify them as `env_issue` and configure the local Space
+provider before measuring Debug Chat performance.
+
+## 3. Start Services
+
+Start the backend from `LANGBOT_REPO`:
+
+```bash
+cd "$LANGBOT_REPO"
+uv run main.py
+```
+
+Start the standalone frontend from `LANGBOT_WEB_REPO` and point it at the
+backend:
+
+```bash
+cd "$LANGBOT_WEB_REPO"
+VITE_API_BASE_URL="$LANGBOT_BACKEND_URL" pnpm dev --host 0.0.0.0
+```
+
+If `VITE_API_BASE_URL` is missing, browser tests can load the Vite page but send
+API requests to the frontend port, which produces false UI failures.
+
+## 4. Prepare User-Path Fixtures
+
+For local-agent Debug Chat cases and the user-path performance gate:
+
+```bash
+node scripts/e2e/ensure-local-agent-pipeline.mjs --write-env
+```
+
+The script:
+
+- refreshes the local QA login and browser token;
+- marks the local wizard as skipped;
+- creates or updates a local QA pipeline;
+- scans Space LLM models, tests candidates, and switches to the first working
+  Space model with tested fallback models;
+- writes `LANGBOT_PIPELINE_URL`, `LANGBOT_PIPELINE_NAME`, and local-agent
+  pipeline/model variables into `skills/.env.local`;
+- returns `env_issue` when no Space model can be scanned or tested.
+
+Useful model controls:
+
+```bash
+LANGBOT_E2E_MODEL_TEST_LIMIT=8
+LANGBOT_E2E_MODEL_FALLBACK_COUNT=3
+LANGBOT_E2E_SKIP_MODEL_UUIDS=uuid-a,uuid-b
+LANGBOT_E2E_SKIP_MODEL_NAMES=model-a,model-b
+LANGBOT_E2E_SCAN_SPACE_MODELS=true
+```
+
+The setup writes a current-runtime compatibility `max-round` value into the
+pipeline config because this backend still reads that field directly during
+message truncation. Do not treat it as a long-term QA contract.
+
+## 5. Run Gates
+
+Fast contract gate, no live service required:
+
+```bash
+bin/lbs suite run langbot-performance-contract-gate --run-id langbot-contract-local
+```
+
+Live backend gate:
+
+```bash
+bin/lbs suite run langbot-live-backend-gate --run-id langbot-backend-local
+```
+
+Browser-visible user-path performance gate:
+
+```bash
+bin/lbs suite plan langbot-user-path-performance-gate
+bin/lbs suite run langbot-user-path-performance-gate --run-id langbot-user-path-local --include-manual-check
+```
+
+Controlled Debug Chat message-path load gate (manual/non-required; run fake-provider cases serially when they share `LANGBOT_FAKE_PROVIDER_URL`):
+
+```bash
+bin/lbs suite plan langbot-debug-chat-load-gate
+bin/lbs test run langbot-fake-provider-debug-chat-load --run-id langbot-fake-load-local
+bin/lbs test run langbot-fake-provider-debug-chat-slow-load --run-id langbot-fake-slow-local
+bin/lbs test run langbot-fake-provider-debug-chat-fault-recovery --run-id langbot-fake-fault-local
+bin/lbs test run langbot-space-debug-chat-concurrency-smoke --run-id langbot-space-smoke-local
+```
+
+Cross-pipeline Debug Chat isolation is a separate manual regression gate because
+current releases may fail it due to product bug #2286:
+
+```bash
+bin/lbs suite plan langbot-debug-chat-isolation-gate
+bin/lbs suite run langbot-debug-chat-isolation-gate --run-id langbot-debug-chat-isolation-local --include-manual-check
+```
+
+Start with `langbot-fake-provider-debug-chat-load`. It launches a local
+OpenAI-compatible fake provider, creates the matching provider/model/pipeline,
+then sends concurrent WebSocket Debug Chat messages through the real backend.
+Use `langbot-fake-provider-debug-chat-slow-load` to measure the same path under
+deterministic streaming latency. Use
+`langbot-fake-provider-debug-chat-fault-recovery` to inject bounded provider
+HTTP failures and confirm later Debug Chat requests recover. Use the separate
+`langbot-debug-chat-isolation-gate` to verify that concurrent Debug Chat traffic
+on two pipelines does not leak assistant responses across pipeline boundaries;
+current releases may fail that gate because of #2286, so keep it out of the
+normal load gate until the product fix lands.
+Use `langbot-space-debug-chat-concurrency-smoke` only as a low-volume live
+provider smoke; it includes Space/model/network latency and should be compared
+against the fake-provider baseline before attributing failures to LangBot.
+
+`manual_check` means the agent must confirm the declared preconditions for that
+run window. When setup automation is declared, run output may stop early with
+`env_issue`; fix that environment input before treating the product path as
+measured.
+
+## 6. Read Results
+
+Suite reports live under `skills/reports/`. Evidence lives under
+`skills/reports/evidence/<run-id>/`.
+
+For performance cases, inspect:
+
+- `metrics.json` for p50/p95/p99, error rate, and total duration;
+- `automation-result.json` for threshold decisions and artifacts;
+- `console.log` and `network.log` for frontend/API failures;
+- backend logs for provider, runner, WebSocket, or persistence failures.
+
+Do not call a user-path performance result a LangBot overhead regression until
+provider/tool/network time has been separated or ruled out.

skills/schemas/case.schema.json

@@ -48,7 +48,18 @@
     },
     "type": {
       "type": "string",
-      "enum": ["smoke", "regression", "feature", "provider", "exploratory"]
+      "enum": [
+        "smoke",
+        "regression",
+        "feature",
+        "provider",
+        "exploratory",
+        "contract",
+        "performance",
+        "reliability",
+        "chaos",
+        "security"
+      ]
     },
     "priority": {
       "type": "string",
@@ -102,7 +113,11 @@
           "backend_log",
           "frontend_log",
           "api_diagnostic",
-          "filesystem"
+          "filesystem",
+          "metrics",
+          "trace",
+          "profile",
+          "resource_log"
         ]
       },
       "minItems": 1
@@ -188,9 +203,101 @@
       "type": "string",
       "enum": ["person", "group"]
     },
+    "automation_debug_chat_response_p95_ms": {
+      "type": "string"
+    },
+    "automation_debug_chat_max_error_rate": {
+      "type": "string"
+    },
+    "automation_debug_chat_load_requests": {
+      "type": "string"
+    },
+    "automation_debug_chat_load_concurrency": {
+      "type": "string"
+    },
+    "automation_debug_chat_load_timeout_ms": {
+      "type": "string"
+    },
+    "automation_debug_chat_load_response_p95_ms": {
+      "type": "string"
+    },
+    "automation_debug_chat_load_first_response_p95_ms": {
+      "type": "string"
+    },
+    "automation_debug_chat_load_max_error_rate": {
+      "type": "string"
+    },
+    "automation_debug_chat_load_min_error_rate": {
+      "type": "string"
+    },
+    "automation_debug_chat_load_min_error_count": {
+      "type": "string"
+    },
+    "automation_debug_chat_load_min_ok_count": {
+      "type": "string"
+    },
+    "automation_debug_chat_load_min_provider_fault_count": {
+      "type": "string"
+    },
+    "automation_debug_chat_load_expected_prefix": {
+      "type": "string"
+    },
+    "automation_debug_chat_load_prompt_template": {
+      "type": "string"
+    },
+    "automation_debug_chat_load_stream": {
+      "type": "string",
+      "enum": ["0", "1", "false", "true"]
+    },
+    "automation_debug_chat_load_reset": {
+      "type": "string",
+      "enum": ["0", "1", "false", "true"]
+    },
+    "automation_debug_chat_load_fail_on_final_mismatch": {
+      "type": "string",
+      "enum": ["0", "1", "false", "true"]
+    },
+    "automation_fake_provider_response_text": {
+      "type": "string"
+    },
+    "automation_fake_provider_first_token_delay_ms": {
+      "type": "string"
+    },
+    "automation_fake_provider_chunk_delay_ms": {
+      "type": "string"
+    },
+    "automation_fake_provider_chunk_count": {
+      "type": "string"
+    },
+    "automation_fake_provider_fail_first_n": {
+      "type": "string"
+    },
+    "automation_fake_provider_fail_every_n": {
+      "type": "string"
+    },
+    "automation_fake_provider_fault_status": {
+      "type": "string"
+    },
+    "automation_fake_provider_fail_after_first_chunk": {
+      "type": "string",
+      "enum": ["0", "1", "false", "true"]
+    },
+    "automation_fake_provider_dynamic_response": {
+      "type": "string",
+      "enum": ["0", "1", "false", "true"]
+    },
     "automation_filesystem_checks_json": {
       "type": "string"
     },
+    "metrics_thresholds_json": {
+      "type": "string"
+    },
+    "load_profile_json": {
+      "type": "string"
+    },
+    "fault_model_json": {
+      "type": "string"
+    },
     "automation_pipeline_url_env": {
       "type": "string",
       "pattern": "^[A-Z][A-Z0-9_]*$"

skills/schemas/suite.schema.json

@@ -18,7 +18,17 @@
     },
     "type": {
       "type": "string",
-      "enum": ["smoke", "regression", "release_gate", "exploratory"]
+      "enum": [
+        "smoke",
+        "regression",
+        "release_gate",
+        "exploratory",
+        "contract",
+        "performance",
+        "reliability",
+        "chaos",
+        "security"
+      ]
     },
     "priority": {
       "type": "string",

skills/scripts/e2e/ensure-fake-provider-cross-pipelines.mjs

@@ -0,0 +1,205 @@
+#!/usr/bin/env node
+
+import { spawn } from "node:child_process";
+import { mkdir, readFile, writeFile } from "node:fs/promises";
+import { dirname, resolve } from "node:path";
+import { env } from "node:process";
+import {
+  appendLine,
+  ensureEvidence,
+  evidencePaths,
+  loadEnvFiles,
+  redact,
+  writeResult,
+} from "./lib/langbot-e2e.mjs";
+
+const caseId = "ensure-fake-provider-cross-pipelines";
+const DEFAULT_PIPELINE_A_NAME = "LangBot QA Fake Provider Debug Chat A";
+const DEFAULT_PIPELINE_B_NAME = "LangBot QA Fake Provider Debug Chat B";
+
+await loadEnvFiles();
+const paths = evidencePaths(caseId);
+await ensureEvidence(paths);
+
+const writeEnv = process.argv.includes("--write-env");
+const envLocalPath = resolve("skills/.env.local");
+const pipelineAName = env.LANGBOT_FAKE_PROVIDER_PIPELINE_A_NAME || DEFAULT_PIPELINE_A_NAME;
+const pipelineBName = env.LANGBOT_FAKE_PROVIDER_PIPELINE_B_NAME || DEFAULT_PIPELINE_B_NAME;
+
+const result = {
+  source: "setup_automation",
+  case_id: caseId,
+  run_id: paths.runId,
+  status: "fail",
+  reason: "",
+  pipeline_a: {
+    name: pipelineAName,
+    id: "",
+    url: "",
+  },
+  pipeline_b: {
+    name: pipelineBName,
+    id: "",
+    url: "",
+  },
+  fake_provider: {
+    url: "",
+    base_url: "",
+    pid: null,
+  },
+  wrote_env: false,
+  evidence: {
+    console_log: paths.consoleLog,
+    automation_result_json: paths.automationResultJson,
+    result_json: paths.resultJson,
+  },
+  evidence_collected: ["api_diagnostic", "filesystem"],
+};
+
+try {
+  console.error(`[langbot-qa] configuring cross-pipeline QA fixtures: pipeline_a=\"${pipelineAName}\", pipeline_b=\"${pipelineBName}\"`);
+  console.error("[langbot-qa] run these fake-provider setup/probe commands serially when they share LANGBOT_FAKE_PROVIDER_URL.");
+  if (pipelineAName === pipelineBName) {
+    throw new Error("LANGBOT_FAKE_PROVIDER_PIPELINE_A_NAME and LANGBOT_FAKE_PROVIDER_PIPELINE_B_NAME must be different.");
+  }
+
+  const setupA = await runPipelineSetup(pipelineAName, "A");
+  const setupB = await runPipelineSetup(pipelineBName, "B");
+  result.pipeline_a = {
+    name: setupA.pipeline_name || pipelineAName,
+    id: setupA.pipeline_id || "",
+    url: setupA.pipeline_url || "",
+  };
+  result.pipeline_b = {
+    name: setupB.pipeline_name || pipelineBName,
+    id: setupB.pipeline_id || "",
+    url: setupB.pipeline_url || "",
+  };
+  result.fake_provider = {
+    url: setupB.fake_provider?.url || setupA.fake_provider?.url || "",
+    base_url: setupB.fake_provider?.base_url || setupA.fake_provider?.base_url || "",
+    pid: setupB.fake_provider?.pid ?? setupA.fake_provider?.pid ?? null,
+  };
+
+  if (!result.pipeline_a.url || !result.pipeline_b.url || !result.fake_provider.url) {
+    throw new Error("Cross-pipeline fake provider setup did not return both pipeline URLs and provider URL.");
+  }
+
+  if (writeEnv) {
+    await upsertEnvLocal(envLocalPath, {
+      LANGBOT_FAKE_PROVIDER_URL: result.fake_provider.url,
+      LANGBOT_FAKE_PROVIDER_BASE_URL: result.fake_provider.base_url,
+      LANGBOT_FAKE_PROVIDER_PID: result.fake_provider.pid ? String(result.fake_provider.pid) : "",
+      LANGBOT_FAKE_PROVIDER_PIPELINE_A_URL: result.pipeline_a.url,
+      LANGBOT_FAKE_PROVIDER_PIPELINE_A_NAME: result.pipeline_a.name,
+      LANGBOT_FAKE_PROVIDER_PIPELINE_B_URL: result.pipeline_b.url,
+      LANGBOT_FAKE_PROVIDER_PIPELINE_B_NAME: result.pipeline_b.name,
+    });
+    result.wrote_env = true;
+  }
+
+  result.status = "pass";
+  result.reason = "Fake provider cross-pipeline fixtures are configured.";
+} catch (error) {
+  result.status = looksLikeEnvIssue(error) ? "env_issue" : "fail";
+  result.reason = safeReason(error.message);
+} finally {
+  await writeResult(paths, result);
+  console.log(JSON.stringify(result, null, 2));
+}
+
+process.exit(result.status === "pass" ? 0 : result.status === "env_issue" ? 2 : 1);
+
+function runPipelineSetup(pipelineName, label) {
+  return new Promise((resolvePromise, rejectPromise) => {
+    const child = spawn(process.execPath, ["scripts/e2e/ensure-fake-provider-pipeline.mjs"], {
+      cwd: resolve("."),
+      env: {
+        ...env,
+        LANGBOT_FAKE_PROVIDER_PIPELINE_NAME: pipelineName,
+        LANGBOT_FAKE_PROVIDER_FIRST_TOKEN_DELAY_MS: env.LANGBOT_FAKE_PROVIDER_FIRST_TOKEN_DELAY_MS || "25",
+        LANGBOT_FAKE_PROVIDER_CHUNK_DELAY_MS: env.LANGBOT_FAKE_PROVIDER_CHUNK_DELAY_MS || "10",
+        LANGBOT_FAKE_PROVIDER_CHUNK_COUNT: env.LANGBOT_FAKE_PROVIDER_CHUNK_COUNT || "0",
+        LANGBOT_FAKE_PROVIDER_FAIL_FIRST_N: "0",
+        LANGBOT_FAKE_PROVIDER_FAIL_EVERY_N: "0",
+        LANGBOT_FAKE_PROVIDER_FAULT_STATUS: env.LANGBOT_FAKE_PROVIDER_FAULT_STATUS || "500",
+        LANGBOT_FAKE_PROVIDER_FAIL_AFTER_FIRST_CHUNK: "false",
+        LANGBOT_FAKE_PROVIDER_DYNAMIC_RESPONSE: "true",
+      },
+      stdio: ["ignore", "pipe", "pipe"],
+    });
+
+    let stdout = "";
+    let stderr = "";
+    child.stdout.on("data", (chunk) => {
+      const text = chunk.toString();
+      stdout += text;
+      appendLine(paths.consoleLog, `[setup ${label} stdout] ${text.trimEnd()}`).catch(() => {});
+    });
+    child.stderr.on("data", (chunk) => {
+      const text = chunk.toString();
+      stderr += text;
+      appendLine(paths.consoleLog, `[setup ${label} stderr] ${text.trimEnd()}`).catch(() => {});
+    });
+    child.on("error", rejectPromise);
+    child.on("close", (code) => {
+      const parsed = parseJsonOutput(stdout);
+      if (code !== 0 || parsed.status !== "pass") {
+        rejectPromise(new Error(parsed.reason || stderr || `Fake provider pipeline setup ${label} exited with ${code}.`));
+        return;
+      }
+      resolvePromise(parsed);
+    });
+  });
+}
+
+function parseJsonOutput(text) {
+  const trimmed = String(text || "").trim();
+  if (!trimmed) return {};
+  try {
+    return JSON.parse(trimmed);
+  } catch {
+    const start = trimmed.indexOf("{");
+    const end = trimmed.lastIndexOf("}");
+    if (start >= 0 && end > start) {
+      try {
+        return JSON.parse(trimmed.slice(start, end + 1));
+      } catch {
+        return {};
+      }
+    }
+    return {};
+  }
+}
+
+async function upsertEnvLocal(path, updates) {
+  await mkdir(dirname(path), { recursive: true });
+  let text = "";
+  try {
+    text = await readFile(path, "utf8");
+  } catch {
+    text = "";
+  }
+  const lines = text.split(/\r?\n/);
+  const seen = new Set();
+  const next = lines.map((line) => {
+    const trimmed = line.trim();
+    const match = trimmed.match(/^([A-Z][A-Z0-9_]*)=/);
+    if (!match || updates[match[1]] === undefined) return line;
+    seen.add(match[1]);
+    return `${match[1]}=${updates[match[1]]}`;
+  });
+  for (const [key, value] of Object.entries(updates)) {
+    if (!seen.has(key)) next.push(`${key}=${value}`);
+  }
+  await writeFile(path, `${next.join("\n").replace(/\n+$/, "")}\n`, "utf8");
+}
+
+function looksLikeEnvIssue(error) {
+  const message = String(error?.message || error || "");
+  return /fetch failed|ECONNREFUSED|ENOTFOUND|LANGBOT_.*not configured|Could not read recovery_key|Backend did not respond/i.test(message);
+}
+
+function safeReason(value) {
+  return redact(String(value || "")).slice(0, 1000);
+}

skills/scripts/e2e/ensure-fake-provider-pipeline.mjs

@@ -0,0 +1,635 @@
+#!/usr/bin/env node
+
+import { spawn } from "node:child_process";
+import { open, readFile, mkdir, writeFile } from "node:fs/promises";
+import { dirname, resolve } from "node:path";
+import { env } from "node:process";
+import {
+  apiJson,
+  ensureEvidence,
+  evidencePaths,
+  loadEnvFiles,
+  redact,
+  resetAndAuthLocalUser,
+  writeResult,
+} from "./lib/langbot-e2e.mjs";
+
+const RUNNER_ID = "local-agent";
+const DEFAULT_LOCAL_PASSWORD = "LangBotE2ELocalPass!2026";
+const DEFAULT_PIPELINE_NAME = "LangBot QA Fake Provider Debug Chat";
+const DEFAULT_PROVIDER_NAME = "LangBot QA Fake OpenAI Provider";
+const QA_RESOURCE_DESCRIPTION = "Managed by LangBot skills QA automation for controlled fake-provider Debug Chat tests. Safe to delete when local QA fixtures are no longer needed.";
+const DEFAULT_MODEL_NAME = "gpt-4o-mini";
+const DEFAULT_REQUESTER = "openai-chat-completions";
+
+const caseId = "ensure-fake-provider-pipeline";
+
+await loadEnvFiles();
+const paths = evidencePaths(caseId);
+await ensureEvidence(paths);
+
+const writeEnv = process.argv.includes("--write-env");
+const frontendUrl = env.LANGBOT_FRONTEND_URL || "";
+const backendUrl = env.LANGBOT_BACKEND_URL || "";
+const envLocalPath = resolve("skills/.env.local");
+const repoRoot = resolve(env.LANGBOT_REPO || "..");
+const fakeStateDir = resolve(env.LANGBOT_FAKE_PROVIDER_STATE_DIR || resolve(repoRoot, ".qa/fake-provider"));
+const fakeStatePath = resolve(fakeStateDir, "state.json");
+const fakeStdoutPath = resolve(fakeStateDir, "fake-provider.stdout.log");
+const fakeStderrPath = resolve(fakeStateDir, "fake-provider.stderr.log");
+const pipelineName = env.LANGBOT_FAKE_PROVIDER_PIPELINE_NAME || DEFAULT_PIPELINE_NAME;
+const providerName = env.LANGBOT_FAKE_PROVIDER_NAME || DEFAULT_PROVIDER_NAME;
+const requester = env.LANGBOT_FAKE_PROVIDER_REQUESTER || DEFAULT_REQUESTER;
+const modelName = env.LANGBOT_FAKE_PROVIDER_MODEL_NAME || DEFAULT_MODEL_NAME;
+
+const result = {
+  source: "automation",
+  case_id: caseId,
+  run_id: paths.runId,
+  status: "fail",
+  reason: "",
+  frontend_url: frontendUrl,
+  backend_url: backendUrl,
+  fake_provider: {
+    url: "",
+    base_url: "",
+    pid: null,
+    reused: false,
+    config: {},
+    state_file: fakeStatePath,
+    stdout_log: fakeStdoutPath,
+    stderr_log: fakeStderrPath,
+  },
+  provider: {
+    uuid: "",
+    name: providerName,
+    requester,
+    created: false,
+    updated: false,
+  },
+  model: {
+    uuid: "",
+    name: modelName,
+    created: false,
+    updated: false,
+    test_status: "not_run",
+    test_reason: "",
+  },
+  pipeline_id: "",
+  pipeline_name: pipelineName,
+  pipeline_url: "",
+  created: false,
+  updated: false,
+  wrote_env: false,
+  evidence: {
+    console_log: paths.consoleLog,
+    network_log: paths.networkLog,
+    automation_result_json: paths.automationResultJson,
+    result_json: paths.resultJson,
+  },
+  evidence_collected: ["api_diagnostic", "network", "filesystem"],
+};
+
+try {
+  console.error(`[langbot-qa] configuring QA-owned fake-provider fixtures: provider=\"${providerName}\", pipeline=\"${pipelineName}\"`);
+  console.error("[langbot-qa] this setup may create or update local QA provider/model/pipeline resources on the selected backend.");
+  if (!backendUrl) {
+    result.status = "env_issue";
+    throw new Error("LANGBOT_BACKEND_URL is not configured.");
+  }
+  if (!frontendUrl) {
+    result.status = "env_issue";
+    throw new Error("LANGBOT_FRONTEND_URL is not configured.");
+  }
+
+  const fakeProvider = await ensureFakeProvider();
+  const setupConfig = await configureFakeProvider(fakeProvider.url, healthyFakeProviderConfig(), true);
+  result.fake_provider = {
+    ...result.fake_provider,
+    ...fakeProvider,
+    config: setupConfig.config || healthyFakeProviderConfig(),
+  };
+
+  const user = env.LANGBOT_E2E_LOGIN_USER || "";
+  const password = env.LANGBOT_E2E_LOGIN_PASSWORD || DEFAULT_LOCAL_PASSWORD;
+  if (!user) {
+    result.status = "env_issue";
+    throw new Error("LANGBOT_E2E_LOGIN_USER is required so this setup can create/update the fake provider pipeline.");
+  }
+
+  const auth = await resetAndAuthLocalUser({ backendUrl, user, password });
+  const wizard = await skipWizard({ backendUrl, token: auth.token });
+  if (wizard.status !== "pass") {
+    result.status = "fail";
+    throw new Error(wizard.reason || "Failed to mark the local QA wizard as skipped.");
+  }
+
+  const provider = await ensureProvider({
+    backendUrl,
+    token: auth.token,
+    name: providerName,
+    requester,
+    baseUrl: fakeProvider.base_url,
+  });
+  result.provider = provider;
+
+  const model = await ensureModel({
+    backendUrl,
+    token: auth.token,
+    providerUuid: provider.uuid,
+    name: modelName,
+  });
+  result.model = model;
+
+  const pipeline = await ensurePipeline({
+    backendUrl,
+    token: auth.token,
+    name: pipelineName,
+    modelUuid: model.uuid,
+  });
+  Object.assign(result, pipeline);
+  result.pipeline_url = `${frontendUrl.replace(/\/$/, "")}/home/pipelines?id=${encodeURIComponent(pipeline.pipeline_id)}`;
+
+  const runConfig = await configureFakeProvider(fakeProvider.url, targetFakeProviderConfig(), true);
+  result.fake_provider.config = runConfig.config || targetFakeProviderConfig();
+
+  if (writeEnv) {
+    await upsertEnvLocal(envLocalPath, {
+      LANGBOT_E2E_LOGIN_USER: user,
+      LANGBOT_FAKE_PROVIDER_URL: fakeProvider.url,
+      LANGBOT_FAKE_PROVIDER_BASE_URL: fakeProvider.base_url,
+      LANGBOT_FAKE_PROVIDER_PID: fakeProvider.pid ? String(fakeProvider.pid) : "",
+      LANGBOT_FAKE_PROVIDER_PROVIDER_UUID: provider.uuid,
+      LANGBOT_FAKE_PROVIDER_MODEL_UUID: model.uuid,
+      LANGBOT_FAKE_PROVIDER_PIPELINE_URL: result.pipeline_url,
+      LANGBOT_FAKE_PROVIDER_PIPELINE_NAME: pipelineName,
+    });
+    result.wrote_env = true;
+  }
+
+  result.status = "pass";
+  result.reason = `Fake provider pipeline is configured with ${requester}/${modelName}.`;
+} catch (error) {
+  result.status = result.status === "env_issue" ? "env_issue" : "fail";
+  result.reason = result.reason || safeReason(error.message);
+} finally {
+  await writeResult(paths, result);
+  console.log(JSON.stringify(result, null, 2));
+}
+
+process.exit(result.status === "pass" ? 0 : result.status === "env_issue" ? 2 : 1);
+
+async function ensureFakeProvider() {
+  const envUrl = normalizeProviderRootUrl(env.LANGBOT_FAKE_PROVIDER_URL || "");
+  if (envUrl && await fakeProviderHealthy(envUrl) && await fakeProviderConfigurable(envUrl)) {
+    return {
+      url: envUrl,
+      base_url: `${envUrl}/v1`,
+      pid: null,
+      reused: true,
+    };
+  }
+
+  const state = await readState(fakeStatePath);
+  const stateUrl = normalizeProviderRootUrl(state.url || "");
+  if (stateUrl && await fakeProviderHealthy(stateUrl)) {
+    if (await fakeProviderConfigurable(stateUrl)) {
+      return {
+        url: stateUrl,
+        base_url: state.base_url || `${stateUrl}/v1`,
+        pid: Number.isInteger(state.pid) ? state.pid : null,
+        reused: true,
+      };
+    }
+    if (Number.isInteger(state.pid)) await stopProcess(state.pid);
+  }
+
+  await mkdir(fakeStateDir, { recursive: true });
+  await writeFile(fakeStatePath, `${JSON.stringify({ status: "starting", started_at: new Date().toISOString() }, null, 2)}\n`, "utf8");
+  const stdout = await open(fakeStdoutPath, "a");
+  const stderr = await open(fakeStderrPath, "a");
+  const scriptPath = resolve("scripts/e2e/fake-openai-provider.mjs");
+  const host = env.LANGBOT_FAKE_PROVIDER_HOST || "127.0.0.1";
+  const port = env.LANGBOT_FAKE_PROVIDER_PORT || "0";
+  const child = spawn(process.execPath, [
+    scriptPath,
+    `--host=${host}`,
+    `--port=${port}`,
+    `--state-file=${fakeStatePath}`,
+  ], {
+    cwd: resolve("."),
+    detached: true,
+    env: {
+      ...env,
+      LANGBOT_FAKE_PROVIDER_MODEL_NAME: modelName,
+    },
+    stdio: ["ignore", stdout.fd, stderr.fd],
+  });
+  child.unref();
+  await stdout.close();
+  await stderr.close();
+
+  const started = await waitForFakeProviderState(fakeStatePath, child.pid, 10_000);
+  if (!started.url || !await fakeProviderHealthy(started.url) || !await fakeProviderConfigurable(started.url)) {
+    throw new Error(`Fake provider did not become healthy. See ${fakeStderrPath}`);
+  }
+
+  return {
+    url: started.url,
+    base_url: started.base_url || `${started.url}/v1`,
+    pid: child.pid ?? started.pid ?? null,
+    reused: false,
+  };
+}
+
+async function configureFakeProvider(rootUrl, config, resetRequestCount) {
+  const response = await fetch(`${normalizeProviderRootUrl(rootUrl)}/__qa/config`, {
+    method: "POST",
+    headers: { "content-type": "application/json" },
+    body: JSON.stringify({
+      config,
+      reset_request_count: resetRequestCount,
+    }),
+    signal: AbortSignal.timeout(3000),
+  });
+  const json = await response.json().catch(() => ({}));
+  if (!response.ok || json.ok !== true) {
+    throw new Error(`Fake provider config failed with HTTP ${response.status}.`);
+  }
+  return json;
+}
+
+async function fakeProviderHealthy(rootUrl) {
+  try {
+    const response = await fetch(`${rootUrl.replace(/\/$/, "")}/healthz`, {
+      signal: AbortSignal.timeout(2000),
+    });
+    if (!response.ok) return false;
+    const json = await response.json().catch(() => ({}));
+    return json.ok === true;
+  } catch {
+    return false;
+  }
+}
+
+async function fakeProviderConfigurable(rootUrl) {
+  try {
+    const response = await fetch(`${rootUrl.replace(/\/$/, "")}/__qa/config`, {
+      signal: AbortSignal.timeout(2000),
+    });
+    if (!response.ok) return false;
+    const json = await response.json().catch(() => ({}));
+    return json.ok === true && json.config && typeof json.config === "object";
+  } catch {
+    return false;
+  }
+}
+
+async function stopProcess(pid) {
+  try {
+    process.kill(pid, "SIGTERM");
+  } catch {
+    return;
+  }
+  await sleep(500);
+}
+
+async function waitForFakeProviderState(path, expectedPid, timeoutMs) {
+  const startedAt = Date.now();
+  let lastState = {};
+  while (Date.now() - startedAt < timeoutMs) {
+    const state = await readState(path);
+    if (state.url && (!expectedPid || state.pid === expectedPid)) return state;
+    lastState = state;
+    await sleep(150);
+  }
+  return lastState;
+}
+
+async function readState(path) {
+  try {
+    return JSON.parse(await readFile(path, "utf8"));
+  } catch {
+    return {};
+  }
+}
+
+function normalizeProviderRootUrl(value) {
+  const trimmed = String(value || "").trim().replace(/\/$/, "");
+  return trimmed.endsWith("/v1") ? trimmed.slice(0, -3) : trimmed;
+}
+
+function healthyFakeProviderConfig() {
+  return {
+    response_text: "OK",
+    first_token_delay_ms: 25,
+    chunk_delay_ms: 10,
+    chunk_count: 0,
+    fault_status: 500,
+    fail_first_n: 0,
+    fail_every_n: 0,
+    fail_after_first_chunk: false,
+    dynamic_response: true,
+  };
+}
+
+function targetFakeProviderConfig() {
+  return {
+    response_text: env.LANGBOT_FAKE_PROVIDER_RESPONSE_TEXT || "OK",
+    first_token_delay_ms: nonNegativeInteger(env.LANGBOT_FAKE_PROVIDER_FIRST_TOKEN_DELAY_MS, 25),
+    chunk_delay_ms: nonNegativeInteger(env.LANGBOT_FAKE_PROVIDER_CHUNK_DELAY_MS, 10),
+    chunk_count: nonNegativeInteger(env.LANGBOT_FAKE_PROVIDER_CHUNK_COUNT, 0),
+    fault_status: httpFaultStatus(env.LANGBOT_FAKE_PROVIDER_FAULT_STATUS, 500),
+    fail_first_n: nonNegativeInteger(env.LANGBOT_FAKE_PROVIDER_FAIL_FIRST_N, 0),
+    fail_every_n: nonNegativeInteger(env.LANGBOT_FAKE_PROVIDER_FAIL_EVERY_N, 0),
+    fail_after_first_chunk: envBool(env.LANGBOT_FAKE_PROVIDER_FAIL_AFTER_FIRST_CHUNK, false),
+    dynamic_response: envBool(env.LANGBOT_FAKE_PROVIDER_DYNAMIC_RESPONSE, true),
+  };
+}
+
+async function skipWizard({ backendUrl, token }) {
+  const response = await apiJson(backendUrl, "/api/v1/system/wizard/completed", {
+    method: "POST",
+    token,
+    body: { status: "skipped" },
+  });
+  const ok = response.status < 400 && response.json.code === 0;
+  return {
+    status: ok ? "pass" : "fail",
+    http_status: response.status,
+    code: response.json.code ?? null,
+    reason: ok ? "Wizard marked skipped for local QA." : response.json.msg || "Wizard status update failed.",
+  };
+}
+
+async function ensureProvider({ backendUrl, token, name, requester, baseUrl }) {
+  const list = await apiJson(backendUrl, "/api/v1/provider/providers", { token });
+  if (isApiFailure(list)) {
+    throw new Error(list.json.msg || "Failed to list providers.");
+  }
+  const providers = list.json.data?.providers || [];
+  const existing = providers.find((provider) => (
+    provider.name === name
+      || (provider.requester === requester && String(provider.base_url || "").replace(/\/$/, "") === baseUrl.replace(/\/$/, ""))
+  ));
+  const body = {
+    name,
+    requester,
+    base_url: baseUrl,
+    api_keys: [env.LANGBOT_FAKE_PROVIDER_API_KEY || "langbot-fake-provider-key"],
+  };
+
+  if (existing?.uuid) {
+    const update = await apiJson(backendUrl, `/api/v1/provider/providers/${encodeURIComponent(existing.uuid)}`, {
+      method: "PUT",
+      token,
+      body,
+    });
+    if (isApiFailure(update)) {
+      throw new Error(update.json.msg || "Failed to update fake provider.");
+    }
+    return {
+      uuid: existing.uuid,
+      name,
+      requester,
+      created: false,
+      updated: true,
+    };
+  }
+
+  const create = await apiJson(backendUrl, "/api/v1/provider/providers", {
+    method: "POST",
+    token,
+    body,
+  });
+  const uuid = create.json.data?.uuid || "";
+  if (isApiFailure(create) || !uuid) {
+    throw new Error(create.json.msg || "Failed to create fake provider.");
+  }
+  return {
+    uuid,
+    name,
+    requester,
+    created: true,
+    updated: false,
+  };
+}
+
+async function ensureModel({ backendUrl, token, providerUuid, name }) {
+  const list = await apiJson(backendUrl, `/api/v1/provider/models/llm?provider_uuid=${encodeURIComponent(providerUuid)}`, { token });
+  if (isApiFailure(list)) {
+    throw new Error(list.json.msg || "Failed to list fake provider models.");
+  }
+  const models = list.json.data?.models || [];
+  const existing = models.find((model) => model.name === name);
+  const body = {
+    name,
+    provider_uuid: providerUuid,
+    abilities: [],
+    context_length: positiveInteger(env.LANGBOT_FAKE_PROVIDER_CONTEXT_LENGTH, 8192),
+    extra_args: {},
+    prefered_ranking: 0,
+  };
+  let modelUuid = existing?.uuid || "";
+  let created = false;
+  let updated = false;
+
+  if (modelUuid) {
+    const update = await apiJson(backendUrl, `/api/v1/provider/models/llm/${encodeURIComponent(modelUuid)}`, {
+      method: "PUT",
+      token,
+      body,
+    });
+    if (isApiFailure(update)) {
+      throw new Error(update.json.msg || "Failed to update fake provider model.");
+    }
+    updated = true;
+  } else {
+    const create = await apiJson(backendUrl, "/api/v1/provider/models/llm", {
+      method: "POST",
+      token,
+      body,
+    });
+    modelUuid = create.json.data?.uuid || "";
+    if (isApiFailure(create) || !modelUuid) {
+      throw new Error(create.json.msg || "Failed to create fake provider model.");
+    }
+    created = true;
+  }
+
+  const test = await apiJson(backendUrl, `/api/v1/provider/models/llm/${encodeURIComponent(modelUuid)}/test`, {
+    method: "POST",
+    token,
+    body: { extra_args: {} },
+  });
+  if (isApiFailure(test)) {
+    throw new Error(safeReason(test.json.msg || test.json.message || "Fake provider model test failed."));
+  }
+
+  return {
+    uuid: modelUuid,
+    name,
+    created,
+    updated,
+    test_status: "pass",
+    test_reason: "",
+  };
+}
+
+async function ensurePipeline({ backendUrl, token, name, modelUuid }) {
+  const list = await apiJson(backendUrl, "/api/v1/pipelines", { token });
+  if (isApiFailure(list)) {
+    throw new Error(list.json.msg || "Failed to list pipelines.");
+  }
+  const pipelines = list.json.data?.pipelines || [];
+  let pipeline = pipelines.find((item) => item.name === name) || null;
+  let created = false;
+
+  if (!pipeline) {
+    const create = await apiJson(backendUrl, "/api/v1/pipelines", {
+      method: "POST",
+      token,
+      body: {
+        name,
+        description: QA_RESOURCE_DESCRIPTION,
+        emoji: "QA",
+      },
+    });
+    const pipelineId = create.json.data?.uuid || "";
+    if (isApiFailure(create) || !pipelineId) {
+      throw new Error(create.json.msg || "Failed to create fake provider pipeline.");
+    }
+    created = true;
+    pipeline = { uuid: pipelineId };
+  }
+
+  const loaded = await apiJson(backendUrl, `/api/v1/pipelines/${encodeURIComponent(pipeline.uuid)}`, { token });
+  pipeline = loaded.json.data?.pipeline || null;
+  if (isApiFailure(loaded) || !pipeline?.uuid) {
+    throw new Error(loaded.json.msg || "Failed to load fake provider pipeline.");
+  }
+
+  const config = pipeline.config && typeof pipeline.config === "object" ? pipeline.config : {};
+  const ai = config.ai && typeof config.ai === "object" ? config.ai : {};
+  const existingLocalAgentConfig = ai["local-agent"] && typeof ai["local-agent"] === "object"
+    ? ai["local-agent"]
+    : {};
+  const localAgentConfig = {
+    timeout: 60,
+    prompt: [{ role: "system", content: "You are a deterministic QA assistant. Reply exactly as instructed." }],
+    "remove-think": false,
+    "knowledge-bases": [],
+    "box-session-id-template": "{launcher_type}_{launcher_id}",
+    "retrieval-top-k": 5,
+    "rerank-model": "",
+    "rerank-top-k": 5,
+    "max-tool-iterations": 20,
+    "tool-execution-mode": "parallel",
+    "max-tool-result-chars": 20000,
+    "context-history-fetch-limit": 20,
+    "context-window-tokens": 8192,
+    "context-reserve-tokens": 1024,
+    "context-keep-recent-tokens": 2048,
+    "context-summary-tokens": 1024,
+    ...existingLocalAgentConfig,
+    // Current backend truncation still reads this field directly.
+    "max-round": positiveInteger(existingLocalAgentConfig["max-round"], 10),
+    model: {
+      primary: modelUuid,
+      fallbacks: [],
+    },
+  };
+  const updatedConfig = {
+    ...config,
+    ai: {
+      ...ai,
+      runner: {
+        ...(ai.runner && typeof ai.runner === "object" ? ai.runner : {}),
+        id: RUNNER_ID,
+        runner: RUNNER_ID,
+        "expire-time": 0,
+      },
+      "local-agent": localAgentConfig,
+    },
+  };
+
+  const update = await apiJson(backendUrl, `/api/v1/pipelines/${encodeURIComponent(pipeline.uuid)}`, {
+    method: "PUT",
+    token,
+    body: {
+      name,
+      description: QA_RESOURCE_DESCRIPTION,
+      emoji: "QA",
+      config: updatedConfig,
+    },
+  });
+  if (isApiFailure(update)) {
+    throw new Error(update.json.msg || "Failed to update fake provider pipeline.");
+  }
+
+  return {
+    pipeline_id: pipeline.uuid,
+    pipeline_name: name,
+    created,
+    updated: true,
+  };
+}
+
+function isApiFailure(response) {
+  return response.status >= 400 || (response.json.code !== undefined && response.json.code !== 0);
+}
+
+function positiveInteger(value, fallback) {
+  const parsed = Number(value);
+  return Number.isInteger(parsed) && parsed > 0 ? parsed : fallback;
+}
+
+function nonNegativeInteger(value, fallback) {
+  const parsed = Number(value);
+  return Number.isInteger(parsed) && parsed >= 0 ? parsed : fallback;
+}
+
+function httpFaultStatus(value, fallback) {
+  const parsed = Number(value);
+  return Number.isInteger(parsed) && parsed >= 400 && parsed <= 599 ? parsed : fallback;
+}
+
+function envBool(value, fallback) {
+  if (value === undefined || value === "") return fallback;
+  if (/^(1|true|yes|on)$/i.test(String(value))) return true;
+  if (/^(0|false|no|off)$/i.test(String(value))) return false;
+  return fallback;
+}
+
+function sleep(ms) {
+  return new Promise((resolve) => setTimeout(resolve, ms));
+}
+
+function safeReason(value) {
+  return redact(String(value || "")).slice(0, 1000);
+}
+
+async function upsertEnvLocal(path, updates) {
+  await mkdir(dirname(path), { recursive: true });
+  let text = "";
+  try {
+    text = await readFile(path, "utf8");
+  } catch {
+    text = "";
+  }
+  const lines = text.split(/\r?\n/);
+  const seen = new Set();
+  const next = lines.map((line) => {
+    const trimmed = line.trim();
+    const equals = trimmed.indexOf("=");
+    if (equals <= 0 || trimmed.startsWith("#")) return line;
+    const key = trimmed.slice(0, equals).trim();
+    if (!(key in updates)) return line;
+    seen.add(key);
+    return `${key}=${updates[key]}`;
+  });
+  for (const [key, value] of Object.entries(updates)) {
+    if (!seen.has(key)) next.push(`${key}=${value}`);
+  }
+  await writeFile(path, `${next.filter((line, index) => line !== "" || index < next.length - 1).join("\n")}\n`, "utf8");
+}

skills/scripts/e2e/ensure-local-agent-pipeline.mjs

@@ -10,6 +10,7 @@ import {
   ensureEvidence,
   evidencePaths,
   loadEnvFiles,
+  redact,
   resetAndAuthLocalUser,
   safeScreenshot,
   setBrowserToken,
@@ -17,9 +18,12 @@ import {
   writeResult,
 } from "./lib/langbot-e2e.mjs";
 
-const RUNNER_ID = "plugin:langbot/local-agent/default";
+const RUNNER_ID = "local-agent";
+const SPACE_PROVIDER_UUID = "00000000-0000-0000-0000-000000000000";
 const DEFAULT_PIPELINE_NAME = "Agent QA Local Agent Debug Chat";
 const DEFAULT_LOCAL_PASSWORD = "LangBotE2ELocalPass!2026";
+const DEFAULT_MODEL_TEST_LIMIT = 8;
+const DEFAULT_MODEL_FALLBACK_COUNT = 3;
 const caseId = "ensure-local-agent-pipeline";
 
 await loadEnvFiles();
@@ -45,11 +49,18 @@ const result = {
   pipeline_url: "",
   runner_id: RUNNER_ID,
   selected_model_id: "",
+  selected_model_name: "",
+  fallback_model_ids: [],
   model_count: 0,
+  space_model_count: 0,
+  scanned_space_model_count: 0,
+  tested_model_count: 0,
+  model_tests: [],
   created: false,
   updated: false,
   wrote_env: false,
   auth: null,
+  wizard: null,
   browser_token_check: null,
   page_signal: "",
   evidence: {
@@ -71,6 +82,7 @@ try {
   const user = env.LANGBOT_E2E_LOGIN_USER || "";
   const password = env.LANGBOT_E2E_LOGIN_PASSWORD || DEFAULT_LOCAL_PASSWORD;
   if (!user) {
+    result.status = "env_issue";
     throw new Error("LANGBOT_E2E_LOGIN_USER is required so this setup can create/update the pipeline via backend API.");
   }
 
@@ -81,6 +93,13 @@ try {
     backend_token_check: auth.check,
   };
 
+  const wizard = await skipWizard({ backendUrl, token: auth.token });
+  result.wizard = wizard;
+  if (wizard.status !== "pass") {
+    result.status = "fail";
+    throw new Error(wizard.reason || "Failed to mark the local QA wizard as skipped.");
+  }
+
   const prepared = await ensureLocalAgentPipeline({
     backendUrl,
     token: auth.token,
@@ -99,6 +118,10 @@ try {
       LANGBOT_PIPELINE_NAME: result.pipeline_name || pipelineName,
       LANGBOT_LOCAL_AGENT_PIPELINE_URL: result.pipeline_url,
       LANGBOT_LOCAL_AGENT_PIPELINE_NAME: result.pipeline_name || pipelineName,
+      ...(result.selected_model_id ? {
+        LANGBOT_LOCAL_AGENT_MODEL_UUID: result.selected_model_id,
+        LANGBOT_E2E_MODEL_UUID: result.selected_model_id,
+      } : {}),
     });
     result.wrote_env = true;
   }
@@ -127,6 +150,21 @@ try {
 
 process.exit(result.status === "pass" ? 0 : result.status === "env_issue" ? 2 : 1);
 
+async function skipWizard({ backendUrl, token }) {
+  const response = await apiJson(backendUrl, "/api/v1/system/wizard/completed", {
+    method: "POST",
+    token,
+    body: { status: "skipped" },
+  });
+  const ok = response.status < 400 && response.json.code === 0;
+  return {
+    status: ok ? "pass" : "fail",
+    http_status: response.status,
+    code: response.json.code ?? null,
+    reason: ok ? "Wizard marked skipped for local QA." : response.json.msg || "Wizard status update failed.",
+  };
+}
+
 async function ensureLocalAgentPipeline({ backendUrl, token, pipelineName, runnerId }) {
   const [pipelineList, modelList] = await Promise.all([
     apiJson(backendUrl, "/api/v1/pipelines", { token }),
@@ -149,7 +187,19 @@ async function ensureLocalAgentPipeline({ backendUrl, token, pipelineName, runne
   }
 
   const models = modelList.json.data?.models || [];
-  const selectedModel = models.find((model) => model.uuid) || null;
+  const skippedModelIds = new Set(
+    String(env.LANGBOT_E2E_SKIP_MODEL_UUIDS || "")
+      .split(",")
+      .map((item) => item.trim())
+      .filter(Boolean),
+  );
+  const skippedModelNames = new Set(
+    String(env.LANGBOT_E2E_SKIP_MODEL_NAMES || "")
+      .split(",")
+      .map((item) => item.trim())
+      .filter(Boolean),
+  );
+  const spaceModels = models.filter((model) => isSpaceModel(model) && !skippedModelIds.has(model.uuid));
   const pipelines = pipelineList.json.data?.pipelines || [];
   let pipeline = pipelines.find((item) => item.name === pipelineName) || null;
   let created = false;
@@ -170,6 +220,7 @@ async function ensureLocalAgentPipeline({ backendUrl, token, pipelineName, runne
         reason: createdResponse.json.msg || "Failed to create pipeline.",
         create_status: createdResponse.status,
         model_count: models.length,
+        space_model_count: spaceModels.length,
       };
     }
     const pipelineId = createdResponse.json.data?.uuid || "";
@@ -183,6 +234,7 @@ async function ensureLocalAgentPipeline({ backendUrl, token, pipelineName, runne
       status: "fail",
       reason: "Pipeline was not created or resolved.",
       model_count: models.length,
+      space_model_count: spaceModels.length,
     };
   }
 
@@ -194,27 +246,37 @@ async function ensureLocalAgentPipeline({ backendUrl, token, pipelineName, runne
       get_status: loaded.status,
       pipeline_id: pipeline.uuid,
       model_count: models.length,
+      space_model_count: spaceModels.length,
     };
   }
   pipeline = loaded.json.data.pipeline;
 
   const config = pipeline.config && typeof pipeline.config === "object" ? pipeline.config : {};
   const ai = config.ai && typeof config.ai === "object" ? config.ai : {};
-  const runnerConfig = ai.runner_config && typeof ai.runner_config === "object" ? ai.runner_config : {};
+  const rawExistingLocalAgentConfig = ai["local-agent"] && typeof ai["local-agent"] === "object"
-  const rawExistingLocalAgentConfig = runnerConfig[runnerId] && typeof runnerConfig[runnerId] === "object"
+    ? ai["local-agent"]
-    ? runnerConfig[runnerId]
     : {};
   const existingLocalAgentConfig = rawExistingLocalAgentConfig;
   const existingModel = existingLocalAgentConfig.model && typeof existingLocalAgentConfig.model === "object"
     ? existingLocalAgentConfig.model
     : {};
   const requestedModelId = env.LANGBOT_LOCAL_AGENT_MODEL_UUID || env.LANGBOT_E2E_MODEL_UUID || "";
-  const selectedModelId = requestedModelId || existingModel.primary || selectedModel?.uuid || "";
+  const selected = await selectWorkingSpaceModel({
+    backendUrl,
+    token,
+    models,
+    skippedModelIds,
+    skippedModelNames,
+    requestedModelId,
+    existingModelId: existingModel.primary || "",
+  });
+  const selectedModelId = selected.selected_model_id || "";
   const localAgentConfig = {
     timeout: 300,
     prompt: [{ role: "system", content: "You are a helpful assistant." }],
     "remove-think": false,
     "knowledge-bases": [],
+    "box-session-id-template": "{launcher_type}_{launcher_id}",
     "retrieval-top-k": 5,
     "rerank-model": "",
     "rerank-top-k": 5,
@@ -227,9 +289,11 @@ async function ensureLocalAgentPipeline({ backendUrl, token, pipelineName, runne
     "context-keep-recent-tokens": 20000,
     "context-summary-tokens": 8000,
     ...existingLocalAgentConfig,
+    // Current backend truncation still reads this field directly.
+    "max-round": positiveInteger(existingLocalAgentConfig["max-round"], 10),
     model: {
       primary: selectedModelId,
-      fallbacks: requestedModelId ? [] : Array.isArray(existingModel.fallbacks) ? existingModel.fallbacks : [],
+      fallbacks: selected.fallback_model_ids || [],
     },
   };
   const updatedConfig = {
@@ -239,12 +303,10 @@ async function ensureLocalAgentPipeline({ backendUrl, token, pipelineName, runne
       runner: {
         ...(ai.runner && typeof ai.runner === "object" ? ai.runner : {}),
         id: runnerId,
+        runner: runnerId,
         "expire-time": 0,
       },
-      runner_config: {
+      "local-agent": localAgentConfig,
-        ...runnerConfig,
-        [runnerId]: localAgentConfig,
-      },
     },
   };
 
@@ -265,19 +327,31 @@ async function ensureLocalAgentPipeline({ backendUrl, token, pipelineName, runne
       update_status: updateResponse.status,
       pipeline_id: pipeline.uuid,
       model_count: models.length,
+      space_model_count: spaceModels.length,
+      scanned_space_model_count: selected.scanned_space_model_count,
+      tested_model_count: selected.tested_model_count,
+      model_tests: selected.model_tests,
       selected_model_id: selectedModelId,
+      selected_model_name: selected.selected_model_name,
+      fallback_model_ids: selected.fallback_model_ids,
     };
   }
 
   return {
     status: selectedModelId ? "pass" : "env_issue",
     reason: selectedModelId
-      ? "Local-agent pipeline is configured for Debug Chat."
+      ? `Local-agent pipeline is configured for Debug Chat with Space model ${selected.selected_model_name || selectedModelId} and ${selected.fallback_model_ids.length} fallback(s).`
-      : "Pipeline was created but no LLM model is configured in this LangBot instance.",
+      : selected.reason || "No working Space LLM model is configured in this LangBot instance.",
     pipeline_id: pipeline.uuid,
-    pipeline_name: pipeline.name,
+    pipeline_name: pipelineName,
     model_count: models.length,
+    space_model_count: spaceModels.length,
+    scanned_space_model_count: selected.scanned_space_model_count,
+    tested_model_count: selected.tested_model_count,
+    model_tests: selected.model_tests,
     selected_model_id: selectedModelId,
+    selected_model_name: selected.selected_model_name,
+    fallback_model_ids: selected.fallback_model_ids,
     created,
     updated: true,
   };
@@ -287,6 +361,229 @@ function isApiFailure(response) {
   return response.status >= 400 || (response.json.code !== undefined && response.json.code !== 0);
 }
 
+function isSpaceModel(model) {
+  const provider = model?.provider && typeof model.provider === "object" ? model.provider : {};
+  return model?.provider_uuid === SPACE_PROVIDER_UUID
+    || provider.uuid === SPACE_PROVIDER_UUID
+    || provider.requester === "space-chat-completions"
+    || provider.name === "LangBot Models";
+}
+
+async function selectWorkingSpaceModel({
+  backendUrl,
+  token,
+  models,
+  skippedModelIds,
+  skippedModelNames,
+  requestedModelId,
+  existingModelId,
+}) {
+  const modelTests = [];
+  const testLimit = positiveInteger(env.LANGBOT_E2E_MODEL_TEST_LIMIT, DEFAULT_MODEL_TEST_LIMIT);
+  const fallbackCount = positiveInteger(env.LANGBOT_E2E_MODEL_FALLBACK_COUNT, DEFAULT_MODEL_FALLBACK_COUNT);
+  const workingModels = [];
+  const spaceModels = rankModels(models.filter((model) => (
+    model.uuid
+      && isSpaceModel(model)
+      && !skippedModelIds.has(model.uuid)
+      && !skippedModelNames.has(model.name)
+  )));
+  const requestedModel = requestedModelId
+    ? spaceModels.find((model) => model.uuid === requestedModelId) || null
+    : null;
+  const existingModel = existingModelId
+    ? spaceModels.find((model) => model.uuid === existingModelId) || null
+    : null;
+  const candidates = uniqueCandidates([
+    ...(requestedModel ? [existingCandidate(requestedModel, "requested")] : []),
+    ...(existingModel ? [existingCandidate(existingModel, "existing-pipeline")] : []),
+    ...spaceModels.map((model) => existingCandidate(model, "configured-space")),
+  ]);
+
+  let scanResult = { status: "skipped", models: [], reason: "" };
+  if (env.LANGBOT_E2E_SCAN_SPACE_MODELS !== "false") {
+    scanResult = await scanSpaceModels({ backendUrl, token });
+    if (scanResult.status === "pass") {
+      const knownNames = new Set(spaceModels.map((model) => model.name));
+      candidates.push(...scanResult.models
+        .filter((model) => model.name && !knownNames.has(model.name) && !skippedModelNames.has(model.name))
+        .map((model) => scannedCandidate(model)));
+    }
+  }
+
+  const unique = uniqueCandidates(candidates);
+  for (const candidate of unique.slice(0, testLimit)) {
+    const test = await ensureAndTestModel({ backendUrl, token, candidate });
+    modelTests.push(test);
+    if (test.status === "pass" && test.model_uuid) {
+      workingModels.push(test);
+      if (workingModels.length >= fallbackCount + 1) break;
+    }
+  }
+
+  if (workingModels.length > 0) {
+    const [primary, ...fallbacks] = workingModels;
+    return {
+      status: "pass",
+      reason: "",
+      selected_model_id: primary.model_uuid,
+      selected_model_name: primary.model_name,
+      fallback_model_ids: fallbacks.map((model) => model.model_uuid),
+      scanned_space_model_count: scanResult.models.length,
+      tested_model_count: modelTests.length,
+      model_tests: modelTests,
+    };
+  }
+
+  const baseReason = unique.length === 0
+    ? scanResult.reason || "No Space LLM model candidates are available."
+    : `No working Space LLM model found after testing ${modelTests.length} candidate(s).`;
+  return {
+    status: "env_issue",
+    reason: requestedModelId && !requestedModel
+      ? `Requested Space LLM model ${requestedModelId} is missing or skipped; ${baseReason}`
+      : baseReason,
+    selected_model_id: "",
+    selected_model_name: "",
+    fallback_model_ids: [],
+    scanned_space_model_count: scanResult.models.length,
+    tested_model_count: modelTests.length,
+    model_tests: modelTests,
+  };
+}
+
+async function scanSpaceModels({ backendUrl, token }) {
+  const response = await apiJson(
+    backendUrl,
+    `/api/v1/provider/providers/${encodeURIComponent(SPACE_PROVIDER_UUID)}/scan-models?type=llm`,
+    { token },
+  );
+  if (isApiFailure(response)) {
+    return {
+      status: "env_issue",
+      models: [],
+      reason: safeReason(response.json.msg || response.json.message || "Failed to scan Space LLM models."),
+    };
+  }
+  return {
+    status: "pass",
+    models: response.json.data?.models || [],
+    reason: "",
+  };
+}
+
+async function ensureAndTestModel({ backendUrl, token, candidate }) {
+  let modelUuid = candidate.uuid || "";
+  let created = false;
+  if (!modelUuid) {
+    const create = await apiJson(backendUrl, "/api/v1/provider/models/llm", {
+      method: "POST",
+      token,
+      body: {
+        name: candidate.name,
+        provider_uuid: SPACE_PROVIDER_UUID,
+        abilities: candidate.abilities || [],
+        context_length: candidate.context_length ?? null,
+        extra_args: {},
+        prefered_ranking: positiveInteger(candidate.prefered_ranking, 0),
+      },
+    });
+    modelUuid = create.json.data?.uuid || "";
+    if (isApiFailure(create) || !modelUuid) {
+      return modelTestResult(candidate, {
+        status: "fail",
+        reason: safeReason(create.json.msg || "Failed to create scanned Space model."),
+        http_status: create.status,
+      });
+    }
+    created = true;
+  }
+
+  const test = await apiJson(backendUrl, `/api/v1/provider/models/llm/${encodeURIComponent(modelUuid)}/test`, {
+    method: "POST",
+    token,
+    body: { extra_args: {} },
+  });
+  const passed = !isApiFailure(test);
+  if (!passed && created) {
+    await apiJson(backendUrl, `/api/v1/provider/models/llm/${encodeURIComponent(modelUuid)}`, {
+      method: "DELETE",
+      token,
+    }).catch(() => {});
+  }
+  return modelTestResult(candidate, {
+    status: passed ? "pass" : "fail",
+    reason: passed ? "" : safeReason(test.json.msg || test.json.message || "Space model test failed."),
+    http_status: test.status,
+    model_uuid: modelUuid,
+    created,
+  });
+}
+
+function modelTestResult(candidate, details) {
+  return {
+    source: candidate.source,
+    model_uuid: details.model_uuid || candidate.uuid || "",
+    model_name: candidate.name,
+    status: details.status,
+    reason: details.reason || "",
+    http_status: details.http_status ?? null,
+    created: Boolean(details.created),
+  };
+}
+
+function existingCandidate(model, source) {
+  return {
+    source,
+    uuid: model.uuid,
+    name: model.name,
+    abilities: model.abilities || [],
+    context_length: model.context_length,
+    prefered_ranking: model.prefered_ranking,
+  };
+}
+
+function scannedCandidate(model) {
+  return {
+    source: "scanned-space",
+    uuid: "",
+    name: model.name || model.id,
+    abilities: model.abilities || [],
+    context_length: model.context_length,
+    prefered_ranking: model.prefered_ranking,
+  };
+}
+
+function uniqueCandidates(candidates) {
+  const seen = new Set();
+  const result = [];
+  for (const candidate of candidates) {
+    const key = candidate.uuid ? `uuid:${candidate.uuid}` : `name:${candidate.name}`;
+    if (!candidate.name || seen.has(key)) continue;
+    seen.add(key);
+    result.push(candidate);
+  }
+  return result;
+}
+
+function rankModels(models) {
+  return [...models].sort((left, right) => {
+    const leftRank = Number.isFinite(Number(left.prefered_ranking)) ? Number(left.prefered_ranking) : 9999;
+    const rightRank = Number.isFinite(Number(right.prefered_ranking)) ? Number(right.prefered_ranking) : 9999;
+    if (leftRank !== rightRank) return leftRank - rightRank;
+    return String(left.name || "").localeCompare(String(right.name || ""));
+  });
+}
+
+function positiveInteger(value, fallback) {
+  const parsed = Number(value);
+  return Number.isInteger(parsed) && parsed > 0 ? parsed : fallback;
+}
+
+function safeReason(value) {
+  return redact(String(value || "")).slice(0, 1000);
+}
+
 async function upsertEnvLocal(path, updates) {
   let text = "";
   try {

skills/scripts/e2e/fake-openai-provider.mjs

@@ -0,0 +1,496 @@
+#!/usr/bin/env node
+
+import { createServer } from "node:http";
+import { mkdir, writeFile } from "node:fs/promises";
+import { dirname, resolve } from "node:path";
+import { env, exit } from "node:process";
+
+const args = parseArgs(process.argv.slice(2));
+const host = args.host || env.LANGBOT_FAKE_PROVIDER_HOST || "127.0.0.1";
+const port = integer(args.port ?? env.LANGBOT_FAKE_PROVIDER_PORT, 0);
+const stateFile = args["state-file"] || env.LANGBOT_FAKE_PROVIDER_STATE_FILE || "";
+const modelName = env.LANGBOT_FAKE_PROVIDER_MODEL_NAME || "gpt-4o-mini";
+const config = {
+  response_text: env.LANGBOT_FAKE_PROVIDER_RESPONSE_TEXT || "OK",
+  first_token_delay_ms: integer(env.LANGBOT_FAKE_PROVIDER_FIRST_TOKEN_DELAY_MS, 25),
+  chunk_delay_ms: integer(env.LANGBOT_FAKE_PROVIDER_CHUNK_DELAY_MS, 10),
+  chunk_count: integer(env.LANGBOT_FAKE_PROVIDER_CHUNK_COUNT, 0),
+  fault_status: integer(env.LANGBOT_FAKE_PROVIDER_FAULT_STATUS, 500),
+  fail_first_n: integer(env.LANGBOT_FAKE_PROVIDER_FAIL_FIRST_N, 0),
+  fail_every_n: integer(env.LANGBOT_FAKE_PROVIDER_FAIL_EVERY_N, 0),
+  fail_after_first_chunk: bool(env.LANGBOT_FAKE_PROVIDER_FAIL_AFTER_FIRST_CHUNK, false),
+  dynamic_response: !/^(0|false|no|off)$/i.test(env.LANGBOT_FAKE_PROVIDER_DYNAMIC_RESPONSE || ""),
+  request_log_limit: integer(env.LANGBOT_FAKE_PROVIDER_REQUEST_LOG_LIMIT, 500),
+};
+
+let requestCount = 0;
+const recentRequests = [];
+
+const server = createServer(async (request, response) => {
+  const startedAt = Date.now();
+  const startedPerf = performance.now();
+  let requestRecord = null;
+  const url = new URL(request.url || "/", `http://${request.headers.host || `${host}:${port}`}`);
+  try {
+    if (request.method === "GET" && url.pathname === "/healthz") {
+      sendJson(response, 200, {
+        ok: true,
+        model: modelName,
+        config,
+        request_count: requestCount,
+        recent_request_count: recentRequests.length,
+      });
+      return;
+    }
+
+    if (request.method === "GET" && url.pathname === "/__qa/config") {
+      sendJson(response, 200, {
+        ok: true,
+        model: modelName,
+        config,
+        request_count: requestCount,
+        recent_requests: recentRequests,
+      });
+      return;
+    }
+
+    if (request.method === "POST" && url.pathname === "/__qa/config") {
+      const body = await readJson(request);
+      applyConfig(body.config && typeof body.config === "object" ? body.config : body);
+      if (body.reset_request_count !== false) resetRequestState();
+      sendJson(response, 200, {
+        ok: true,
+        model: modelName,
+        config,
+        request_count: requestCount,
+      });
+      return;
+    }
+
+    if (request.method === "POST" && url.pathname === "/__qa/reset") {
+      resetRequestState();
+      sendJson(response, 200, {
+        ok: true,
+        model: modelName,
+        config,
+        request_count: requestCount,
+      });
+      return;
+    }
+
+    if (request.method === "GET" && ["/models", "/v1/models"].includes(url.pathname)) {
+      sendJson(response, 200, {
+        object: "list",
+        data: [
+          {
+            id: modelName,
+            object: "model",
+            created: 1,
+            owned_by: "langbot-qa",
+            type: "llm",
+          },
+        ],
+      });
+      return;
+    }
+
+    if (request.method === "POST" && ["/chat/completions", "/v1/chat/completions"].includes(url.pathname)) {
+      requestCount += 1;
+      const body = await readJson(request);
+      const requestId = `chatcmpl-langbot-fake-${requestCount}`;
+      const shouldFail = requestCount <= config.fail_first_n
+        || (config.fail_every_n > 0 && requestCount % config.fail_every_n === 0);
+      const replyText = responseTextForBody(body);
+      requestRecord = recordRequest({
+        id: requestId,
+        request_number: requestCount,
+        path: url.pathname,
+        stream: Boolean(body.stream),
+        model: body.model || "",
+        message_count: Array.isArray(body.messages) ? body.messages.length : 0,
+        should_fail: shouldFail,
+        status: "running",
+        http_status: null,
+        expected_text: replyText,
+        response_text_preview: previewText(replyText),
+        started_at: new Date(startedAt).toISOString(),
+        started_epoch_ms: startedAt,
+        configured_first_token_delay_ms: config.first_token_delay_ms,
+        configured_chunk_delay_ms: config.chunk_delay_ms,
+        configured_chunk_count: config.chunk_count,
+      });
+
+      if (shouldFail) {
+        await sleep(config.first_token_delay_ms);
+        sendJson(response, config.fault_status, {
+          error: {
+            message: `LangBot fake provider injected HTTP ${config.fault_status}`,
+            type: "fake_provider_fault",
+            code: "fake_provider_fault",
+          },
+        });
+        finishRequestRecord(requestRecord, startedPerf, {
+          status: "http_fault",
+          http_status: config.fault_status,
+        });
+        return;
+      }
+
+      if (body.stream) {
+        await streamCompletion(response, {
+          requestId,
+          model: body.model || modelName,
+          content: replyText,
+          failAfterFirstChunk: config.fail_after_first_chunk,
+          requestRecord,
+          startedPerf,
+        });
+      } else {
+        await sleep(config.first_token_delay_ms + config.chunk_delay_ms);
+        sendJson(response, 200, completionPayload({
+          requestId,
+          model: body.model || modelName,
+          content: replyText,
+        }));
+        markRequestTiming(requestRecord, "first_chunk", startedPerf);
+        markRequestTiming(requestRecord, "first_content_chunk", startedPerf);
+        requestRecord.content_chunk_count = 1;
+        finishRequestRecord(requestRecord, startedPerf, {
+          status: "ok",
+          http_status: 200,
+        });
+      }
+      return;
+    }
+
+    sendJson(response, 404, {
+      error: {
+        message: `No fake provider route for ${request.method} ${url.pathname}`,
+        type: "not_found",
+      },
+    });
+  } catch (error) {
+    if (requestRecord) {
+      finishRequestRecord(requestRecord, startedPerf, {
+        status: "fake_provider_error",
+        http_status: 500,
+        error: error instanceof Error ? error.message : String(error),
+      });
+    }
+    sendJson(response, 500, {
+      error: {
+        message: error instanceof Error ? error.message : String(error),
+        type: "fake_provider_error",
+      },
+    });
+  } finally {
+    const durationMs = Date.now() - startedAt;
+    if (url.pathname !== "/healthz") {
+      console.log(JSON.stringify({
+        at: new Date().toISOString(),
+        method: request.method,
+        path: url.pathname,
+        duration_ms: durationMs,
+      }));
+    }
+  }
+});
+
+server.listen(port, host, async () => {
+  const address = server.address();
+  const selectedPort = typeof address === "object" && address ? address.port : port;
+  const url = `http://${host}:${selectedPort}`;
+  const state = {
+    status: "ready",
+    pid: process.pid,
+    url,
+    base_url: `${url}/v1`,
+    model: modelName,
+    started_at: new Date().toISOString(),
+  };
+  if (stateFile) {
+    const path = resolve(stateFile);
+    await mkdir(dirname(path), { recursive: true });
+    await writeFile(path, `${JSON.stringify(state, null, 2)}\n`, "utf8");
+  }
+  console.log(JSON.stringify(state));
+});
+
+server.on("error", (error) => {
+  console.error(JSON.stringify({
+    status: "error",
+    reason: error instanceof Error ? error.message : String(error),
+  }));
+  exit(1);
+});
+
+process.on("SIGTERM", () => {
+  server.close(() => exit(0));
+});
+
+function parseArgs(argv) {
+  const result = {};
+  for (const item of argv) {
+    const match = item.match(/^--([^=]+)(?:=(.*))?$/);
+    if (!match) continue;
+    result[match[1]] = match[2] ?? "1";
+  }
+  return result;
+}
+
+function integer(value, fallback) {
+  const parsed = Number.parseInt(String(value ?? ""), 10);
+  return Number.isFinite(parsed) && parsed >= 0 ? parsed : fallback;
+}
+
+function bool(value, fallback) {
+  if (value === undefined || value === "") return fallback;
+  if (/^(1|true|yes|on)$/i.test(String(value))) return true;
+  if (/^(0|false|no|off)$/i.test(String(value))) return false;
+  return fallback;
+}
+
+function sleep(ms) {
+  return new Promise((resolve) => setTimeout(resolve, Math.max(0, ms)));
+}
+
+async function readJson(request) {
+  let text = "";
+  for await (const chunk of request) text += chunk.toString();
+  if (!text) return {};
+  return JSON.parse(text);
+}
+
+function sendJson(response, status, payload) {
+  const text = `${JSON.stringify(payload)}\n`;
+  response.writeHead(status, {
+    "content-type": "application/json",
+    "content-length": Buffer.byteLength(text),
+  });
+  response.end(text);
+}
+
+function completionPayload({ requestId, model, content }) {
+  const completionTokens = tokenEstimate(content);
+  return {
+    id: requestId,
+    object: "chat.completion",
+    created: Math.floor(Date.now() / 1000),
+    model,
+    choices: [
+      {
+        index: 0,
+        message: {
+          role: "assistant",
+          content,
+        },
+        finish_reason: "stop",
+      },
+    ],
+    usage: {
+      prompt_tokens: 8,
+      completion_tokens: completionTokens,
+      total_tokens: 8 + completionTokens,
+    },
+  };
+}
+
+async function streamCompletion(response, {
+  requestId,
+  model,
+  content,
+  failAfterFirstChunk: failMidStream,
+  requestRecord,
+  startedPerf,
+}) {
+  response.writeHead(200, {
+    "content-type": "text/event-stream; charset=utf-8",
+    "cache-control": "no-cache",
+    "connection": "keep-alive",
+  });
+
+  await sleep(config.first_token_delay_ms);
+  markRequestTiming(requestRecord, "first_chunk", startedPerf);
+  writeSse(response, {
+    id: requestId,
+    object: "chat.completion.chunk",
+    created: Math.floor(Date.now() / 1000),
+    model,
+    choices: [{ index: 0, delta: { role: "assistant" }, finish_reason: null }],
+  });
+
+  const chunks = splitContent(content);
+  for (let index = 0; index < chunks.length; index += 1) {
+    await sleep(config.chunk_delay_ms);
+    if (index === 0) markRequestTiming(requestRecord, "first_content_chunk", startedPerf);
+    requestRecord.content_chunk_count = (requestRecord.content_chunk_count || 0) + 1;
+    writeSse(response, {
+      id: requestId,
+      object: "chat.completion.chunk",
+      created: Math.floor(Date.now() / 1000),
+      model,
+      choices: [{ index: 0, delta: { content: chunks[index] }, finish_reason: null }],
+    });
+    if (failMidStream && index === 0) {
+      finishRequestRecord(requestRecord, startedPerf, {
+        status: "mid_stream_disconnect",
+        http_status: 200,
+      });
+      response.destroy(new Error("LangBot fake provider injected mid-stream disconnect"));
+      return;
+    }
+  }
+
+  await sleep(config.chunk_delay_ms);
+  const completionTokens = tokenEstimate(content);
+  writeSse(response, {
+    id: requestId,
+    object: "chat.completion.chunk",
+    created: Math.floor(Date.now() / 1000),
+    model,
+    choices: [{ index: 0, delta: {}, finish_reason: "stop" }],
+    usage: {
+      prompt_tokens: 8,
+      completion_tokens: completionTokens,
+      total_tokens: 8 + completionTokens,
+    },
+  });
+  response.write("data: [DONE]\n\n");
+  response.end();
+  finishRequestRecord(requestRecord, startedPerf, {
+    status: "ok",
+    http_status: 200,
+  });
+}
+
+function writeSse(response, payload) {
+  response.write(`data: ${JSON.stringify(payload)}\n\n`);
+}
+
+function splitContent(content) {
+  const text = String(content);
+  const requested = config.chunk_count;
+  if (requested <= 1 || text.length <= 1) return [text];
+  const chunkSize = Math.max(1, Math.ceil(text.length / requested));
+  const chunks = [];
+  for (let index = 0; index < text.length; index += chunkSize) {
+    chunks.push(text.slice(index, index + chunkSize));
+  }
+  return chunks;
+}
+
+function tokenEstimate(content) {
+  return Math.max(1, Math.ceil(String(content || "").length / 4));
+}
+
+function responseTextForBody(body) {
+  if (!config.dynamic_response) {
+    return config.response_text;
+  }
+  const messages = Array.isArray(body.messages) ? body.messages : [];
+  const lastUser = [...messages].reverse().find((message) => message?.role === "user");
+  const text = flattenContent(lastUser?.content || "");
+  const quoted = text.match(/["'“”](.{1,80}?)["'“”]/);
+  if (quoted?.[1]) return quoted[1].trim();
+  const exact = text.match(/(?:reply|回复|输出|return)\s+(?:exactly\s+)?([A-Za-z0-9_.:@-]{1,80})/i);
+  if (exact?.[1]) return exact[1].trim().replace(/[。.!?]+$/, "");
+  const only = text.match(/只回复\s*([A-Za-z0-9_.:@-]{1,80})/);
+  if (only?.[1]) return only[1].trim().replace(/[。.!?]+$/, "");
+  return config.response_text;
+}
+
+function flattenContent(content) {
+  if (typeof content === "string") return content;
+  if (Array.isArray(content)) {
+    return content
+      .map((item) => {
+        if (typeof item === "string") return item;
+        if (item && typeof item === "object") return item.text || "";
+        return "";
+      })
+      .join("\n");
+  }
+  return "";
+}
+
+function recordRequest(entry) {
+  const item = {
+    ...entry,
+    at: new Date().toISOString(),
+    finished_at: null,
+    finished_epoch_ms: null,
+    duration_ms: null,
+    first_chunk_at: null,
+    first_chunk_epoch_ms: null,
+    first_chunk_ms: null,
+    first_content_chunk_at: null,
+    first_content_chunk_epoch_ms: null,
+    first_content_chunk_ms: null,
+    content_chunk_count: 0,
+  };
+  recentRequests.push(item);
+  while (recentRequests.length > config.request_log_limit) recentRequests.shift();
+  return item;
+}
+
+function markRequestTiming(entry, key, startedPerf) {
+  if (!entry || entry[`${key}_at`]) return;
+  const now = Date.now();
+  entry[`${key}_at`] = new Date(now).toISOString();
+  entry[`${key}_epoch_ms`] = now;
+  entry[`${key}_ms`] = rounded(performance.now() - startedPerf);
+}
+
+function finishRequestRecord(entry, startedPerf, updates = {}) {
+  if (!entry || entry.finished_at) return;
+  const now = Date.now();
+  Object.assign(entry, updates);
+  entry.finished_at = new Date(now).toISOString();
+  entry.finished_epoch_ms = now;
+  entry.duration_ms = rounded(performance.now() - startedPerf);
+}
+
+function rounded(value) {
+  return Number(value.toFixed(3));
+}
+
+function previewText(value) {
+  return String(value || "").slice(0, 120);
+}
+
+function resetRequestState() {
+  requestCount = 0;
+  recentRequests.length = 0;
+}
+
+function applyConfig(updates) {
+  if (!updates || typeof updates !== "object") return;
+  assignString(updates, "response_text");
+  assignNonNegativeInteger(updates, "first_token_delay_ms");
+  assignNonNegativeInteger(updates, "chunk_delay_ms");
+  assignNonNegativeInteger(updates, "chunk_count");
+  assignNonNegativeInteger(updates, "fail_first_n");
+  assignNonNegativeInteger(updates, "fail_every_n");
+  assignNonNegativeInteger(updates, "request_log_limit");
+  if (updates.fault_status !== undefined) {
+    const parsed = Number.parseInt(String(updates.fault_status), 10);
+    if (Number.isInteger(parsed) && parsed >= 400 && parsed <= 599) config.fault_status = parsed;
+  }
+  assignBoolean(updates, "fail_after_first_chunk");
+  assignBoolean(updates, "dynamic_response");
+}
+
+function assignString(updates, key) {
+  if (updates[key] !== undefined) config[key] = String(updates[key]);
+}
+
+function assignNonNegativeInteger(updates, key) {
+  if (updates[key] === undefined) return;
+  const parsed = Number.parseInt(String(updates[key]), 10);
+  if (Number.isInteger(parsed) && parsed >= 0) config[key] = parsed;
+}
+
+function assignBoolean(updates, key) {
+  if (updates[key] === undefined) return;
+  config[key] = bool(updates[key], config[key]);
+}

skills/scripts/e2e/lib/langbot-e2e.mjs

@@ -72,6 +72,7 @@ export async function writeResult(paths, result) {
 }
 
 export async function loadEnvFiles(paths = ["skills/.env", "skills/.env.local"]) {
+  const processEnvKeys = new Set(Object.keys(env));
   for (const path of paths) {
     let text = "";
     try {
@@ -86,7 +87,7 @@ export async function loadEnvFiles(paths = ["skills/.env", "skills/.env.local"])
       if (equals <= 0) continue;
       const key = trimmed.slice(0, equals).trim();
       const value = trimmed.slice(equals + 1).trim().replace(/^["']|["']$/g, "");
-      if (!(key in env)) env[key] = value;
+      if (!processEnvKeys.has(key)) env[key] = value;
     }
   }
 }

skills/scripts/e2e/pipeline-debug-chat.mjs

@@ -54,6 +54,7 @@ const debugChatSessionType = env.LANGBOT_E2E_DEBUG_CHAT_SESSION_TYPE || "person"
 const pipelineConfigDiagnosticPath = resolve(paths.evidenceDir, "pipeline-config-diagnostic.json");
 const debugChatResetDiagnosticPath = resolve(paths.evidenceDir, "debug-chat-reset-diagnostic.json");
 const pipelineConfigRestoreDiagnosticPath = resolve(paths.evidenceDir, "pipeline-config-restore-diagnostic.json");
+const metricsPath = resolve(paths.evidenceDir, "metrics.json");
 const startedAt = new Date();
 
 let browser;
@@ -80,10 +81,11 @@ let result = {
     console_log: paths.consoleLog,
     network_log: paths.networkLog,
     screenshot: paths.screenshot,
+    metrics_json: metricsPath,
     automation_result_json: paths.automationResultJson,
     result_json: paths.resultJson,
   },
-  evidence_collected: ["ui", "screenshot", "console", "network"],
+  evidence_collected: ["ui", "screenshot", "console", "network", "metrics"],
 };
 
 function boolFromEnv(value, defaultValue) {
@@ -103,6 +105,29 @@ function parseJsonEnv(key, fallback) {
   }
 }
 
+function positiveNumberEnv(key, fallback) {
+  const value = Number(env[key] || "");
+  return Number.isFinite(value) && value >= 0 ? value : fallback;
+}
+
+function percentile(values, percentileValue) {
+  if (values.length === 0) return 0;
+  const sorted = [...values].sort((a, b) => a - b);
+  const index = Math.min(sorted.length - 1, Math.ceil((percentileValue / 100) * sorted.length) - 1);
+  return Number(sorted[index].toFixed(3));
+}
+
+function stats(values) {
+  if (values.length === 0) return { min: 0, p50: 0, p95: 0, p99: 0, max: 0 };
+  return {
+    min: Number(Math.min(...values).toFixed(3)),
+    p50: percentile(values, 50),
+    p95: percentile(values, 95),
+    p99: percentile(values, 99),
+    max: Number(Math.max(...values).toFixed(3)),
+  };
+}
+
 function promptStepsFromEnv() {
   const rawSteps = parseJsonEnv("LANGBOT_E2E_PROMPTS_JSON", null);
   if (rawSteps === null) {
@@ -658,6 +683,7 @@ try {
       } else {
         for (let index = 0; index < promptSteps.length; index += 1) {
           const step = promptSteps[index];
+          const promptStartedAt = Date.now();
           const chatResult = await runDebugChatPrompt(page, {
             prompt: step.prompt,
             expectedText: step.expectedText,
@@ -665,11 +691,13 @@ try {
             imagePath: index === 0 ? imagePath : "",
             failureSignals: failureSignals.length > 0 ? failureSignals : undefined,
           });
+          const promptDurationMs = Date.now() - promptStartedAt;
           result.chat_results.push({
             index,
             expected_text: step.expectedText,
             status: chatResult.status,
             reason: chatResult.reason,
+            response_duration_ms: promptDurationMs,
             min_expected_count: chatResult.min_expected_count,
             final_count: chatResult.final_count,
             before_assistant_expected_count: chatResult.before_assistant_expected_count,
@@ -714,6 +742,56 @@ try {
   const finishedAt = new Date();
   result.finished_at = finishedAt.toISOString();
   result.finished_at_local = localIsoWithOffset(finishedAt);
+  result.duration_ms = finishedAt.getTime() - startedAt.getTime();
+  const responseDurations = result.chat_results
+    .map((item) => item.response_duration_ms)
+    .filter((value) => Number.isFinite(value));
+  const passedPrompts = result.chat_results.filter((item) => item.status === "pass").length;
+  const attemptedPrompts = result.chat_results.length;
+  const errorRate = attemptedPrompts === 0 ? 1 : Number(((attemptedPrompts - passedPrompts) / attemptedPrompts).toFixed(4));
+  const responseStats = stats(responseDurations);
+  const responseP95BudgetMs = positiveNumberEnv(
+    "LANGBOT_E2E_DEBUG_CHAT_RESPONSE_P95_MS",
+    positiveNumberEnv("LANGBOT_DEBUG_CHAT_RESPONSE_P95_MS", safeResponseTimeoutMs),
+  );
+  const maxErrorRate = positiveNumberEnv("LANGBOT_E2E_DEBUG_CHAT_MAX_ERROR_RATE", 0);
+  const metrics = {
+    probe: caseId,
+    url: result.url,
+    prompt_count: result.prompt_count,
+    attempted_prompt_count: attemptedPrompts,
+    passed_prompt_count: passedPrompts,
+    error_rate: errorRate,
+    response_duration_ms: responseStats,
+    total_duration_ms: result.duration_ms,
+    chat_results: result.chat_results,
+  };
+  result.metrics_summary = {
+    prompt_count: metrics.prompt_count,
+    attempted_prompt_count: metrics.attempted_prompt_count,
+    passed_prompt_count: metrics.passed_prompt_count,
+    error_rate: metrics.error_rate,
+    response_p50_ms: metrics.response_duration_ms.p50,
+    response_p95_ms: metrics.response_duration_ms.p95,
+    total_duration_ms: metrics.total_duration_ms,
+  };
+  result.thresholds_summary = {
+    response_p95_ms: {
+      actual: metrics.response_duration_ms.p95,
+      max: responseP95BudgetMs,
+      pass: attemptedPrompts > 0 && metrics.response_duration_ms.p95 <= responseP95BudgetMs,
+    },
+    error_rate: {
+      actual: metrics.error_rate,
+      max: maxErrorRate,
+      pass: metrics.error_rate <= maxErrorRate,
+    },
+  };
+  await writeFile(metricsPath, `${JSON.stringify(metrics, null, 2)}\n`, "utf8");
+  if (result.status === "pass" && !Object.values(result.thresholds_summary).every((item) => item.pass)) {
+    result.status = "fail";
+    result.reason = "Debug Chat performance breached response latency or error-rate thresholds.";
+  }
   const existingEvidence = {};
   for (const [key, value] of Object.entries(result.evidence)) {
     if (typeof value !== "string") continue;

skills/skills.index.json

@@ -130,6 +130,7 @@
         "references/local-agent-runner.md",
         "references/mcp-stdio-testing.md",
         "references/model-provider-testing.md",
+        "references/performance-reliability-testing.md",
         "references/pipeline-debug-chat.md",
         "references/plugin-e2e-smoke.md",
         "references/sandbox-skill-authoring.md",
@@ -150,6 +151,16 @@
         "agent-runner-release-preflight",
         "agent-runner-runtime-chaos",
         "dify-agent-debug-chat",
+        "langbot-fake-provider-debug-chat-cross-pipeline-isolation",
+        "langbot-fake-provider-debug-chat-fault-recovery",
+        "langbot-fake-provider-debug-chat-load",
+        "langbot-fake-provider-debug-chat-slow-load",
+        "langbot-fault-taxonomy-contract",
+        "langbot-live-backend-latency",
+        "langbot-live-backend-log-health",
+        "langbot-live-control-plane-api",
+        "langbot-overhead-accounting-contract",
+        "langbot-space-debug-chat-concurrency-smoke",
         "langrag-kb-retrieve",
         "langrag-parser-golden-e2e",
         "langrag-sentinel-kb-discover",
@@ -165,6 +176,7 @@
         "mcp-stdio-register",
         "mcp-stdio-tool-call",
         "pipeline-debug-chat",
+        "pipeline-debug-chat-performance",
         "plugin-e2e-smoke",
         "provider-deepseek",
         "qa-plugin-smoke-live-install",
@@ -486,6 +498,316 @@
             "backend_log"
           ]
         },
+        {
+          "id": "langbot-fake-provider-debug-chat-cross-pipeline-isolation",
+          "title": "LangBot Debug Chat fake-provider cross-pipeline isolation probe",
+          "mode": "probe",
+          "area": "reliability",
+          "type": "reliability",
+          "priority": "p1",
+          "risk": "high",
+          "ci_eligible": false,
+          "tags": [
+            "reliability",
+            "debug-chat",
+            "websocket",
+            "fake-provider",
+            "isolation",
+            "concurrency",
+            "metrics"
+          ],
+          "automation": "skills/langbot-testing/probes/langbot-debug-chat-cross-pipeline-isolation.mjs",
+          "setup_automation": [
+            "node:scripts/e2e/ensure-fake-provider-cross-pipelines.mjs --write-env"
+          ],
+          "setup_provides_env": [
+            "LANGBOT_FAKE_PROVIDER_URL",
+            "LANGBOT_FAKE_PROVIDER_BASE_URL",
+            "LANGBOT_FAKE_PROVIDER_PID",
+            "LANGBOT_FAKE_PROVIDER_PIPELINE_A_URL",
+            "LANGBOT_FAKE_PROVIDER_PIPELINE_A_NAME",
+            "LANGBOT_FAKE_PROVIDER_PIPELINE_B_URL",
+            "LANGBOT_FAKE_PROVIDER_PIPELINE_B_NAME"
+          ],
+          "evidence_required": [
+            "metrics",
+            "network",
+            "api_diagnostic",
+            "filesystem"
+          ]
+        },
+        {
+          "id": "langbot-fake-provider-debug-chat-fault-recovery",
+          "title": "LangBot Debug Chat fake-provider fault recovery probe",
+          "mode": "probe",
+          "area": "reliability",
+          "type": "chaos",
+          "priority": "p1",
+          "risk": "high",
+          "ci_eligible": false,
+          "tags": [
+            "reliability",
+            "chaos",
+            "debug-chat",
+            "websocket",
+            "fake-provider",
+            "fault-injection",
+            "metrics"
+          ],
+          "automation": "skills/langbot-testing/probes/langbot-debug-chat-concurrency.mjs",
+          "setup_automation": [
+            "node:scripts/e2e/ensure-fake-provider-pipeline.mjs --write-env"
+          ],
+          "setup_provides_env": [
+            "LANGBOT_FAKE_PROVIDER_URL",
+            "LANGBOT_FAKE_PROVIDER_BASE_URL",
+            "LANGBOT_FAKE_PROVIDER_PID",
+            "LANGBOT_FAKE_PROVIDER_PROVIDER_UUID",
+            "LANGBOT_FAKE_PROVIDER_MODEL_UUID",
+            "LANGBOT_FAKE_PROVIDER_PIPELINE_URL",
+            "LANGBOT_FAKE_PROVIDER_PIPELINE_NAME"
+          ],
+          "evidence_required": [
+            "metrics",
+            "network",
+            "api_diagnostic",
+            "filesystem"
+          ]
+        },
+        {
+          "id": "langbot-fake-provider-debug-chat-load",
+          "title": "LangBot Debug Chat controlled fake-provider load probe",
+          "mode": "probe",
+          "area": "performance",
+          "type": "performance",
+          "priority": "p1",
+          "risk": "medium",
+          "ci_eligible": false,
+          "tags": [
+            "performance",
+            "debug-chat",
+            "websocket",
+            "fake-provider",
+            "load",
+            "metrics"
+          ],
+          "automation": "skills/langbot-testing/probes/langbot-debug-chat-concurrency.mjs",
+          "setup_automation": [
+            "node:scripts/e2e/ensure-fake-provider-pipeline.mjs --write-env"
+          ],
+          "setup_provides_env": [
+            "LANGBOT_FAKE_PROVIDER_URL",
+            "LANGBOT_FAKE_PROVIDER_BASE_URL",
+            "LANGBOT_FAKE_PROVIDER_PID",
+            "LANGBOT_FAKE_PROVIDER_PROVIDER_UUID",
+            "LANGBOT_FAKE_PROVIDER_MODEL_UUID",
+            "LANGBOT_FAKE_PROVIDER_PIPELINE_URL",
+            "LANGBOT_FAKE_PROVIDER_PIPELINE_NAME"
+          ],
+          "evidence_required": [
+            "metrics",
+            "network",
+            "api_diagnostic",
+            "filesystem"
+          ]
+        },
+        {
+          "id": "langbot-fake-provider-debug-chat-slow-load",
+          "title": "LangBot Debug Chat slow fake-provider load probe",
+          "mode": "probe",
+          "area": "performance",
+          "type": "performance",
+          "priority": "p1",
+          "risk": "medium",
+          "ci_eligible": false,
+          "tags": [
+            "performance",
+            "debug-chat",
+            "websocket",
+            "fake-provider",
+            "slow-provider",
+            "load",
+            "metrics"
+          ],
+          "automation": "skills/langbot-testing/probes/langbot-debug-chat-concurrency.mjs",
+          "setup_automation": [
+            "node:scripts/e2e/ensure-fake-provider-pipeline.mjs --write-env"
+          ],
+          "setup_provides_env": [
+            "LANGBOT_FAKE_PROVIDER_URL",
+            "LANGBOT_FAKE_PROVIDER_BASE_URL",
+            "LANGBOT_FAKE_PROVIDER_PID",
+            "LANGBOT_FAKE_PROVIDER_PROVIDER_UUID",
+            "LANGBOT_FAKE_PROVIDER_MODEL_UUID",
+            "LANGBOT_FAKE_PROVIDER_PIPELINE_URL",
+            "LANGBOT_FAKE_PROVIDER_PIPELINE_NAME"
+          ],
+          "evidence_required": [
+            "metrics",
+            "network",
+            "api_diagnostic",
+            "filesystem"
+          ]
+        },
+        {
+          "id": "langbot-fault-taxonomy-contract",
+          "title": "LangBot fault taxonomy and cleanup contract",
+          "mode": "probe",
+          "area": "reliability",
+          "type": "chaos",
+          "priority": "p1",
+          "risk": "medium",
+          "ci_eligible": true,
+          "tags": [
+            "reliability",
+            "chaos",
+            "contract",
+            "synthetic"
+          ],
+          "automation": "skills/langbot-testing/probes/langbot-fault-taxonomy-contract.mjs",
+          "setup_automation": [],
+          "setup_provides_env": [],
+          "evidence_required": [
+            "metrics",
+            "filesystem"
+          ]
+        },
+        {
+          "id": "langbot-live-backend-latency",
+          "title": "LangBot live backend basic latency probe",
+          "mode": "probe",
+          "area": "performance",
+          "type": "performance",
+          "priority": "p1",
+          "risk": "medium",
+          "ci_eligible": false,
+          "tags": [
+            "performance",
+            "live-backend",
+            "latency",
+            "metrics"
+          ],
+          "automation": "skills/langbot-testing/probes/langbot-live-backend-latency.mjs",
+          "setup_automation": [],
+          "setup_provides_env": [],
+          "evidence_required": [
+            "metrics",
+            "network",
+            "api_diagnostic",
+            "filesystem"
+          ]
+        },
+        {
+          "id": "langbot-live-backend-log-health",
+          "title": "LangBot live backend log health probe",
+          "mode": "probe",
+          "area": "reliability",
+          "type": "reliability",
+          "priority": "p1",
+          "risk": "medium",
+          "ci_eligible": false,
+          "tags": [
+            "reliability",
+            "live-backend",
+            "backend-log",
+            "metrics"
+          ],
+          "automation": "skills/langbot-testing/probes/langbot-live-backend-log-health.mjs",
+          "setup_automation": [],
+          "setup_provides_env": [],
+          "evidence_required": [
+            "metrics",
+            "backend_log",
+            "filesystem"
+          ]
+        },
+        {
+          "id": "langbot-live-control-plane-api",
+          "title": "LangBot live control-plane API probe",
+          "mode": "probe",
+          "area": "performance",
+          "type": "performance",
+          "priority": "p1",
+          "risk": "medium",
+          "ci_eligible": false,
+          "tags": [
+            "performance",
+            "reliability",
+            "live-backend",
+            "control-plane",
+            "metrics"
+          ],
+          "automation": "skills/langbot-testing/probes/langbot-live-control-plane-api.mjs",
+          "setup_automation": [],
+          "setup_provides_env": [],
+          "evidence_required": [
+            "metrics",
+            "network",
+            "api_diagnostic",
+            "filesystem"
+          ]
+        },
+        {
+          "id": "langbot-overhead-accounting-contract",
+          "title": "LangBot overhead accounting metrics contract",
+          "mode": "probe",
+          "area": "performance",
+          "type": "performance",
+          "priority": "p1",
+          "risk": "medium",
+          "ci_eligible": true,
+          "tags": [
+            "performance",
+            "metrics",
+            "contract",
+            "synthetic"
+          ],
+          "automation": "skills/langbot-testing/probes/langbot-overhead-accounting-contract.mjs",
+          "setup_automation": [],
+          "setup_provides_env": [],
+          "evidence_required": [
+            "metrics",
+            "resource_log",
+            "filesystem"
+          ]
+        },
+        {
+          "id": "langbot-space-debug-chat-concurrency-smoke",
+          "title": "LangBot Debug Chat real Space-provider concurrency smoke",
+          "mode": "probe",
+          "area": "performance",
+          "type": "performance",
+          "priority": "p1",
+          "risk": "high",
+          "ci_eligible": false,
+          "tags": [
+            "performance",
+            "debug-chat",
+            "websocket",
+            "space",
+            "live-provider",
+            "smoke",
+            "metrics"
+          ],
+          "automation": "skills/langbot-testing/probes/langbot-debug-chat-concurrency.mjs",
+          "setup_automation": [
+            "node:scripts/e2e/ensure-local-agent-pipeline.mjs --write-env"
+          ],
+          "setup_provides_env": [
+            "LANGBOT_PIPELINE_URL",
+            "LANGBOT_PIPELINE_NAME",
+            "LANGBOT_LOCAL_AGENT_PIPELINE_URL",
+            "LANGBOT_LOCAL_AGENT_PIPELINE_NAME",
+            "LANGBOT_LOCAL_AGENT_MODEL_UUID",
+            "LANGBOT_E2E_MODEL_UUID"
+          ],
+          "evidence_required": [
+            "metrics",
+            "network",
+            "api_diagnostic",
+            "filesystem"
+          ]
+        },
         {
           "id": "langrag-kb-retrieve",
           "title": "LangRAG knowledge base ingests and retrieves a sentinel document",
@@ -911,6 +1233,38 @@
             "backend_log"
           ]
         },
+        {
+          "id": "pipeline-debug-chat-performance",
+          "title": "Pipeline Debug Chat user-path performance probe",
+          "mode": "agent-browser",
+          "area": "pipeline",
+          "type": "performance",
+          "priority": "p1",
+          "risk": "medium",
+          "ci_eligible": false,
+          "tags": [
+            "performance",
+            "pipeline",
+            "debug-chat",
+            "user-path",
+            "metrics"
+          ],
+          "automation": "scripts/e2e/pipeline-debug-chat.mjs",
+          "setup_automation": [
+            "node:scripts/e2e/ensure-local-agent-pipeline.mjs --write-env"
+          ],
+          "setup_provides_env": [
+            "LANGBOT_PIPELINE_URL",
+            "LANGBOT_PIPELINE_NAME"
+          ],
+          "evidence_required": [
+            "ui",
+            "screenshot",
+            "console",
+            "network",
+            "metrics"
+          ]
+        },
         {
           "id": "plugin-e2e-smoke",
           "title": "Plugin system installs a local plugin and exposes tool/page APIs",
@@ -1059,6 +1413,12 @@
       "suites": [
         "agent-runner-release-gate",
         "core-smoke",
+        "langbot-debug-chat-isolation-gate",
+        "langbot-debug-chat-load-gate",
+        "langbot-live-backend-gate",
+        "langbot-performance-contract-gate",
+        "langbot-performance-reliability-gate",
+        "langbot-user-path-performance-gate",
         "local-agent-gate"
       ],
       "suite_summaries": [
@@ -1121,6 +1481,113 @@
             "local-agent-basic-debug-chat"
           ]
         },
+        {
+          "id": "langbot-debug-chat-isolation-gate",
+          "title": "LangBot Debug Chat isolation gate",
+          "description": "Manual/non-required cross-pipeline Debug Chat isolation gate. Current releases may fail this gate because of product bug #2286; use it as regression evidence after the routing fix lands.",
+          "type": "reliability",
+          "priority": "p1",
+          "tags": [
+            "reliability",
+            "debug-chat",
+            "websocket",
+            "isolation",
+            "concurrency"
+          ],
+          "cases": [
+            "langbot-fake-provider-debug-chat-cross-pipeline-isolation"
+          ]
+        },
+        {
+          "id": "langbot-debug-chat-load-gate",
+          "title": "LangBot Debug Chat load gate",
+          "description": "Manual/non-required message-path load checks for Pipeline Debug Chat: controlled fake-provider baseline, slow-provider and fault-recovery profiles, plus optional real Space-provider smoke. Cross-pipeline isolation is split into langbot-debug-chat-isolation-gate because current releases may fail it due to product bug #2286.",
+          "type": "performance",
+          "priority": "p1",
+          "tags": [
+            "performance",
+            "debug-chat",
+            "websocket",
+            "load"
+          ],
+          "cases": [
+            "langbot-fake-provider-debug-chat-load",
+            "langbot-fake-provider-debug-chat-slow-load",
+            "langbot-fake-provider-debug-chat-fault-recovery",
+            "langbot-space-debug-chat-concurrency-smoke"
+          ]
+        },
+        {
+          "id": "langbot-live-backend-gate",
+          "title": "LangBot live backend reliability gate",
+          "description": "Live backend control-plane responsiveness and runtime log health checks for a locally running LangBot instance.",
+          "type": "reliability",
+          "priority": "p1",
+          "tags": [
+            "performance",
+            "reliability",
+            "live-backend",
+            "metrics"
+          ],
+          "cases": [
+            "langbot-live-backend-latency",
+            "langbot-live-control-plane-api",
+            "langbot-live-backend-log-health"
+          ]
+        },
+        {
+          "id": "langbot-performance-contract-gate",
+          "title": "LangBot performance contract gate",
+          "description": "Fast synthetic contract checks for performance metric accounting and non-destructive reliability fault taxonomy.",
+          "type": "contract",
+          "priority": "p1",
+          "tags": [
+            "performance",
+            "reliability",
+            "contract",
+            "metrics"
+          ],
+          "cases": [
+            "langbot-overhead-accounting-contract",
+            "langbot-fault-taxonomy-contract"
+          ]
+        },
+        {
+          "id": "langbot-performance-reliability-gate",
+          "title": "LangBot performance and reliability starter gate",
+          "description": "Starter gate for LangBot performance accounting, live backend control-plane latency, and non-destructive fault taxonomy checks.",
+          "type": "reliability",
+          "priority": "p1",
+          "tags": [
+            "performance",
+            "reliability",
+            "metrics",
+            "chaos"
+          ],
+          "cases": [
+            "langbot-overhead-accounting-contract",
+            "langbot-fault-taxonomy-contract",
+            "langbot-live-backend-latency",
+            "langbot-live-control-plane-api",
+            "langbot-live-backend-log-health"
+          ]
+        },
+        {
+          "id": "langbot-user-path-performance-gate",
+          "title": "LangBot user-path performance gate",
+          "description": "Browser-visible performance checks for user-facing LangBot paths such as Pipeline Debug Chat.",
+          "type": "performance",
+          "priority": "p1",
+          "tags": [
+            "performance",
+            "browser",
+            "debug-chat",
+            "user-path"
+          ],
+          "cases": [
+            "pipeline-debug-chat-performance"
+          ]
+        },
         {
           "id": "local-agent-gate",
           "title": "Local Agent runner regression gate",
@@ -1265,6 +1732,7 @@
         "sandbox-native-tools-unavailable",
         "socks-proxy-without-socksio",
         "survey-widget-blocks-debug-chat",
+        "telemetry-proxy-noise",
         "tool-name-collision-between-mcp-and-plugin",
         "uv-run-resyncs-local-sdk"
       ],
@@ -1449,6 +1917,14 @@
             "mcp-stdio-tool-call"
           ]
         },
+        {
+          "id": "telemetry-proxy-noise",
+          "title": "Telemetry posting fails through the proxy while the target flow succeeds",
+          "category": "env_issue",
+          "related_cases": [
+            "langbot-space-debug-chat-concurrency-smoke"
+          ]
+        },
         {
           "id": "tool-name-collision-between-mcp-and-plugin",
           "title": "MCP and plugin expose the same tool name",

skills/skills/.env.example

@@ -26,6 +26,23 @@ LANGBOT_NO_PROXY=localhost,127.0.0.1,::1
 LANGBOT_PIPELINE_URL=
 LANGBOT_PIPELINE_NAME=
 
+# Optional fake OpenAI-compatible provider controls for Debug Chat load tests.
+# Leave URL empty to let setup automation start a local provider and write the
+# selected URL to skills/.env.local.
+LANGBOT_FAKE_PROVIDER_URL=
+LANGBOT_FAKE_PROVIDER_HOST=127.0.0.1
+LANGBOT_FAKE_PROVIDER_PORT=
+LANGBOT_FAKE_PROVIDER_MODEL_NAME=gpt-4o-mini
+LANGBOT_FAKE_PROVIDER_RESPONSE_TEXT=OK
+LANGBOT_FAKE_PROVIDER_FIRST_TOKEN_DELAY_MS=25
+LANGBOT_FAKE_PROVIDER_CHUNK_DELAY_MS=10
+LANGBOT_FAKE_PROVIDER_CHUNK_COUNT=0
+LANGBOT_FAKE_PROVIDER_FAIL_FIRST_N=0
+LANGBOT_FAKE_PROVIDER_FAIL_EVERY_N=0
+LANGBOT_FAKE_PROVIDER_FAULT_STATUS=500
+LANGBOT_FAKE_PROVIDER_FAIL_AFTER_FIRST_CHUNK=false
+LANGBOT_FAKE_PROVIDER_DYNAMIC_RESPONSE=true
+
 # Optional case-specific runner targets. Prefer these for runner-specific cases
 # so the automation cannot silently test the wrong runner.
 LANGBOT_LOCAL_AGENT_PIPELINE_URL=

skills/skills/langbot-env-setup/references/service-startup.md

@@ -53,7 +53,7 @@ Start the new frontend from the web repo:
 
 ```bash
 cd "$LANGBOT_WEB_REPO"
-npm run dev
+VITE_API_BASE_URL="$LANGBOT_BACKEND_URL" pnpm dev --host 0.0.0.0
 ```
 
 Healthy startup includes:
@@ -68,6 +68,10 @@ Quick check:
 curl -I --max-time 3 "$LANGBOT_FRONTEND_URL"
 ```
 
+If `VITE_API_BASE_URL` is missing, Vite still serves the page but frontend API
+calls may go to the frontend port instead of the backend port. That produces
+false browser failures in login, wizard, pipeline, and Debug Chat cases.
+
 ## Completion Signal
 
 Environment setup is not complete until the required frontend/backend URLs are reachable and the chosen browser-control path can open the WebUI.

skills/skills/langbot-testing/SKILL.md

@@ -21,6 +21,7 @@ Use this skill when an agent needs to verify LangBot behavior through the WebUI
 - **Sandbox-backed skill authoring**: read `references/sandbox-skill-authoring.md`.
 - **LangRAG knowledge bases**: read `references/langrag-knowledge-base.md`.
 - **MCP stdio tool testing**: read `references/mcp-stdio-testing.md`.
+- **Performance, reliability, or chaos probes**: read `references/performance-reliability-testing.md`.
 - **Drive a live instance over MCP (not raw HTTP)**: use the `langbot-mcp-ops` skill — the instance exposes an MCP server at `http://<host>:5300/mcp` (reuses API keys). Useful for setting up bots/pipelines/models as test fixtures programmatically.
 - **Known failures and fixes**: read `references/troubleshooting.md`.
 - **Reusable test groups**: run `bin/lbs suite list` and `bin/lbs suite plan <suite-id>` before manually assembling a case set.
@@ -36,6 +37,8 @@ Use this skill when an agent needs to verify LangBot behavior through the WebUI
 - Use an authenticated browser profile prepared by `langbot-env-setup`.
 - Do not expose API keys, OAuth secrets, tokens, or localStorage token values in output.
 - A WebUI test is not complete until the visible UI result is checked against backend logs or network behavior.
+- A performance result is not complete without `metrics` evidence and a clear split between LangBot overhead and external provider/tool/network time.
+- A chaos or reliability result is not complete until the fault scope, cleanup, and recovery checks are recorded.
 - For a suite, use `bin/lbs suite start <suite-id>` to create the suite evidence root, per-case directories, and `suite-start.json`/`suite-start.md` handoff files; use `bin/lbs test result <case-id>` to write final per-case `result.json`, then run `bin/lbs suite report <suite-id> --evidence-dir <dir>`.
 - Do not mark a case `pass` until `test result --evidence` covers every value in the case's `evidence_required`.
 - For runner-specific Debug Chat cases, use the case-specific pipeline env declared by `automation_pipeline_url_env` / `automation_pipeline_name_env`; do not silently reuse a generic `LANGBOT_PIPELINE_URL`.

skills/skills/langbot-testing/cases/langbot-fake-provider-debug-chat-cross-pipeline-isolation.yaml

@@ -0,0 +1,84 @@
+id: langbot-fake-provider-debug-chat-cross-pipeline-isolation
+title: "LangBot Debug Chat fake-provider cross-pipeline isolation probe"
+mode: probe
+area: reliability
+type: reliability
+priority: p1
+risk: high
+ci_eligible: false
+tags:
+  - reliability
+  - debug-chat
+  - websocket
+  - fake-provider
+  - isolation
+  - concurrency
+  - metrics
+skills:
+  - langbot-env-setup
+  - langbot-testing
+env:
+  - LANGBOT_BACKEND_URL
+  - LANGBOT_FRONTEND_URL
+  - LANGBOT_E2E_LOGIN_USER
+automation: skills/langbot-testing/probes/langbot-debug-chat-cross-pipeline-isolation.mjs
+automation_env:
+  - LANGBOT_BACKEND_URL
+  - LANGBOT_E2E_LOGIN_USER
+  - LANGBOT_FAKE_PROVIDER_URL
+  - LANGBOT_FAKE_PROVIDER_PIPELINE_A_URL
+  - LANGBOT_FAKE_PROVIDER_PIPELINE_A_NAME
+  - LANGBOT_FAKE_PROVIDER_PIPELINE_B_URL
+  - LANGBOT_FAKE_PROVIDER_PIPELINE_B_NAME
+automation_debug_chat_load_requests: "6"
+automation_debug_chat_load_concurrency: "4"
+automation_debug_chat_load_timeout_ms: "30000"
+automation_debug_chat_load_response_p95_ms: "5000"
+automation_debug_chat_load_max_error_rate: "0"
+automation_debug_chat_load_prompt_template: '请只回复 "{expected}"，不要解释，不要添加其他字符。'
+automation_debug_chat_load_stream: "true"
+automation_debug_chat_load_reset: "true"
+metrics_thresholds_json: '{"cross_pipeline_leak_count":{"max":0},"response_p95_ms":{"max":5000},"error_rate":{"max":0}}'
+load_profile_json: '{"requests_per_pipeline":6,"pipelines":2,"concurrency":4,"path":"Pipeline Debug Chat WebSocket","provider":"controlled fake OpenAI-compatible provider","metric":"cross-pipeline response isolation and send-to-final-assistant-response"}'
+setup_automation:
+  - "node:scripts/e2e/ensure-fake-provider-cross-pipelines.mjs --write-env"
+setup_provides_env:
+  - LANGBOT_FAKE_PROVIDER_URL
+  - LANGBOT_FAKE_PROVIDER_BASE_URL
+  - LANGBOT_FAKE_PROVIDER_PID
+  - LANGBOT_FAKE_PROVIDER_PIPELINE_A_URL
+  - LANGBOT_FAKE_PROVIDER_PIPELINE_A_NAME
+  - LANGBOT_FAKE_PROVIDER_PIPELINE_B_URL
+  - LANGBOT_FAKE_PROVIDER_PIPELINE_B_NAME
+steps:
+  - "Start or reuse the local fake OpenAI-compatible provider."
+  - "Create or update two local-agent pipelines that both point at the controlled fake provider."
+  - "Reset both Debug Chat sessions and the fake-provider request log."
+  - "Open concurrent WebSocket Debug Chat connections to both pipelines and send unique pipeline-scoped response tokens."
+checks:
+  - "automation-result.json status is pass only when every request receives its own expected token and cross_pipeline_leak_count is zero."
+  - "metrics_summary includes by_pipeline status counts, fake-provider request count, and LangBot/provider timing estimates."
+  - "samples.json contains per-request pipeline labels so any leak can be attributed to the receiving pipeline."
+evidence_required:
+  - metrics
+  - network
+  - api_diagnostic
+  - filesystem
+diagnostics:
+  - "This probe targets Debug Chat isolation under concurrent traffic from two pipelines."
+  - "It is designed to expose regressions where global pipeline state causes one pipeline's assistant response to be delivered to another pipeline's Debug Chat session."
+  - "Same-pipeline foreign responses are tolerated because Debug Chat intentionally broadcasts within the same pipeline/session; cross-pipeline tokens are never tolerated."
+  - "Known product bug: current releases may fail this probe because Debug Chat replies can read singleton WebSocket proxy pipeline state after another pipeline overwrites it. See https://github.com/langbot-app/LangBot/issues/2286."
+expected_failures:
+  - "https://github.com/langbot-app/LangBot/issues/2286"
+success_patterns:
+  - "Debug Chat cross-pipeline isolation probe passed"
+failure_patterns:
+  - "cross_pipeline_leak"
+  - "Timed out after"
+  - "WebSocket connection error"
+  - "Final assistant response did not include"
+troubleshooting:
+  - backend-not-listening
+  - debug-chat-history-contaminates-automation
+  - local-agent-model-route-unavailable

skills/skills/langbot-testing/cases/langbot-fake-provider-debug-chat-fault-recovery.yaml

@@ -0,0 +1,95 @@
+id: langbot-fake-provider-debug-chat-fault-recovery
+title: "LangBot Debug Chat fake-provider fault recovery probe"
+mode: probe
+area: reliability
+type: chaos
+priority: p1
+risk: high
+ci_eligible: false
+tags:
+  - reliability
+  - chaos
+  - debug-chat
+  - websocket
+  - fake-provider
+  - fault-injection
+  - metrics
+skills:
+  - langbot-env-setup
+  - langbot-testing
+env:
+  - LANGBOT_BACKEND_URL
+  - LANGBOT_FRONTEND_URL
+  - LANGBOT_E2E_LOGIN_USER
+automation: skills/langbot-testing/probes/langbot-debug-chat-concurrency.mjs
+automation_env:
+  - LANGBOT_BACKEND_URL
+  - LANGBOT_E2E_LOGIN_USER
+  - LANGBOT_FAKE_PROVIDER_PIPELINE_URL
+  - LANGBOT_FAKE_PROVIDER_PIPELINE_NAME
+automation_pipeline_url_env: LANGBOT_FAKE_PROVIDER_PIPELINE_URL
+automation_pipeline_name_env: LANGBOT_FAKE_PROVIDER_PIPELINE_NAME
+automation_debug_chat_load_requests: "6"
+automation_debug_chat_load_concurrency: "1"
+automation_debug_chat_load_timeout_ms: "15000"
+automation_debug_chat_load_response_p95_ms: "5000"
+automation_debug_chat_load_max_error_rate: "0"
+automation_debug_chat_load_min_ok_count: "6"
+automation_debug_chat_load_min_provider_fault_count: "2"
+automation_debug_chat_load_expected_prefix: "FAULTQA"
+automation_debug_chat_load_prompt_template: '请只回复 "{expected}"，不要解释，不要添加其他字符。'
+automation_debug_chat_load_stream: "true"
+automation_debug_chat_load_reset: "true"
+automation_debug_chat_load_fail_on_final_mismatch: "true"
+automation_fake_provider_first_token_delay_ms: "25"
+automation_fake_provider_chunk_delay_ms: "10"
+automation_fake_provider_chunk_count: "0"
+automation_fake_provider_fail_first_n: "2"
+automation_fake_provider_fail_every_n: "0"
+automation_fake_provider_fault_status: "503"
+metrics_thresholds_json: '{"response_p95_ms":{"max":5000},"error_rate":{"max":0},"ok_count_min":{"min":6},"fake_provider_fault_count_min":{"min":2}}'
+fault_model_json: '{"provider_fault":"HTTP 503 for first 2 fake-provider chat completions after reset","expected_behavior":"LangBot retries or otherwise recovers from bounded provider failures so every Debug Chat request receives its expected response without backend crash."}'
+load_profile_json: '{"requests":6,"concurrency":1,"path":"Pipeline Debug Chat WebSocket","provider":"controlled fake OpenAI-compatible provider","classification":"fault-recovery-not-throughput-benchmark"}'
+setup_automation:
+  - "node:scripts/e2e/ensure-fake-provider-pipeline.mjs --write-env"
+setup_provides_env:
+  - LANGBOT_FAKE_PROVIDER_URL
+  - LANGBOT_FAKE_PROVIDER_BASE_URL
+  - LANGBOT_FAKE_PROVIDER_PID
+  - LANGBOT_FAKE_PROVIDER_PROVIDER_UUID
+  - LANGBOT_FAKE_PROVIDER_MODEL_UUID
+  - LANGBOT_FAKE_PROVIDER_PIPELINE_URL
+  - LANGBOT_FAKE_PROVIDER_PIPELINE_NAME
+steps:
+  - "Configure the local fake provider to return HTTP 503 for the first two chat completions after reset."
+  - "Create or update the LangBot provider, model, and local-agent pipeline that points at the fake provider."
+  - "Reset the target Debug Chat session and fake-provider request counter."
+  - "Send a sequential Debug Chat batch and verify later requests recover after the injected provider faults."
+checks:
+  - "automation-result.json status is pass when the fake provider records at least two injected faults, every Debug Chat request succeeds, and total user-visible error rate stays at zero."
+  - "metrics_summary includes fake_provider_fault_count and status_counts for the same run window."
+  - "backend logs show request handling for the same run window without unexpected Traceback or task-leak findings."
+evidence_required:
+  - metrics
+  - network
+  - api_diagnostic
+  - filesystem
+diagnostics:
+  - "This is a fault-recovery probe, not a throughput benchmark."
+  - "Provider faults may be retried inside the provider/requester path; judge this case by fake_provider_fault_count plus user-visible success/error metrics."
+  - "The profile uses concurrency 1 because Debug Chat broadcasts assistant responses to every connection in a session, and failed responses do not carry the unique success token needed for concurrent attribution."
+success_patterns:
+  - "Debug Chat WebSocket concurrency probe passed"
+  - "Streaming completed"
+failure_patterns:
+  - "fake_provider_fault"
+  - "HTTP 503"
+  - "Timed out after"
+  - "All models failed during streaming setup"
+expected_failures:
+  - "fake_provider_fault"
+  - "HTTP 503"
+troubleshooting:
+  - backend-not-listening
+  - debug-chat-history-contaminates-automation
+  - local-agent-model-route-unavailable

skills/skills/langbot-testing/cases/langbot-fake-provider-debug-chat-load.yaml

@@ -0,0 +1,81 @@
+id: langbot-fake-provider-debug-chat-load
+title: "LangBot Debug Chat controlled fake-provider load probe"
+mode: probe
+area: performance
+type: performance
+priority: p1
+risk: medium
+ci_eligible: false
+tags:
+  - performance
+  - debug-chat
+  - websocket
+  - fake-provider
+  - load
+  - metrics
+skills:
+  - langbot-env-setup
+  - langbot-testing
+env:
+  - LANGBOT_BACKEND_URL
+  - LANGBOT_FRONTEND_URL
+  - LANGBOT_E2E_LOGIN_USER
+automation: skills/langbot-testing/probes/langbot-debug-chat-concurrency.mjs
+automation_env:
+  - LANGBOT_BACKEND_URL
+  - LANGBOT_E2E_LOGIN_USER
+  - LANGBOT_FAKE_PROVIDER_PIPELINE_URL
+  - LANGBOT_FAKE_PROVIDER_PIPELINE_NAME
+automation_pipeline_url_env: LANGBOT_FAKE_PROVIDER_PIPELINE_URL
+automation_pipeline_name_env: LANGBOT_FAKE_PROVIDER_PIPELINE_NAME
+automation_debug_chat_load_requests: "12"
+automation_debug_chat_load_concurrency: "4"
+automation_debug_chat_load_timeout_ms: "30000"
+automation_debug_chat_load_response_p95_ms: "5000"
+automation_debug_chat_load_first_response_p95_ms: "3000"
+automation_debug_chat_load_max_error_rate: "0"
+automation_debug_chat_load_expected_prefix: "FAKEQA"
+automation_debug_chat_load_prompt_template: '请只回复 "{expected}"，不要解释，不要添加其他字符。'
+automation_debug_chat_load_stream: "true"
+automation_debug_chat_load_reset: "true"
+metrics_thresholds_json: '{"response_p95_ms":{"max":5000},"first_response_p95_ms":{"max":3000},"error_rate":{"max":0}}'
+load_profile_json: '{"requests":12,"concurrency":4,"path":"Pipeline Debug Chat WebSocket","provider":"controlled fake OpenAI-compatible provider","metric":"send-to-final-assistant-response"}'
+setup_automation:
+  - "node:scripts/e2e/ensure-fake-provider-pipeline.mjs --write-env"
+setup_provides_env:
+  - LANGBOT_FAKE_PROVIDER_URL
+  - LANGBOT_FAKE_PROVIDER_BASE_URL
+  - LANGBOT_FAKE_PROVIDER_PID
+  - LANGBOT_FAKE_PROVIDER_PROVIDER_UUID
+  - LANGBOT_FAKE_PROVIDER_MODEL_UUID
+  - LANGBOT_FAKE_PROVIDER_PIPELINE_URL
+  - LANGBOT_FAKE_PROVIDER_PIPELINE_NAME
+steps:
+  - "Start or reuse the local fake OpenAI-compatible provider."
+  - "Create or update the LangBot provider, model, and local-agent pipeline that points at the fake provider."
+  - "Reset the target Debug Chat session."
+  - "Open concurrent WebSocket Debug Chat connections and send unique deterministic prompts through the real backend pipeline."
+checks:
+  - "automation-result.json status is pass when every request receives its own expected assistant response."
+  - "metrics_summary includes request count, concurrency, p50/p95 response latency, first response latency, throughput, and error rate."
+  - "thresholds_summary shows response_p95_ms, first_response_p95_ms, and error_rate pass."
+evidence_required:
+  - metrics
+  - network
+  - api_diagnostic
+  - filesystem
+diagnostics:
+  - "This probe removes external model latency from the measurement; it still exercises the live LangBot backend, provider requester, local-agent runner, pipeline, and Debug Chat WebSocket adapter."
+  - "Use this as the repeatable message-path baseline before comparing against Space or another real provider."
+success_patterns:
+  - "Debug Chat WebSocket concurrency probe passed"
+  - "Streaming completed"
+failure_patterns:
+  - "WebSocket connection error"
+  - "Timed out after"
+  - "Final assistant response did not include"
+  - "All models failed during streaming setup"
+troubleshooting:
+  - backend-not-listening
+  - debug-chat-history-contaminates-automation
+  - local-agent-model-route-unavailable

skills/skills/langbot-testing/cases/langbot-fake-provider-debug-chat-slow-load.yaml

@@ -0,0 +1,88 @@
+id: langbot-fake-provider-debug-chat-slow-load
+title: "LangBot Debug Chat slow fake-provider load probe"
+mode: probe
+area: performance
+type: performance
+priority: p1
+risk: medium
+ci_eligible: false
+tags:
+  - performance
+  - debug-chat
+  - websocket
+  - fake-provider
+  - slow-provider
+  - load
+  - metrics
+skills:
+  - langbot-env-setup
+  - langbot-testing
+env:
+  - LANGBOT_BACKEND_URL
+  - LANGBOT_FRONTEND_URL
+  - LANGBOT_E2E_LOGIN_USER
+automation: skills/langbot-testing/probes/langbot-debug-chat-concurrency.mjs
+automation_env:
+  - LANGBOT_BACKEND_URL
+  - LANGBOT_E2E_LOGIN_USER
+  - LANGBOT_FAKE_PROVIDER_PIPELINE_URL
+  - LANGBOT_FAKE_PROVIDER_PIPELINE_NAME
+automation_pipeline_url_env: LANGBOT_FAKE_PROVIDER_PIPELINE_URL
+automation_pipeline_name_env: LANGBOT_FAKE_PROVIDER_PIPELINE_NAME
+automation_debug_chat_load_requests: "8"
+automation_debug_chat_load_concurrency: "4"
+automation_debug_chat_load_timeout_ms: "45000"
+automation_debug_chat_load_response_p95_ms: "10000"
+automation_debug_chat_load_first_response_p95_ms: "7000"
+automation_debug_chat_load_max_error_rate: "0"
+automation_debug_chat_load_expected_prefix: "SLOWQA"
+automation_debug_chat_load_prompt_template: '请只回复 "{expected}"，不要解释，不要添加其他字符。'
+automation_debug_chat_load_stream: "true"
+automation_debug_chat_load_reset: "true"
+automation_fake_provider_first_token_delay_ms: "1000"
+automation_fake_provider_chunk_delay_ms: "250"
+automation_fake_provider_chunk_count: "4"
+automation_fake_provider_fail_first_n: "0"
+automation_fake_provider_fail_every_n: "0"
+automation_fake_provider_fault_status: "500"
+metrics_thresholds_json: '{"response_p95_ms":{"max":10000},"first_response_p95_ms":{"max":7000},"error_rate":{"max":0}}'
+load_profile_json: '{"requests":8,"concurrency":4,"path":"Pipeline Debug Chat WebSocket","provider":"controlled slow fake OpenAI-compatible provider","metric":"send-to-final-assistant-response","provider_profile":{"first_token_delay_ms":1000,"chunk_delay_ms":250,"chunk_count":4}}'
+setup_automation:
+  - "node:scripts/e2e/ensure-fake-provider-pipeline.mjs --write-env"
+setup_provides_env:
+  - LANGBOT_FAKE_PROVIDER_URL
+  - LANGBOT_FAKE_PROVIDER_BASE_URL
+  - LANGBOT_FAKE_PROVIDER_PID
+  - LANGBOT_FAKE_PROVIDER_PROVIDER_UUID
+  - LANGBOT_FAKE_PROVIDER_MODEL_UUID
+  - LANGBOT_FAKE_PROVIDER_PIPELINE_URL
+  - LANGBOT_FAKE_PROVIDER_PIPELINE_NAME
+steps:
+  - "Configure the local fake provider with deterministic slow streaming latency."
+  - "Create or update the LangBot provider, model, and local-agent pipeline that points at the fake provider."
+  - "Reset the target Debug Chat session."
+  - "Open concurrent WebSocket Debug Chat connections and send unique deterministic prompts through the real backend pipeline."
+checks:
+  - "automation-result.json status is pass when every request receives its own expected assistant response."
+  - "metrics_summary shows zero errors under the slow-provider profile."
+  - "thresholds_summary shows response_p95_ms, first_response_p95_ms, and error_rate pass."
+evidence_required:
+  - metrics
+  - network
+  - api_diagnostic
+  - filesystem
+diagnostics:
+  - "This probe keeps the model deterministic while injecting provider latency, so it catches backend timeout, streaming, and WebSocket backpressure issues without Space variability."
+  - "Compare with langbot-fake-provider-debug-chat-load to separate fixed LangBot overhead from provider-latency amplification."
+success_patterns:
+  - "Debug Chat WebSocket concurrency probe passed"
+  - "Streaming completed"
+failure_patterns:
+  - "WebSocket connection error"
+  - "Timed out after"
+  - "Final assistant response did not include"
+  - "All models failed during streaming setup"
+troubleshooting:
+  - backend-not-listening
+  - debug-chat-history-contaminates-automation
+  - local-agent-model-route-unavailable

skills/skills/langbot-testing/cases/langbot-fault-taxonomy-contract.yaml

@@ -0,0 +1,35 @@
+id: langbot-fault-taxonomy-contract
+title: "LangBot fault taxonomy and cleanup contract"
+mode: probe
+area: reliability
+type: chaos
+priority: p1
+risk: medium
+ci_eligible: true
+tags:
+  - reliability
+  - chaos
+  - contract
+  - synthetic
+skills:
+  - langbot-testing
+automation: skills/langbot-testing/probes/langbot-fault-taxonomy-contract.mjs
+fault_model_json: '{"kind":"taxonomy-contract","destructive":false,"scenarios":["provider-timeout","plugin-runtime-disconnect","mcp-stdio-server-exit","operator-missing-login","transient-marketplace-timeout"]}'
+steps:
+  - "Run `rtk bin/lbs test run langbot-fault-taxonomy-contract --dry-run` first; remove `--dry-run` after checking the evidence directory."
+  - "Automation validates that representative fault scenarios declare target, injected fault, expected status, recovery check, and cleanup."
+  - "Review metrics.json, fault-model.json, and automation-result.json under LBS_EVIDENCE_DIR."
+checks:
+  - "automation-result.json status is pass."
+  - "Every scenario has an expected status in pass, fail, blocked, env_issue, or flaky."
+  - "Every scenario declares a cleanup action and recovery check."
+evidence_required:
+  - metrics
+  - filesystem
+diagnostics:
+  - "This is a non-destructive taxonomy contract probe; it does not inject real runtime faults."
+  - "Use it as a gate before adding live chaos cases that kill runtimes, route traffic through a proxy, or disrupt a backend dependency."
+success_patterns:
+  - "Fault taxonomy contract declares status"
+failure_patterns:
+  - "missing required scenario fields"

skills/skills/langbot-testing/cases/langbot-live-backend-latency.yaml

@@ -0,0 +1,42 @@
+id: langbot-live-backend-latency
+title: "LangBot live backend basic latency probe"
+mode: probe
+area: performance
+type: performance
+priority: p1
+risk: medium
+ci_eligible: false
+tags:
+  - performance
+  - live-backend
+  - latency
+  - metrics
+skills:
+  - langbot-testing
+env:
+  - LANGBOT_BACKEND_URL
+automation: skills/langbot-testing/probes/langbot-live-backend-latency.mjs
+metrics_thresholds_json: '{"backend_p95_ms":{"max":1000},"error_rate":{"max":0}}'
+load_profile_json: '{"requests":12,"concurrency":2,"endpoints":["/healthz"]}'
+steps:
+  - "Confirm the selected LangBot backend is the intended test target."
+  - "Run `rtk bin/lbs test run langbot-live-backend-latency --dry-run` first; remove `--dry-run` after checking LANGBOT_BACKEND_URL and evidence directory."
+  - "Automation sends a small request batch to LANGBOT_BACKEND_URL/healthz and records latency, status counts, and network errors."
+checks:
+  - "automation-result.json status is pass when the backend responds and p95/error-rate thresholds pass."
+  - "automation-result.json status is env_issue when the backend is not reachable."
+  - "metrics.json and network.log are written under LBS_EVIDENCE_DIR."
+evidence_required:
+  - metrics
+  - network
+  - api_diagnostic
+  - filesystem
+diagnostics:
+  - "This probe measures backend health endpoint reachability latency only; it does not cover model/provider, browser, Debug Chat, RAG, or plugin runtime latency."
+success_patterns:
+  - "Live backend latency probe passed"
+failure_patterns:
+  - "Backend did not respond"
+  - "breached latency or error-rate thresholds"
+troubleshooting:
+  - socks-proxy-without-socksio

skills/skills/langbot-testing/cases/langbot-live-backend-log-health.yaml

@@ -0,0 +1,45 @@
+id: langbot-live-backend-log-health
+title: "LangBot live backend log health probe"
+mode: probe
+area: reliability
+type: reliability
+priority: p1
+risk: medium
+ci_eligible: false
+tags:
+  - reliability
+  - live-backend
+  - backend-log
+  - metrics
+skills:
+  - langbot-testing
+env:
+  - LANGBOT_BACKEND_URL
+automation: skills/langbot-testing/probes/langbot-live-backend-log-health.mjs
+metrics_thresholds_json: '{"fail_count":{"max":0}}'
+load_profile_json: '{"lookback_seconds":300,"log_source":"LANGBOT_BACKEND_LOG or latest LANGBOT_REPO/data/logs/langbot-*.log"}'
+steps:
+  - "Confirm the selected LangBot backend log belongs to the intended test target."
+  - "Run `rtk bin/lbs test run langbot-live-backend-log-health --dry-run` first; remove `--dry-run` after checking evidence directory and log source."
+  - "Automation scans the recent backend log window for fail-severity runtime findings such as Traceback, ImportError, ERROR, unclosed sessions, and unawaited coroutines."
+checks:
+  - "automation-result.json status is pass only when fail_count is 0."
+  - "metrics_summary includes scanned_line_count, fail_count, warning_count, and finding_count."
+  - "findings.json and scanned-backend.log are written under LBS_EVIDENCE_DIR."
+evidence_required:
+  - metrics
+  - backend_log
+  - filesystem
+diagnostics:
+  - "Set LANGBOT_BACKEND_LOG to an explicit log path when the latest log file is not the run target."
+  - "Set LANGBOT_BACKEND_LOG_SINCE or LANGBOT_BACKEND_LOG_LOOKBACK_SECONDS to control the scan window."
+  - "This probe measures runtime log health; it does not prove user-facing Debug Chat, plugin, model, or RAG behavior."
+success_patterns:
+  - "Live backend log health passed"
+failure_patterns:
+  - "Traceback"
+  - "ImportError"
+  - "ERROR"
+  - "unclosed"
+troubleshooting:
+  - socks-proxy-without-socksio

skills/skills/langbot-testing/cases/langbot-live-control-plane-api.yaml

@@ -0,0 +1,44 @@
+id: langbot-live-control-plane-api
+title: "LangBot live control-plane API probe"
+mode: probe
+area: performance
+type: performance
+priority: p1
+risk: medium
+ci_eligible: false
+tags:
+  - performance
+  - reliability
+  - live-backend
+  - control-plane
+  - metrics
+skills:
+  - langbot-testing
+env:
+  - LANGBOT_BACKEND_URL
+automation: skills/langbot-testing/probes/langbot-live-control-plane-api.mjs
+metrics_thresholds_json: '{"error_rate":{"max":0},"response_shape_failures":{"max":0},"healthz_p95_ms":{"max":500},"system_info_p95_ms":{"max":1000}}'
+load_profile_json: '{"requests":20,"concurrency":4,"endpoints":["/healthz","/api/v1/system/info"],"auth_required":false}'
+steps:
+  - "Confirm the selected LangBot backend is the intended test target."
+  - "Run `rtk bin/lbs test run langbot-live-control-plane-api --dry-run` first; remove `--dry-run` after checking LANGBOT_BACKEND_URL and evidence directory."
+  - "Automation sends a small request batch to /healthz and /api/v1/system/info, then validates status code, JSON shape, and latency budgets."
+checks:
+  - "automation-result.json status is pass when every control-plane request returns HTTP 200, JSON code 0, and required response fields."
+  - "metrics_summary includes per-endpoint p50/p95 latency, error rate, status counts, and response_shape_failures."
+  - "thresholds_summary shows error_rate, response_shape_failures, healthz_p95_ms, and system_info_p95_ms all pass."
+evidence_required:
+  - metrics
+  - network
+  - api_diagnostic
+  - filesystem
+diagnostics:
+  - "This probe measures unauthenticated backend control-plane readiness; it does not cover authenticated UI flows, Debug Chat, model calls, plugins, or RAG."
+  - "A system_info shape failure usually means the API contract or startup state changed and should be investigated before treating latency as healthy."
+success_patterns:
+  - "Live control-plane API probe passed"
+failure_patterns:
+  - "Backend did not respond"
+  - "breached shape, latency, or error-rate thresholds"
+troubleshooting:
+  - socks-proxy-without-socksio

skills/skills/langbot-testing/cases/langbot-overhead-accounting-contract.yaml

@@ -0,0 +1,37 @@
+id: langbot-overhead-accounting-contract
+title: "LangBot overhead accounting metrics contract"
+mode: probe
+area: performance
+type: performance
+priority: p1
+risk: medium
+ci_eligible: true
+tags:
+  - performance
+  - metrics
+  - contract
+  - synthetic
+skills:
+  - langbot-testing
+automation: skills/langbot-testing/probes/langbot-overhead-accounting-contract.mjs
+metrics_thresholds_json: '{"sample_count":{"min":50},"langbot_overhead_p95_ms":{"max":25},"accounting_gap_max_ms":{"max":0.001}}'
+load_profile_json: '{"kind":"synthetic-overhead-accounting","samples":80,"external_latency_segments":["provider","external_tool","network"]}'
+steps:
+  - "Run `rtk bin/lbs test run langbot-overhead-accounting-contract --dry-run` first; remove `--dry-run` after checking the evidence directory."
+  - "Automation generates deterministic message-path latency samples and separates LangBot overhead from provider/tool/network latency."
+  - "Review metrics.json, thresholds.json, resource-log.json, and automation-result.json under LBS_EVIDENCE_DIR."
+checks:
+  - "automation-result.json status is pass."
+  - "metrics_summary includes sample_count, langbot_overhead_p95_ms, e2e_latency_p95_ms, external_latency_p95_ms, and accounting_gap_max_ms."
+  - "thresholds_summary shows sample_count, langbot_overhead_p95_ms, and accounting_gap_max_ms all pass."
+evidence_required:
+  - metrics
+  - resource_log
+  - filesystem
+diagnostics:
+  - "This is a synthetic contract probe for the QA harness; it is not live product performance."
+  - "Use it to verify that reports can carry overhead accounting metrics before running live backend or browser performance probes."
+success_patterns:
+  - "Overhead accounting contract passed"
+failure_patterns:
+  - "breached one or more thresholds"

skills/skills/langbot-testing/cases/langbot-space-debug-chat-concurrency-smoke.yaml

@@ -0,0 +1,84 @@
+id: langbot-space-debug-chat-concurrency-smoke
+title: "LangBot Debug Chat real Space-provider concurrency smoke"
+mode: probe
+area: performance
+type: performance
+priority: p1
+risk: high
+ci_eligible: false
+tags:
+  - performance
+  - debug-chat
+  - websocket
+  - space
+  - live-provider
+  - smoke
+  - metrics
+skills:
+  - langbot-env-setup
+  - langbot-testing
+env:
+  - LANGBOT_BACKEND_URL
+  - LANGBOT_FRONTEND_URL
+  - LANGBOT_E2E_LOGIN_USER
+automation: skills/langbot-testing/probes/langbot-debug-chat-concurrency.mjs
+automation_env:
+  - LANGBOT_BACKEND_URL
+  - LANGBOT_E2E_LOGIN_USER
+  - LANGBOT_LOCAL_AGENT_PIPELINE_URL
+  - LANGBOT_LOCAL_AGENT_PIPELINE_NAME
+automation_pipeline_url_env: LANGBOT_LOCAL_AGENT_PIPELINE_URL
+automation_pipeline_name_env: LANGBOT_LOCAL_AGENT_PIPELINE_NAME
+automation_debug_chat_load_requests: "3"
+automation_debug_chat_load_concurrency: "2"
+automation_debug_chat_load_timeout_ms: "120000"
+automation_debug_chat_load_response_p95_ms: "120000"
+automation_debug_chat_load_max_error_rate: "0"
+automation_debug_chat_load_expected_prefix: "SPACEQA"
+automation_debug_chat_load_prompt_template: '请只回复 "{expected}"，不要解释，不要添加其他字符。'
+automation_debug_chat_load_stream: "true"
+automation_debug_chat_load_reset: "true"
+metrics_thresholds_json: '{"response_p95_ms":{"max":120000},"error_rate":{"max":0}}'
+load_profile_json: '{"requests":3,"concurrency":2,"path":"Pipeline Debug Chat WebSocket","provider":"LangBot Space model route","metric":"send-to-final-assistant-response","classification":"smoke-not-benchmark"}'
+setup_automation:
+  - "node:scripts/e2e/ensure-local-agent-pipeline.mjs --write-env"
+setup_provides_env:
+  - LANGBOT_PIPELINE_URL
+  - LANGBOT_PIPELINE_NAME
+  - LANGBOT_LOCAL_AGENT_PIPELINE_URL
+  - LANGBOT_LOCAL_AGENT_PIPELINE_NAME
+  - LANGBOT_LOCAL_AGENT_MODEL_UUID
+  - LANGBOT_E2E_MODEL_UUID
+preconditions:
+  - "The selected local LangBot instance is safe for a low-volume real Space model smoke run."
+  - "Treat Space/provider/network failures as environment or dependency findings until fake-provider baseline evidence separates LangBot overhead."
+steps:
+  - "Prepare a local-agent pipeline with a tested Space model and fallback models."
+  - "Reset the target Debug Chat session."
+  - "Open a small number of concurrent WebSocket Debug Chat connections and send unique deterministic prompts through the live Space provider path."
+checks:
+  - "automation-result.json status is pass when every request receives its own expected assistant response."
+  - "metrics_summary includes request count, concurrency, p95 response latency, throughput, and error rate."
+  - "The report classifies the result as a live-provider smoke, not a stable LangBot overhead benchmark."
+evidence_required:
+  - metrics
+  - network
+  - api_diagnostic
+  - filesystem
+diagnostics:
+  - "This probe measures real user-path latency through Space and includes provider latency, model behavior, and network effects."
+  - "Compare with langbot-fake-provider-debug-chat-load before attributing slow or failed runs to LangBot itself."
+success_patterns:
+  - "Debug Chat WebSocket concurrency probe passed"
+  - "Streaming completed"
+failure_patterns:
+  - "invalid api key"
+  - "WebSocket connection error"
+  - "Timed out after"
+  - "Final assistant response did not include"
+  - "All models failed during streaming setup"
+troubleshooting:
+  - local-agent-model-route-unavailable
+  - marketplace-network-flaky
+  - proxy-env-mismatch
+  - telemetry-proxy-noise

skills/skills/langbot-testing/cases/pipeline-debug-chat-performance.yaml

@@ -0,0 +1,80 @@
+id: pipeline-debug-chat-performance
+title: "Pipeline Debug Chat user-path performance probe"
+mode: agent-browser
+area: pipeline
+type: performance
+priority: p1
+risk: medium
+ci_eligible: false
+tags:
+  - performance
+  - pipeline
+  - debug-chat
+  - user-path
+  - metrics
+skills:
+  - langbot-env-setup
+  - langbot-testing
+env:
+  - LANGBOT_FRONTEND_URL
+  - LANGBOT_BACKEND_URL
+env_any:
+  - LANGBOT_PIPELINE_URL|LANGBOT_PIPELINE_NAME
+automation: scripts/e2e/pipeline-debug-chat.mjs
+automation_env:
+  - LANGBOT_FRONTEND_URL
+  - LANGBOT_BACKEND_URL
+  - LANGBOT_BROWSER_PROFILE
+  - LANGBOT_CHROMIUM_EXECUTABLE
+  - LANGBOT_E2E_PROMPT
+  - LANGBOT_E2E_EXPECTED_TEXT
+  - LANGBOT_E2E_RESPONSE_TIMEOUT_MS
+automation_env_any:
+  - LANGBOT_PIPELINE_URL|LANGBOT_PIPELINE_NAME
+automation_prompt: "请只回复 OK，用于性能测试。"
+automation_expected_text: "OK"
+automation_response_timeout_ms: "120000"
+automation_reset_debug_chat: "true"
+automation_debug_chat_response_p95_ms: "120000"
+automation_debug_chat_max_error_rate: "0"
+metrics_thresholds_json: '{"response_p95_ms":{"max":120000},"error_rate":{"max":0}}'
+load_profile_json: '{"prompts":1,"browser":true,"path":"Pipeline Debug Chat","metric":"send-to-visible-completion"}'
+setup_automation:
+  - "node:scripts/e2e/ensure-local-agent-pipeline.mjs --write-env"
+setup_provides_env:
+  - LANGBOT_PIPELINE_URL
+  - LANGBOT_PIPELINE_NAME
+preconditions:
+  - "LANGBOT_PIPELINE_URL or LANGBOT_PIPELINE_NAME points to the pipeline intended for this Debug Chat performance run."
+  - "The target pipeline is safe to reset Debug Chat history for this run."
+  - "The target pipeline has a known-good runner/model; provider latency should be interpreted separately from LangBot overhead."
+steps:
+  - "Open LANGBOT_FRONTEND_URL with the prepared browser profile."
+  - "Open the target pipeline and select Debug Chat."
+  - "Reset Debug Chat history through the backend API when configured."
+  - "Send the deterministic prompt and wait for the expected assistant response."
+checks:
+  - "automation-result.json status is pass when the expected assistant response appears."
+  - "metrics_summary includes response_p50_ms, response_p95_ms, error_rate, and total_duration_ms."
+  - "thresholds_summary shows response_p95_ms and error_rate pass."
+evidence_required:
+  - ui
+  - screenshot
+  - console
+  - network
+  - metrics
+diagnostics:
+  - "This case measures browser-visible send-to-completion latency; it does not split provider latency from LangBot overhead."
+  - "Use backend logs and provider diagnostics to explain slow runs before calling them LangBot regressions."
+success_patterns:
+  - "Processing request from person_websocket"
+  - "Streaming completed"
+failure_patterns:
+  - "Action invoke_llm_stream call timed out"
+  - "Task exception was never retrieved"
+  - "All models failed during streaming setup"
+troubleshooting:
+  - debug-chat-history-contaminates-automation
+  - local-agent-model-route-unavailable
+  - plugin-runtime-timeout
+  - proxy-env-mismatch

skills/skills/langbot-testing/fixtures/plugins/qa-plugin-smoke/.gitignore

@@ -1 +1,3 @@
-dist/
+dist/*
+!dist/
+!dist/qa-plugin-smoke-0.1.0.lbpkg

skills/skills/langbot-testing/probes/langbot-debug-chat-concurrency.mjs

@@ -0,0 +1,837 @@
+#!/usr/bin/env node
+
+import crypto from "node:crypto";
+import net from "node:net";
+import tls from "node:tls";
+import { mkdir, writeFile } from "node:fs/promises";
+import { join, resolve } from "node:path";
+import { env, exit } from "node:process";
+import {
+  apiJson,
+  appendLine,
+  ensureEvidence,
+  evidencePaths,
+  loadEnvFiles,
+  localIsoWithOffset,
+  redact,
+  resetAndAuthLocalUser,
+  writeResult,
+} from "../../../scripts/e2e/lib/langbot-e2e.mjs";
+import {
+  buildProviderTimingMetrics,
+  summarizeFakeProviderState,
+} from "./lib/fake-provider-timing.mjs";
+
+const DEFAULT_LOCAL_PASSWORD = "LangBotE2ELocalPass!2026";
+
+await loadEnvFiles();
+const caseId = env.LBS_CASE_ID || "langbot-debug-chat-concurrency";
+const paths = evidencePaths(caseId);
+await ensureEvidence(paths);
+
+const startedAt = new Date();
+const metricsPath = resolve(paths.evidenceDir, "metrics.json");
+const samplesPath = resolve(paths.evidenceDir, "samples.json");
+const fakeProviderStatePath = resolve(paths.evidenceDir, "fake-provider-state.json");
+const resetDiagnosticPath = resolve(paths.evidenceDir, "debug-chat-reset-diagnostic.json");
+const backendUrl = env.LANGBOT_BACKEND_URL || "";
+const fakeProviderUrl = env.LANGBOT_FAKE_PROVIDER_URL || "";
+const pipelineUrl = env.LANGBOT_E2E_PIPELINE_URL || env.LANGBOT_PIPELINE_URL || "";
+const pipelineName = env.LANGBOT_E2E_PIPELINE_NAME || env.LANGBOT_PIPELINE_NAME || "";
+const sessionType = env.LANGBOT_DEBUG_CHAT_LOAD_SESSION_TYPE || env.LANGBOT_E2E_DEBUG_CHAT_SESSION_TYPE || "person";
+const totalRequests = positiveInteger(env.LANGBOT_DEBUG_CHAT_LOAD_REQUESTS, defaultRequests(caseId));
+const concurrency = Math.min(totalRequests, positiveInteger(env.LANGBOT_DEBUG_CHAT_LOAD_CONCURRENCY, defaultConcurrency(caseId)));
+const timeoutMs = positiveInteger(env.LANGBOT_DEBUG_CHAT_LOAD_TIMEOUT_MS, defaultTimeout(caseId));
+const expectedPrefix = env.LANGBOT_DEBUG_CHAT_LOAD_EXPECTED_PREFIX || "LBQA";
+const promptTemplate = env.LANGBOT_DEBUG_CHAT_LOAD_PROMPT_TEMPLATE
+  || "请只回复 \"{expected}\"，不要解释，不要添加其他字符。";
+const stream = bool(env.LANGBOT_DEBUG_CHAT_LOAD_STREAM, true);
+const resetBeforeRun = bool(env.LANGBOT_DEBUG_CHAT_LOAD_RESET, true);
+const responseP95BudgetMs = positiveNumber(env.LANGBOT_DEBUG_CHAT_LOAD_RESPONSE_P95_MS, defaultP95Budget(caseId));
+const firstResponseP95BudgetMs = positiveNumber(env.LANGBOT_DEBUG_CHAT_LOAD_FIRST_RESPONSE_P95_MS, 0);
+const maxErrorRate = positiveNumber(env.LANGBOT_DEBUG_CHAT_LOAD_MAX_ERROR_RATE, 0);
+const minErrorRate = positiveNumber(env.LANGBOT_DEBUG_CHAT_LOAD_MIN_ERROR_RATE, 0);
+const minErrorCount = nonNegativeInteger(env.LANGBOT_DEBUG_CHAT_LOAD_MIN_ERROR_COUNT, 0);
+const minOkCount = nonNegativeInteger(env.LANGBOT_DEBUG_CHAT_LOAD_MIN_OK_COUNT, 0);
+const minProviderFaultCount = nonNegativeInteger(env.LANGBOT_DEBUG_CHAT_LOAD_MIN_PROVIDER_FAULT_COUNT, 0);
+const failOnFinalMismatch = bool(env.LANGBOT_DEBUG_CHAT_LOAD_FAIL_ON_FINAL_MISMATCH, false);
+const failureSignals = textList(env.LANGBOT_E2E_FAILURE_SIGNALS || env.LANGBOT_DEBUG_CHAT_LOAD_FAILURE_SIGNALS || "");
+
+const result = {
+  source: "automation",
+  case_id: caseId,
+  run_id: paths.runId,
+  status: "fail",
+  reason: "",
+  started_at: startedAt.toISOString(),
+  started_at_local: localIsoWithOffset(startedAt),
+  finished_at: "",
+  finished_at_local: "",
+  duration_ms: 0,
+  backend_url: backendUrl,
+  pipeline_url: pipelineUrl,
+  pipeline_name: pipelineName,
+  pipeline_id: "",
+  session_type: sessionType,
+  load_profile: {
+    requests: totalRequests,
+    concurrency,
+    timeout_ms: timeoutMs,
+    stream,
+    reset_before_run: resetBeforeRun,
+    fail_on_final_mismatch: failOnFinalMismatch,
+  },
+  evidence: {
+    network_log: paths.networkLog,
+    metrics_json: metricsPath,
+    samples_json: samplesPath,
+    fake_provider_state_json: fakeProviderStatePath,
+    debug_chat_reset_diagnostic_json: resetDiagnosticPath,
+    automation_result_json: paths.automationResultJson,
+    result_json: paths.resultJson,
+  },
+  evidence_collected: ["metrics", "network", "api_diagnostic", "filesystem"],
+};
+
+try {
+  if (!backendUrl) {
+    result.status = "env_issue";
+    throw new Error("LANGBOT_BACKEND_URL is not configured.");
+  }
+  if (!["person", "group"].includes(sessionType)) {
+    throw new Error(`LANGBOT_DEBUG_CHAT_LOAD_SESSION_TYPE must be person or group, got ${sessionType}.`);
+  }
+  const backendReady = await backendReachable(backendUrl);
+  if (!backendReady) {
+    result.status = "env_issue";
+    throw new Error(`Backend did not respond at ${backendUrl}.`);
+  }
+
+  const user = env.LANGBOT_E2E_LOGIN_USER || "";
+  const password = env.LANGBOT_E2E_LOGIN_PASSWORD || DEFAULT_LOCAL_PASSWORD;
+  if (!user) {
+    result.status = "env_issue";
+    throw new Error("LANGBOT_E2E_LOGIN_USER is required so this probe can resolve/reset the Debug Chat session.");
+  }
+  const auth = await resetAndAuthLocalUser({ backendUrl, user, password });
+
+  const pipeline = await resolvePipeline({ backendUrl, token: auth.token, pipelineUrl, pipelineName });
+  result.pipeline_id = pipeline.id;
+  result.pipeline_name = pipeline.name || pipelineName;
+  if (!result.pipeline_url && env.LANGBOT_FRONTEND_URL) {
+    result.pipeline_url = `${env.LANGBOT_FRONTEND_URL.replace(/\/$/, "")}/home/pipelines?id=${encodeURIComponent(pipeline.id)}`;
+  }
+
+  if (resetBeforeRun) {
+    const reset = await apiJson(backendUrl, `/api/v1/pipelines/${encodeURIComponent(pipeline.id)}/ws/reset/${encodeURIComponent(sessionType)}`, {
+      method: "POST",
+      token: auth.token,
+    });
+    const resetDiagnostic = {
+      status: isApiFailure(reset) ? "fail" : "ready",
+      http_status: reset.status,
+      code: reset.json.code ?? null,
+      reason: isApiFailure(reset) ? reset.json.msg || "Debug Chat reset failed." : "Debug Chat session reset.",
+    };
+    await writeFile(resetDiagnosticPath, `${JSON.stringify(resetDiagnostic, null, 2)}\n`, "utf8");
+    if (resetDiagnostic.status === "fail") {
+      throw new Error(resetDiagnostic.reason);
+    }
+  }
+
+  const wsUrl = websocketUrl(backendUrl, pipeline.id, sessionType);
+  const loadStartedAt = performance.now();
+  const samples = await runLoad({
+    wsUrl,
+    totalRequests,
+    concurrency,
+    timeoutMs,
+    promptTemplate,
+    expectedPrefix,
+    stream,
+    failOnFinalMismatch,
+    failureSignals,
+  });
+  const loadDurationMs = performance.now() - loadStartedAt;
+  const fakeProviderState = await readFakeProviderState(fakeProviderUrl);
+  if (fakeProviderState) {
+    await writeFile(fakeProviderStatePath, `${JSON.stringify(fakeProviderState, null, 2)}\n`, "utf8");
+  }
+  const metrics = buildMetrics({
+    samples,
+    totalRequests,
+    concurrency,
+    timeoutMs,
+    loadDurationMs,
+    backendUrl,
+    pipelineId: pipeline.id,
+    sessionType,
+    fakeProviderState,
+  });
+  const thresholds = buildThresholds(metrics);
+  const passed = Object.values(thresholds).every((item) => item.pass);
+  result.status = passed ? "pass" : "fail";
+  result.reason = passed
+    ? "Debug Chat WebSocket concurrency probe passed all thresholds."
+    : "Debug Chat WebSocket concurrency probe breached latency or error-rate thresholds.";
+  result.metrics_summary = {
+    requests: metrics.total_requests,
+    concurrency: metrics.concurrency,
+    ok_count: metrics.ok_count,
+    error_count: metrics.error_count,
+    timeout_count: metrics.timeout_count,
+    error_rate: metrics.error_rate,
+    response_p50_ms: metrics.response_duration_ms.p50,
+    response_p95_ms: metrics.response_duration_ms.p95,
+    first_assistant_event_p95_ms: metrics.first_assistant_event_ms.p95,
+    first_assistant_content_p95_ms: metrics.first_assistant_content_ms.p95,
+    first_response_p95_ms: metrics.first_response_ms.p95,
+    throughput_rps: metrics.throughput_rps,
+    status_counts: metrics.status_counts,
+    fake_provider_request_count: metrics.fake_provider?.request_count ?? null,
+    fake_provider_fault_count: metrics.fake_provider?.fault_count ?? null,
+    fake_provider_duration_p95_ms: metrics.provider_timing?.provider_duration_ms.p95 ?? null,
+    langbot_overhead_estimate_p95_ms: metrics.provider_timing?.langbot_overhead_estimate_ms.p95 ?? null,
+    send_to_provider_start_p95_ms: metrics.provider_timing?.send_to_provider_start_ms.p95 ?? null,
+    provider_finish_to_ws_final_p95_ms: metrics.provider_timing?.provider_finish_to_ws_final_ms.p95 ?? null,
+    provider_timing_matched_request_count: metrics.provider_timing?.matched_request_count ?? null,
+  };
+  result.thresholds_summary = thresholds;
+  result.artifacts = {
+    metrics_json: metricsPath,
+    samples_json: samplesPath,
+    fake_provider_state_json: fakeProviderState ? fakeProviderStatePath : "",
+    network_log: paths.networkLog,
+    automation_result_json: paths.automationResultJson,
+    result_json: paths.resultJson,
+  };
+
+  await writeFile(metricsPath, `${JSON.stringify({ ...metrics, thresholds }, null, 2)}\n`, "utf8");
+  await writeFile(samplesPath, `${JSON.stringify(samples, null, 2)}\n`, "utf8");
+} catch (error) {
+  if (!["env_issue", "blocked"].includes(result.status)) {
+    result.status = looksLikeEnvIssue(error) ? "env_issue" : "fail";
+  }
+  result.reason = result.reason || safeReason(error.message);
+} finally {
+  const finishedAt = new Date();
+  result.finished_at = finishedAt.toISOString();
+  result.finished_at_local = localIsoWithOffset(finishedAt);
+  result.duration_ms = finishedAt.getTime() - startedAt.getTime();
+  await mkdir(paths.evidenceDir, { recursive: true });
+  await writeResult(paths, result);
+  console.log(JSON.stringify(result, null, 2));
+}
+
+exit(result.status === "pass" ? 0 : result.status === "env_issue" || result.status === "blocked" ? 2 : 1);
+
+function defaultRequests(id) {
+  return id.includes("space") ? 3 : 12;
+}
+
+function defaultConcurrency(id) {
+  return id.includes("space") ? 1 : 4;
+}
+
+function defaultTimeout(id) {
+  return id.includes("space") ? 120_000 : 30_000;
+}
+
+function defaultP95Budget(id) {
+  return id.includes("space") ? 120_000 : 5_000;
+}
+
+function positiveInteger(value, fallback) {
+  const parsed = Number.parseInt(String(value || ""), 10);
+  return Number.isInteger(parsed) && parsed > 0 ? parsed : fallback;
+}
+
+function nonNegativeInteger(value, fallback) {
+  const parsed = Number.parseInt(String(value ?? ""), 10);
+  return Number.isInteger(parsed) && parsed >= 0 ? parsed : fallback;
+}
+
+function positiveNumber(value, fallback) {
+  const parsed = Number(value || "");
+  return Number.isFinite(parsed) && parsed >= 0 ? parsed : fallback;
+}
+
+function bool(value, fallback) {
+  if (value === undefined || value === "") return fallback;
+  if (/^(1|true|yes|on)$/i.test(String(value))) return true;
+  if (/^(0|false|no|off)$/i.test(String(value))) return false;
+  return fallback;
+}
+
+function textList(value) {
+  return String(value || "")
+    .split(/\r?\n|,/)
+    .map((item) => item.trim())
+    .filter(Boolean);
+}
+
+async function backendReachable(baseUrl) {
+  try {
+    const response = await fetch(`${baseUrl.replace(/\/$/, "")}/healthz`, {
+      signal: AbortSignal.timeout(3000),
+    });
+    return response.status < 500;
+  } catch {
+    return false;
+  }
+}
+
+async function readFakeProviderState(rootUrl) {
+  if (!rootUrl) return null;
+  try {
+    const response = await fetch(`${normalizeProviderRootUrl(rootUrl)}/__qa/config`, {
+      signal: AbortSignal.timeout(3000),
+    });
+    const json = await response.json().catch(() => ({}));
+    return {
+      status: response.ok && json.ok === true ? "loaded" : "unavailable",
+      url: normalizeProviderRootUrl(rootUrl),
+      http_status: response.status,
+      model: json.model || "",
+      config: json.config || {},
+      request_count: Number.isFinite(json.request_count) ? json.request_count : null,
+      recent_requests: Array.isArray(json.recent_requests) ? json.recent_requests : [],
+    };
+  } catch (error) {
+    return {
+      status: "unavailable",
+      url: normalizeProviderRootUrl(rootUrl),
+      reason: safeReason(error.message),
+      request_count: null,
+      recent_requests: [],
+    };
+  }
+}
+
+function normalizeProviderRootUrl(value) {
+  const trimmed = String(value || "").trim().replace(/\/$/, "");
+  return trimmed.endsWith("/v1") ? trimmed.slice(0, -3) : trimmed;
+}
+
+function pipelineIdFromUrl(url) {
+  if (!url) return "";
+  try {
+    const parsed = new URL(url);
+    return parsed.searchParams.get("id") || "";
+  } catch {
+    return "";
+  }
+}
+
+async function resolvePipeline({ backendUrl, token, pipelineUrl, pipelineName }) {
+  const idFromUrl = pipelineIdFromUrl(pipelineUrl);
+  if (idFromUrl) {
+    const response = await apiJson(backendUrl, `/api/v1/pipelines/${encodeURIComponent(idFromUrl)}`, { token });
+    const pipeline = response.json.data?.pipeline;
+    if (isApiFailure(response) || !pipeline?.uuid) {
+      throw new Error(response.json.msg || `Could not load pipeline ${idFromUrl}.`);
+    }
+    return { id: pipeline.uuid, name: pipeline.name || "" };
+  }
+  if (!pipelineName) {
+    throw new Error("Set LANGBOT_E2E_PIPELINE_URL or LANGBOT_E2E_PIPELINE_NAME before running this probe.");
+  }
+  const response = await apiJson(backendUrl, "/api/v1/pipelines", { token });
+  if (isApiFailure(response)) {
+    throw new Error(response.json.msg || "Failed to list pipelines.");
+  }
+  const pipeline = (response.json.data?.pipelines || []).find((item) => item.name === pipelineName);
+  if (!pipeline?.uuid) {
+    throw new Error(`Could not find pipeline named ${pipelineName}.`);
+  }
+  return { id: pipeline.uuid, name: pipeline.name || pipelineName };
+}
+
+function isApiFailure(response) {
+  return response.status >= 400 || (response.json.code !== undefined && response.json.code !== 0);
+}
+
+function websocketUrl(baseUrl, pipelineId, sessionType) {
+  const parsed = new URL(baseUrl);
+  parsed.protocol = parsed.protocol === "https:" ? "wss:" : "ws:";
+  parsed.pathname = `/api/v1/pipelines/${encodeURIComponent(pipelineId)}/ws/connect`;
+  parsed.search = `?session_type=${encodeURIComponent(sessionType)}`;
+  return parsed.toString();
+}
+
+async function runLoad(options) {
+  const samples = [];
+  let nextIndex = 0;
+  const workers = Array.from({ length: options.concurrency }, async () => {
+    while (nextIndex < options.totalRequests) {
+      const index = nextIndex;
+      nextIndex += 1;
+      const sample = await runSingleRequest({ ...options, index });
+      samples.push(sample);
+    }
+  });
+  await Promise.all(workers);
+  return samples.sort((left, right) => left.index - right.index);
+}
+
+function expectedForIndex(prefix, index) {
+  return `${prefix}-${String(index + 1).padStart(4, "0")}`;
+}
+
+function promptForIndex(template, expected) {
+  return template.replaceAll("{expected}", expected);
+}
+
+function runSingleRequest({
+  wsUrl,
+  index,
+  timeoutMs,
+  promptTemplate,
+  expectedPrefix,
+  stream,
+  failOnFinalMismatch,
+  failureSignals,
+}) {
+  return new Promise((resolve) => {
+    const expected = expectedForIndex(expectedPrefix, index);
+    const prompt = promptForIndex(promptTemplate, expected);
+    const sample = {
+      index,
+      status: "running",
+      ok: false,
+      expected_text: expected,
+      prompt,
+      response_text: "",
+      started_at: new Date().toISOString(),
+      started_epoch_ms: Date.now(),
+      connected_at: null,
+      connected_epoch_ms: null,
+      sent_at: null,
+      sent_epoch_ms: null,
+      first_assistant_event_at: null,
+      first_assistant_event_epoch_ms: null,
+      first_assistant_event_ms: null,
+      first_assistant_content_at: null,
+      first_assistant_content_epoch_ms: null,
+      first_assistant_content_ms: null,
+      first_response_at: null,
+      first_response_epoch_ms: null,
+      connected_ms: null,
+      first_response_ms: null,
+      response_duration_ms: null,
+      finished_at: null,
+      finished_epoch_ms: null,
+      event_count: 0,
+      foreign_response_count: 0,
+      last_foreign_response_text: "",
+      error: "",
+      close_code: null,
+      close_reason: "",
+    };
+    let closed = false;
+    let connectedAt = 0;
+    let sentAt = 0;
+    const startedAt = performance.now();
+    let client = null;
+    const timer = setTimeout(() => {
+      finish("timeout", `Timed out after ${timeoutMs} ms.`);
+    }, timeoutMs);
+
+    client = openRawWebSocket(wsUrl, {
+      onOpen() {
+        connectedAt = performance.now();
+        const now = Date.now();
+        sample.connected_at = new Date(now).toISOString();
+        sample.connected_epoch_ms = now;
+        sample.connected_ms = rounded(connectedAt - startedAt);
+      },
+      onMessage(text) {
+        sample.event_count += 1;
+        let data;
+        try {
+          data = JSON.parse(String(text || ""));
+        } catch (error) {
+          finish("error", `Invalid WebSocket JSON: ${error.message}`);
+          return;
+        }
+        appendLine(paths.networkLog, JSON.stringify({
+          request_index: index,
+          type: data.type,
+          session_type: data.session_type || "",
+          role: data.data?.role || "",
+          is_final: data.data?.is_final ?? null,
+          content_preview: redact(String(data.data?.content || data.message || "").slice(0, 200)),
+        })).catch(() => {});
+
+        if (data.type === "connected") {
+          sentAt = performance.now();
+          const now = Date.now();
+          sample.sent_at = new Date(now).toISOString();
+          sample.sent_epoch_ms = now;
+          client.send(JSON.stringify({
+            type: "message",
+            message: [{ type: "Plain", text: prompt }],
+            stream,
+          }));
+          return;
+        }
+        if (data.type === "error") {
+          finish("error", data.message || "WebSocket error message.");
+          return;
+        }
+        if (data.type !== "response" || data.data?.role !== "assistant") return;
+
+        const content = String(data.data.content || "");
+        markFirstAssistantEvent(sample, sentAt);
+        if (content) sample.response_text = content;
+        if (content) markFirstAssistantContent(sample, sentAt);
+        if (content.includes(expected) && sample.first_response_ms === null && sentAt > 0) {
+          const now = Date.now();
+          sample.first_response_at = new Date(now).toISOString();
+          sample.first_response_epoch_ms = now;
+          sample.first_response_ms = rounded(performance.now() - sentAt);
+        }
+        if (data.data.is_final === true) {
+          const ok = sample.response_text.includes(expected);
+          if (ok) {
+            if (sample.first_response_ms === null && sentAt > 0) {
+              sample.first_response_ms = rounded(performance.now() - sentAt);
+            }
+            finish("pass", "");
+          } else if (matchesFailureSignal(sample.response_text, failureSignals)) {
+            finish("app_error", `Assistant final response matched a failure signal: ${sample.response_text}`);
+          } else if (failOnFinalMismatch && !containsLoadToken(sample.response_text, expectedPrefix)) {
+            finish("mismatch", `Final assistant response did not include ${expected}: ${sample.response_text}`);
+          } else {
+            sample.foreign_response_count += 1;
+            sample.last_foreign_response_text = sample.response_text;
+          }
+        }
+      },
+      onError(error) {
+        finish("connection_error", `WebSocket connection error: ${error.message}`);
+      },
+      onClose(event) {
+        sample.close_code = event.code;
+        sample.close_reason = event.reason || "";
+        if (!closed) finish("closed", `WebSocket closed before final assistant response: ${event.code}`);
+      },
+    });
+
+    function finish(status, reason) {
+      if (closed) return;
+      closed = true;
+      clearTimeout(timer);
+      sample.status = status;
+      sample.ok = status === "pass";
+      sample.error = status === "timeout" && sample.foreign_response_count > 0
+        ? `${reason || ""} Saw ${sample.foreign_response_count} foreign assistant response(s); last=${sample.last_foreign_response_text}`
+        : reason || "";
+      if (sentAt > 0) sample.response_duration_ms = rounded(performance.now() - sentAt);
+      else sample.response_duration_ms = rounded(performance.now() - startedAt);
+      const now = Date.now();
+      sample.finished_at = new Date(now).toISOString();
+      sample.finished_epoch_ms = now;
+      try {
+        client?.close();
+      } catch {
+        // Closing a failed socket should not hide the sample result.
+      }
+      resolve(sample);
+    }
+  });
+}
+
+function markFirstAssistantEvent(sample, sentAt) {
+  if (sample.first_assistant_event_ms !== null || sentAt <= 0) return;
+  const now = Date.now();
+  sample.first_assistant_event_at = new Date(now).toISOString();
+  sample.first_assistant_event_epoch_ms = now;
+  sample.first_assistant_event_ms = rounded(performance.now() - sentAt);
+}
+
+function markFirstAssistantContent(sample, sentAt) {
+  if (sample.first_assistant_content_ms !== null || sentAt <= 0) return;
+  const now = Date.now();
+  sample.first_assistant_content_at = new Date(now).toISOString();
+  sample.first_assistant_content_epoch_ms = now;
+  sample.first_assistant_content_ms = rounded(performance.now() - sentAt);
+}
+
+function containsLoadToken(text, prefix) {
+  const escaped = String(prefix).replace(/[.*+?^${}()|[\]\\]/g, "\\$&");
+  return new RegExp(`${escaped}-\\d{4}`).test(String(text || ""));
+}
+
+function matchesFailureSignal(text, signals) {
+  const lower = String(text || "").toLowerCase();
+  return signals.some((signal) => lower.includes(signal.toLowerCase()));
+}
+
+function openRawWebSocket(wsUrl, handlers) {
+  const parsed = new URL(wsUrl);
+  const secure = parsed.protocol === "wss:";
+  const port = Number(parsed.port || (secure ? 443 : 80));
+  const host = parsed.hostname;
+  const path = `${parsed.pathname}${parsed.search}`;
+  const key = crypto.randomBytes(16).toString("base64");
+  const socket = secure
+    ? tls.connect({ host, port, servername: host })
+    : net.connect({ host, port });
+  let opened = false;
+  let closed = false;
+  let buffer = Buffer.alloc(0);
+
+  socket.setNoDelay(true);
+  socket.on("connect", () => {
+    const originProtocol = secure ? "https" : "http";
+    const request = [
+      `GET ${path} HTTP/1.1`,
+      `Host: ${parsed.host}`,
+      "Upgrade: websocket",
+      "Connection: Upgrade",
+      `Sec-WebSocket-Key: ${key}`,
+      "Sec-WebSocket-Version: 13",
+      `Origin: ${originProtocol}://${parsed.host}`,
+      "",
+      "",
+    ].join("\r\n");
+    socket.write(request);
+  });
+  socket.on("data", (chunk) => {
+    buffer = Buffer.concat([buffer, chunk]);
+    if (!opened) {
+      const headerEnd = buffer.indexOf("\r\n\r\n");
+      if (headerEnd === -1) return;
+      const headerText = buffer.slice(0, headerEnd).toString("utf8");
+      buffer = buffer.slice(headerEnd + 4);
+      if (!/^HTTP\/1\.1 101\b/i.test(headerText)) {
+        handlers.onError(new Error(`Handshake failed: ${headerText.split("\r\n")[0] || "missing status"}`));
+        socket.destroy();
+        return;
+      }
+      opened = true;
+      handlers.onOpen();
+    }
+    processFrames();
+  });
+  socket.on("error", (error) => {
+    if (!closed) handlers.onError(error);
+  });
+  socket.on("close", () => {
+    if (closed) return;
+    closed = true;
+    handlers.onClose({ code: null, reason: "" });
+  });
+
+  function processFrames() {
+    while (true) {
+      const frame = readFrame(buffer);
+      if (!frame) return;
+      buffer = buffer.slice(frame.consumed);
+      if (frame.opcode === 0x1) {
+        handlers.onMessage(frame.payload.toString("utf8"));
+      } else if (frame.opcode === 0x8) {
+        const code = frame.payload.length >= 2 ? frame.payload.readUInt16BE(0) : null;
+        const reason = frame.payload.length > 2 ? frame.payload.slice(2).toString("utf8") : "";
+        closed = true;
+        handlers.onClose({ code, reason });
+        socket.end();
+        return;
+      } else if (frame.opcode === 0x9) {
+        writeFrame(socket, 0xA, frame.payload);
+      }
+    }
+  }
+
+  return {
+    send(text) {
+      if (closed || !opened) return;
+      writeFrame(socket, 0x1, Buffer.from(text, "utf8"));
+    },
+    close() {
+      if (closed) return;
+      closed = true;
+      if (!socket.destroyed) {
+        if (opened) writeFrame(socket, 0x8, Buffer.alloc(0));
+        setTimeout(() => socket.end(), 50).unref();
+      }
+    },
+  };
+}
+
+function readFrame(buffer) {
+  if (buffer.length < 2) return null;
+  const first = buffer[0];
+  const second = buffer[1];
+  const opcode = first & 0x0f;
+  const masked = Boolean(second & 0x80);
+  let length = second & 0x7f;
+  let offset = 2;
+  if (length === 126) {
+    if (buffer.length < offset + 2) return null;
+    length = buffer.readUInt16BE(offset);
+    offset += 2;
+  } else if (length === 127) {
+    if (buffer.length < offset + 8) return null;
+    const high = buffer.readUInt32BE(offset);
+    const low = buffer.readUInt32BE(offset + 4);
+    length = high * 2 ** 32 + low;
+    offset += 8;
+  }
+  let mask = null;
+  if (masked) {
+    if (buffer.length < offset + 4) return null;
+    mask = buffer.slice(offset, offset + 4);
+    offset += 4;
+  }
+  if (buffer.length < offset + length) return null;
+  let payload = buffer.slice(offset, offset + length);
+  if (mask) {
+    payload = Buffer.from(payload);
+    for (let index = 0; index < payload.length; index += 1) {
+      payload[index] ^= mask[index % 4];
+    }
+  }
+  return {
+    opcode,
+    payload,
+    consumed: offset + length,
+  };
+}
+
+function writeFrame(socket, opcode, payload) {
+  const body = Buffer.isBuffer(payload) ? payload : Buffer.from(payload || "");
+  const mask = crypto.randomBytes(4);
+  const headerLength = body.length < 126 ? 2 : body.length <= 0xffff ? 4 : 10;
+  const header = Buffer.alloc(headerLength);
+  header[0] = 0x80 | opcode;
+  if (body.length < 126) {
+    header[1] = 0x80 | body.length;
+  } else if (body.length <= 0xffff) {
+    header[1] = 0x80 | 126;
+    header.writeUInt16BE(body.length, 2);
+  } else {
+    header[1] = 0x80 | 127;
+    header.writeUInt32BE(Math.floor(body.length / 2 ** 32), 2);
+    header.writeUInt32BE(body.length >>> 0, 6);
+  }
+  const masked = Buffer.from(body);
+  for (let index = 0; index < masked.length; index += 1) {
+    masked[index] ^= mask[index % 4];
+  }
+  socket.write(Buffer.concat([header, mask, masked]));
+}
+
+function rounded(value) {
+  return Number(value.toFixed(3));
+}
+
+function percentile(values, percentileValue) {
+  if (values.length === 0) return 0;
+  const sorted = [...values].sort((a, b) => a - b);
+  const index = Math.min(sorted.length - 1, Math.ceil((percentileValue / 100) * sorted.length) - 1);
+  return rounded(sorted[index]);
+}
+
+function stats(values) {
+  if (values.length === 0) return { min: 0, p50: 0, p95: 0, p99: 0, max: 0 };
+  return {
+    min: rounded(Math.min(...values)),
+    p50: percentile(values, 50),
+    p95: percentile(values, 95),
+    p99: percentile(values, 99),
+    max: rounded(Math.max(...values)),
+  };
+}
+
+function buildMetrics({ samples, totalRequests, concurrency, timeoutMs, loadDurationMs, backendUrl, pipelineId, sessionType, fakeProviderState }) {
+  const okSamples = samples.filter((sample) => sample.ok);
+  const statusCounts = {};
+  for (const sample of samples) {
+    statusCounts[sample.status] = (statusCounts[sample.status] || 0) + 1;
+  }
+  const errorCount = samples.length - okSamples.length;
+  return {
+    probe: caseId,
+    backend_url: backendUrl,
+    pipeline_id: pipelineId,
+    session_type: sessionType,
+    total_requests: totalRequests,
+    completed_requests: samples.length,
+    concurrency,
+    timeout_ms: timeoutMs,
+    ok_count: okSamples.length,
+    error_count: errorCount,
+    timeout_count: samples.filter((sample) => sample.status === "timeout").length,
+    error_rate: samples.length === 0 ? 1 : rounded(errorCount / samples.length),
+    load_duration_ms: rounded(loadDurationMs),
+    throughput_rps: loadDurationMs <= 0 ? 0 : rounded(okSamples.length / (loadDurationMs / 1000)),
+    status_counts: statusCounts,
+    connected_ms: stats(samples.map((sample) => sample.connected_ms).filter(Number.isFinite)),
+    first_assistant_event_ms: stats(samples.map((sample) => sample.first_assistant_event_ms).filter(Number.isFinite)),
+    first_assistant_content_ms: stats(samples.map((sample) => sample.first_assistant_content_ms).filter(Number.isFinite)),
+    first_response_ms: stats(okSamples.map((sample) => sample.first_response_ms).filter(Number.isFinite)),
+    response_duration_ms: stats(okSamples.map((sample) => sample.response_duration_ms).filter(Number.isFinite)),
+    fake_provider: summarizeFakeProviderState(fakeProviderState),
+    provider_timing: buildProviderTimingMetrics(samples, fakeProviderState),
+    samples,
+  };
+}
+
+function buildThresholds(metrics) {
+  const thresholds = {
+    error_rate: { actual: metrics.error_rate, max: maxErrorRate, pass: metrics.error_rate <= maxErrorRate },
+    response_p95_ms: {
+      actual: metrics.response_duration_ms.p95,
+      max: responseP95BudgetMs,
+      pass: metrics.ok_count > 0 && metrics.response_duration_ms.p95 <= responseP95BudgetMs,
+    },
+  };
+  if (minErrorRate > 0) {
+    thresholds.error_rate_min = {
+      actual: metrics.error_rate,
+      min: minErrorRate,
+      pass: metrics.error_rate >= minErrorRate,
+    };
+  }
+  if (minErrorCount > 0) {
+    thresholds.error_count_min = {
+      actual: metrics.error_count,
+      min: minErrorCount,
+      pass: metrics.error_count >= minErrorCount,
+    };
+  }
+  if (minOkCount > 0) {
+    thresholds.ok_count_min = {
+      actual: metrics.ok_count,
+      min: minOkCount,
+      pass: metrics.ok_count >= minOkCount,
+    };
+  }
+  if (minProviderFaultCount > 0) {
+    const actual = metrics.fake_provider?.fault_count ?? 0;
+    thresholds.fake_provider_fault_count_min = {
+      actual,
+      min: minProviderFaultCount,
+      pass: actual >= minProviderFaultCount,
+    };
+  }
+  if (firstResponseP95BudgetMs > 0) {
+    thresholds.first_response_p95_ms = {
+      actual: metrics.first_response_ms.p95,
+      max: firstResponseP95BudgetMs,
+      pass: metrics.ok_count > 0 && metrics.first_response_ms.p95 <= firstResponseP95BudgetMs,
+    };
+  }
+  return thresholds;
+}
+
+function looksLikeEnvIssue(error) {
+  const message = String(error?.message || error || "");
+  return /fetch failed|ECONNREFUSED|ENOTFOUND|LANGBOT_.*not configured|Could not read recovery_key|Backend did not respond/i.test(message);
+}
+
+function safeReason(value) {
+  return redact(String(value || "")).slice(0, 1000);
+}

skills/skills/langbot-testing/probes/langbot-debug-chat-cross-pipeline-isolation.mjs

@@ -0,0 +1,861 @@
+#!/usr/bin/env node
+
+import crypto from "node:crypto";
+import net from "node:net";
+import tls from "node:tls";
+import { mkdir, writeFile } from "node:fs/promises";
+import { resolve } from "node:path";
+import { env, exit } from "node:process";
+import {
+  apiJson,
+  appendLine,
+  ensureEvidence,
+  evidencePaths,
+  loadEnvFiles,
+  localIsoWithOffset,
+  redact,
+  resetAndAuthLocalUser,
+  writeResult,
+} from "../../../scripts/e2e/lib/langbot-e2e.mjs";
+import {
+  buildProviderTimingMetrics,
+  summarizeFakeProviderState,
+} from "./lib/fake-provider-timing.mjs";
+
+const DEFAULT_LOCAL_PASSWORD = "LangBotE2ELocalPass!2026";
+
+await loadEnvFiles();
+const caseId = env.LBS_CASE_ID || "langbot-debug-chat-cross-pipeline-isolation";
+const paths = evidencePaths(caseId);
+await ensureEvidence(paths);
+
+const startedAt = new Date();
+const metricsPath = resolve(paths.evidenceDir, "metrics.json");
+const samplesPath = resolve(paths.evidenceDir, "samples.json");
+const fakeProviderStatePath = resolve(paths.evidenceDir, "fake-provider-state.json");
+const resetDiagnosticPath = resolve(paths.evidenceDir, "debug-chat-reset-diagnostic.json");
+const backendUrl = env.LANGBOT_BACKEND_URL || "";
+const fakeProviderUrl = env.LANGBOT_FAKE_PROVIDER_URL || "";
+const sessionType = env.LANGBOT_DEBUG_CHAT_LOAD_SESSION_TYPE || env.LANGBOT_E2E_DEBUG_CHAT_SESSION_TYPE || "person";
+const requestsPerPipeline = positiveInteger(env.LANGBOT_DEBUG_CHAT_LOAD_REQUESTS, 6);
+const concurrency = Math.min(requestsPerPipeline * 2, positiveInteger(env.LANGBOT_DEBUG_CHAT_LOAD_CONCURRENCY, 4));
+const timeoutMs = positiveInteger(env.LANGBOT_DEBUG_CHAT_LOAD_TIMEOUT_MS, 30_000);
+const stream = bool(env.LANGBOT_DEBUG_CHAT_LOAD_STREAM, true);
+const resetBeforeRun = bool(env.LANGBOT_DEBUG_CHAT_LOAD_RESET, true);
+const responseP95BudgetMs = positiveNumber(env.LANGBOT_DEBUG_CHAT_LOAD_RESPONSE_P95_MS, 5_000);
+const maxErrorRate = positiveNumber(env.LANGBOT_DEBUG_CHAT_LOAD_MAX_ERROR_RATE, 0);
+const promptTemplate = env.LANGBOT_DEBUG_CHAT_LOAD_PROMPT_TEMPLATE
+  || "请只回复 \"{expected}\"，不要解释，不要添加其他字符。";
+const failureSignals = textList(env.LANGBOT_E2E_FAILURE_SIGNALS || env.LANGBOT_DEBUG_CHAT_LOAD_FAILURE_SIGNALS || "");
+
+const pipelineTargets = [
+  {
+    label: "A",
+    expectedPrefix: "PIPEA",
+    otherPrefix: "PIPEB",
+    url: env.LANGBOT_FAKE_PROVIDER_PIPELINE_A_URL || "",
+    name: env.LANGBOT_FAKE_PROVIDER_PIPELINE_A_NAME || "",
+  },
+  {
+    label: "B",
+    expectedPrefix: "PIPEB",
+    otherPrefix: "PIPEA",
+    url: env.LANGBOT_FAKE_PROVIDER_PIPELINE_B_URL || "",
+    name: env.LANGBOT_FAKE_PROVIDER_PIPELINE_B_NAME || "",
+  },
+];
+
+const result = {
+  source: "automation",
+  case_id: caseId,
+  run_id: paths.runId,
+  status: "fail",
+  reason: "",
+  started_at: startedAt.toISOString(),
+  started_at_local: localIsoWithOffset(startedAt),
+  finished_at: "",
+  finished_at_local: "",
+  duration_ms: 0,
+  backend_url: backendUrl,
+  session_type: sessionType,
+  pipelines: [],
+  load_profile: {
+    requests_per_pipeline: requestsPerPipeline,
+    total_requests: requestsPerPipeline * 2,
+    concurrency,
+    timeout_ms: timeoutMs,
+    stream,
+    reset_before_run: resetBeforeRun,
+  },
+  evidence: {
+    network_log: paths.networkLog,
+    metrics_json: metricsPath,
+    samples_json: samplesPath,
+    fake_provider_state_json: fakeProviderStatePath,
+    debug_chat_reset_diagnostic_json: resetDiagnosticPath,
+    automation_result_json: paths.automationResultJson,
+    result_json: paths.resultJson,
+  },
+  evidence_collected: ["metrics", "network", "api_diagnostic", "filesystem"],
+};
+
+try {
+  if (!backendUrl) {
+    result.status = "env_issue";
+    throw new Error("LANGBOT_BACKEND_URL is not configured.");
+  }
+  if (!["person", "group"].includes(sessionType)) {
+    throw new Error(`LANGBOT_DEBUG_CHAT_LOAD_SESSION_TYPE must be person or group, got ${sessionType}.`);
+  }
+  for (const target of pipelineTargets) {
+    if (!target.url && !target.name) {
+      result.status = "env_issue";
+      throw new Error(`Set LANGBOT_FAKE_PROVIDER_PIPELINE_${target.label}_URL or LANGBOT_FAKE_PROVIDER_PIPELINE_${target.label}_NAME.`);
+    }
+  }
+
+  const backendReady = await backendReachable(backendUrl);
+  if (!backendReady) {
+    result.status = "env_issue";
+    throw new Error(`Backend did not respond at ${backendUrl}.`);
+  }
+
+  const user = env.LANGBOT_E2E_LOGIN_USER || "";
+  const password = env.LANGBOT_E2E_LOGIN_PASSWORD || DEFAULT_LOCAL_PASSWORD;
+  if (!user) {
+    result.status = "env_issue";
+    throw new Error("LANGBOT_E2E_LOGIN_USER is required so this probe can resolve/reset Debug Chat sessions.");
+  }
+  const auth = await resetAndAuthLocalUser({ backendUrl, user, password });
+  const pipelines = [];
+  for (const target of pipelineTargets) {
+    const pipeline = await resolvePipeline({
+      backendUrl,
+      token: auth.token,
+      pipelineUrl: target.url,
+      pipelineName: target.name,
+    });
+    pipelines.push({
+      ...target,
+      id: pipeline.id,
+      name: pipeline.name || target.name,
+      wsUrl: websocketUrl(backendUrl, pipeline.id, sessionType),
+    });
+  }
+  result.pipelines = pipelines.map((pipeline) => ({
+    label: pipeline.label,
+    id: pipeline.id,
+    name: pipeline.name,
+    url: pipeline.url,
+  }));
+
+  if (resetBeforeRun) {
+    const resetDiagnostics = [];
+    for (const pipeline of pipelines) {
+      const reset = await apiJson(backendUrl, `/api/v1/pipelines/${encodeURIComponent(pipeline.id)}/ws/reset/${encodeURIComponent(sessionType)}`, {
+        method: "POST",
+        token: auth.token,
+      });
+      resetDiagnostics.push({
+        pipeline_label: pipeline.label,
+        pipeline_id: pipeline.id,
+        status: isApiFailure(reset) ? "fail" : "ready",
+        http_status: reset.status,
+        code: reset.json.code ?? null,
+        reason: isApiFailure(reset) ? reset.json.msg || "Debug Chat reset failed." : "Debug Chat session reset.",
+      });
+    }
+    await writeFile(resetDiagnosticPath, `${JSON.stringify(resetDiagnostics, null, 2)}\n`, "utf8");
+    const failedReset = resetDiagnostics.find((item) => item.status === "fail");
+    if (failedReset) throw new Error(failedReset.reason);
+  }
+  await resetFakeProvider(fakeProviderUrl);
+
+  const jobs = [];
+  for (let index = 0; index < requestsPerPipeline; index += 1) {
+    for (const pipeline of pipelines) {
+      jobs.push({ ...pipeline, index });
+    }
+  }
+
+  const loadStartedAt = performance.now();
+  const samples = await runLoad({
+    jobs,
+    concurrency,
+    timeoutMs,
+    promptTemplate,
+    stream,
+    failureSignals,
+  });
+  const loadDurationMs = performance.now() - loadStartedAt;
+  const fakeProviderState = await readFakeProviderState(fakeProviderUrl);
+  if (fakeProviderState) {
+    await writeFile(fakeProviderStatePath, `${JSON.stringify(fakeProviderState, null, 2)}\n`, "utf8");
+  }
+  const metrics = buildMetrics({
+    samples,
+    requestsPerPipeline,
+    concurrency,
+    timeoutMs,
+    loadDurationMs,
+    backendUrl,
+    sessionType,
+    fakeProviderState,
+  });
+  const thresholds = buildThresholds(metrics);
+  const passed = Object.values(thresholds).every((item) => item.pass);
+  result.status = passed ? "pass" : "fail";
+  result.reason = passed
+    ? "Debug Chat cross-pipeline isolation probe passed all thresholds."
+    : "Debug Chat cross-pipeline isolation probe found leaks, errors, or latency threshold breaches.";
+  result.metrics_summary = {
+    requests_per_pipeline: metrics.requests_per_pipeline,
+    total_requests: metrics.total_requests,
+    concurrency: metrics.concurrency,
+    ok_count: metrics.ok_count,
+    error_count: metrics.error_count,
+    cross_pipeline_leak_count: metrics.cross_pipeline_leak_count,
+    timeout_count: metrics.timeout_count,
+    error_rate: metrics.error_rate,
+    response_p95_ms: metrics.response_duration_ms.p95,
+    first_response_p95_ms: metrics.first_response_ms.p95,
+    throughput_rps: metrics.throughput_rps,
+    status_counts: metrics.status_counts,
+    by_pipeline: metrics.by_pipeline,
+    fake_provider_request_count: metrics.fake_provider?.request_count ?? null,
+    fake_provider_duration_p95_ms: metrics.provider_timing?.provider_duration_ms.p95 ?? null,
+    langbot_overhead_estimate_p95_ms: metrics.provider_timing?.langbot_overhead_estimate_ms.p95 ?? null,
+    send_to_provider_start_p95_ms: metrics.provider_timing?.send_to_provider_start_ms.p95 ?? null,
+    provider_finish_to_ws_final_p95_ms: metrics.provider_timing?.provider_finish_to_ws_final_ms.p95 ?? null,
+  };
+  result.thresholds_summary = thresholds;
+  result.artifacts = {
+    metrics_json: metricsPath,
+    samples_json: samplesPath,
+    fake_provider_state_json: fakeProviderState ? fakeProviderStatePath : "",
+    network_log: paths.networkLog,
+    automation_result_json: paths.automationResultJson,
+    result_json: paths.resultJson,
+  };
+
+  await writeFile(metricsPath, `${JSON.stringify({ ...metrics, thresholds }, null, 2)}\n`, "utf8");
+  await writeFile(samplesPath, `${JSON.stringify(samples, null, 2)}\n`, "utf8");
+} catch (error) {
+  if (!["env_issue", "blocked"].includes(result.status)) {
+    result.status = looksLikeEnvIssue(error) ? "env_issue" : "fail";
+  }
+  result.reason = result.reason || safeReason(error.message);
+} finally {
+  const finishedAt = new Date();
+  result.finished_at = finishedAt.toISOString();
+  result.finished_at_local = localIsoWithOffset(finishedAt);
+  result.duration_ms = finishedAt.getTime() - startedAt.getTime();
+  await mkdir(paths.evidenceDir, { recursive: true });
+  await writeResult(paths, result);
+  console.log(JSON.stringify(result, null, 2));
+}
+
+exit(result.status === "pass" ? 0 : result.status === "env_issue" || result.status === "blocked" ? 2 : 1);
+
+async function backendReachable(baseUrl) {
+  try {
+    const response = await fetch(`${baseUrl.replace(/\/$/, "")}/healthz`, {
+      signal: AbortSignal.timeout(3000),
+    });
+    return response.status < 500;
+  } catch {
+    return false;
+  }
+}
+
+async function resetFakeProvider(rootUrl) {
+  if (!rootUrl) return;
+  try {
+    await fetch(`${normalizeProviderRootUrl(rootUrl)}/__qa/reset`, {
+      method: "POST",
+      signal: AbortSignal.timeout(3000),
+    });
+  } catch {
+    // Missing fake-provider diagnostics should not hide the isolation result.
+  }
+}
+
+async function readFakeProviderState(rootUrl) {
+  if (!rootUrl) return null;
+  try {
+    const response = await fetch(`${normalizeProviderRootUrl(rootUrl)}/__qa/config`, {
+      signal: AbortSignal.timeout(3000),
+    });
+    const json = await response.json().catch(() => ({}));
+    return {
+      status: response.ok && json.ok === true ? "loaded" : "unavailable",
+      url: normalizeProviderRootUrl(rootUrl),
+      http_status: response.status,
+      model: json.model || "",
+      config: json.config || {},
+      request_count: Number.isFinite(json.request_count) ? json.request_count : null,
+      recent_requests: Array.isArray(json.recent_requests) ? json.recent_requests : [],
+    };
+  } catch (error) {
+    return {
+      status: "unavailable",
+      url: normalizeProviderRootUrl(rootUrl),
+      reason: safeReason(error.message),
+      request_count: null,
+      recent_requests: [],
+    };
+  }
+}
+
+function normalizeProviderRootUrl(value) {
+  const trimmed = String(value || "").trim().replace(/\/$/, "");
+  return trimmed.endsWith("/v1") ? trimmed.slice(0, -3) : trimmed;
+}
+
+function pipelineIdFromUrl(url) {
+  if (!url) return "";
+  try {
+    const parsed = new URL(url);
+    return parsed.searchParams.get("id") || "";
+  } catch {
+    return "";
+  }
+}
+
+async function resolvePipeline({ backendUrl, token, pipelineUrl, pipelineName }) {
+  const idFromUrl = pipelineIdFromUrl(pipelineUrl);
+  if (idFromUrl) {
+    const response = await apiJson(backendUrl, `/api/v1/pipelines/${encodeURIComponent(idFromUrl)}`, { token });
+    const pipeline = response.json.data?.pipeline;
+    if (isApiFailure(response) || !pipeline?.uuid) {
+      throw new Error(response.json.msg || `Could not load pipeline ${idFromUrl}.`);
+    }
+    return { id: pipeline.uuid, name: pipeline.name || "" };
+  }
+  if (!pipelineName) {
+    throw new Error("Set pipeline URL or name before running this probe.");
+  }
+  const response = await apiJson(backendUrl, "/api/v1/pipelines", { token });
+  if (isApiFailure(response)) {
+    throw new Error(response.json.msg || "Failed to list pipelines.");
+  }
+  const pipeline = (response.json.data?.pipelines || []).find((item) => item.name === pipelineName);
+  if (!pipeline?.uuid) {
+    throw new Error(`Could not find pipeline named ${pipelineName}.`);
+  }
+  return { id: pipeline.uuid, name: pipeline.name || pipelineName };
+}
+
+function isApiFailure(response) {
+  return response.status >= 400 || (response.json.code !== undefined && response.json.code !== 0);
+}
+
+function websocketUrl(baseUrl, pipelineId, sessionTypeValue) {
+  const parsed = new URL(baseUrl);
+  parsed.protocol = parsed.protocol === "https:" ? "wss:" : "ws:";
+  parsed.pathname = `/api/v1/pipelines/${encodeURIComponent(pipelineId)}/ws/connect`;
+  parsed.search = `?session_type=${encodeURIComponent(sessionTypeValue)}`;
+  return parsed.toString();
+}
+
+async function runLoad(options) {
+  const samples = [];
+  const queue = [...options.jobs];
+  const workers = Array.from({ length: options.concurrency }, async () => {
+    while (queue.length > 0) {
+      const job = queue.shift();
+      if (!job) continue;
+      const sample = await runSingleRequest({ ...options, job });
+      samples.push(sample);
+    }
+  });
+  await Promise.all(workers);
+  return samples.sort((left, right) => (
+    left.pipeline_label.localeCompare(right.pipeline_label) || left.index - right.index
+  ));
+}
+
+function expectedForIndex(prefix, index) {
+  return `${prefix}-${String(index + 1).padStart(4, "0")}`;
+}
+
+function promptForIndex(template, expected) {
+  return template.replaceAll("{expected}", expected);
+}
+
+function runSingleRequest({
+  job,
+  timeoutMs,
+  promptTemplate,
+  stream,
+  failureSignals,
+}) {
+  return new Promise((resolvePromise) => {
+    const expected = expectedForIndex(job.expectedPrefix, job.index);
+    const prompt = promptForIndex(promptTemplate, expected);
+    const sample = {
+      index: job.index,
+      pipeline_label: job.label,
+      pipeline_id: job.id,
+      pipeline_name: job.name,
+      status: "running",
+      ok: false,
+      expected_text: expected,
+      expected_prefix: job.expectedPrefix,
+      other_prefix: job.otherPrefix,
+      prompt,
+      response_text: "",
+      started_at: new Date().toISOString(),
+      started_epoch_ms: Date.now(),
+      connected_at: null,
+      connected_epoch_ms: null,
+      sent_at: null,
+      sent_epoch_ms: null,
+      first_assistant_event_at: null,
+      first_assistant_event_epoch_ms: null,
+      first_assistant_event_ms: null,
+      first_assistant_content_at: null,
+      first_assistant_content_epoch_ms: null,
+      first_assistant_content_ms: null,
+      first_response_at: null,
+      first_response_epoch_ms: null,
+      connected_ms: null,
+      first_response_ms: null,
+      response_duration_ms: null,
+      finished_at: null,
+      finished_epoch_ms: null,
+      event_count: 0,
+      same_pipeline_foreign_response_count: 0,
+      cross_pipeline_leak_count: 0,
+      last_foreign_response_text: "",
+      error: "",
+      close_code: null,
+      close_reason: "",
+    };
+    let closed = false;
+    let connectedAt = 0;
+    let sentAt = 0;
+    const startedPerf = performance.now();
+    let client = null;
+    const timer = setTimeout(() => {
+      finish("timeout", `Timed out after ${timeoutMs} ms.`);
+    }, timeoutMs);
+
+    client = openRawWebSocket(job.wsUrl, {
+      onOpen() {
+        connectedAt = performance.now();
+        const now = Date.now();
+        sample.connected_at = new Date(now).toISOString();
+        sample.connected_epoch_ms = now;
+        sample.connected_ms = rounded(connectedAt - startedPerf);
+      },
+      onMessage(text) {
+        sample.event_count += 1;
+        let data;
+        try {
+          data = JSON.parse(String(text || ""));
+        } catch (error) {
+          finish("error", `Invalid WebSocket JSON: ${error.message}`);
+          return;
+        }
+        appendLine(paths.networkLog, JSON.stringify({
+          pipeline_label: job.label,
+          request_index: job.index,
+          type: data.type,
+          session_type: data.session_type || "",
+          role: data.data?.role || "",
+          is_final: data.data?.is_final ?? null,
+          content_preview: redact(String(data.data?.content || data.message || "").slice(0, 200)),
+        })).catch(() => {});
+
+        if (data.type === "connected") {
+          sentAt = performance.now();
+          const now = Date.now();
+          sample.sent_at = new Date(now).toISOString();
+          sample.sent_epoch_ms = now;
+          client.send(JSON.stringify({
+            type: "message",
+            message: [{ type: "Plain", text: prompt }],
+            stream,
+          }));
+          return;
+        }
+        if (data.type === "error") {
+          finish("error", data.message || "WebSocket error message.");
+          return;
+        }
+        if (data.type !== "response" || data.data?.role !== "assistant") return;
+
+        const content = String(data.data.content || "");
+        markFirstAssistantEvent(sample, sentAt);
+        if (content) sample.response_text = content;
+        if (content) markFirstAssistantContent(sample, sentAt);
+        if (containsPipelineToken(content, job.otherPrefix)) {
+          sample.cross_pipeline_leak_count += 1;
+          finish("cross_pipeline_leak", `Pipeline ${job.label} received response from ${job.otherPrefix}: ${content}`);
+          return;
+        }
+        if (content.includes(expected) && sample.first_response_ms === null && sentAt > 0) {
+          const now = Date.now();
+          sample.first_response_at = new Date(now).toISOString();
+          sample.first_response_epoch_ms = now;
+          sample.first_response_ms = rounded(performance.now() - sentAt);
+        }
+        if (data.data.is_final === true) {
+          const ok = sample.response_text.includes(expected);
+          if (ok) {
+            if (sample.first_response_ms === null && sentAt > 0) {
+              const now = Date.now();
+              sample.first_response_at = new Date(now).toISOString();
+              sample.first_response_epoch_ms = now;
+              sample.first_response_ms = rounded(performance.now() - sentAt);
+            }
+            finish("pass", "");
+          } else if (matchesFailureSignal(sample.response_text, failureSignals)) {
+            finish("app_error", `Assistant final response matched a failure signal: ${sample.response_text}`);
+          } else if (containsPipelineToken(sample.response_text, job.expectedPrefix)) {
+            sample.same_pipeline_foreign_response_count += 1;
+            sample.last_foreign_response_text = sample.response_text;
+          } else {
+            finish("mismatch", `Final assistant response did not include ${expected}: ${sample.response_text}`);
+          }
+        }
+      },
+      onError(error) {
+        finish("connection_error", `WebSocket connection error: ${error.message}`);
+      },
+      onClose(event) {
+        sample.close_code = event.code;
+        sample.close_reason = event.reason || "";
+        if (!closed) finish("closed", `WebSocket closed before final assistant response: ${event.code}`);
+      },
+    });
+
+    function finish(status, reason) {
+      if (closed) return;
+      closed = true;
+      clearTimeout(timer);
+      sample.status = status;
+      sample.ok = status === "pass";
+      sample.error = status === "timeout" && sample.same_pipeline_foreign_response_count > 0
+        ? `${reason || ""} Saw ${sample.same_pipeline_foreign_response_count} same-pipeline foreign assistant response(s); last=${sample.last_foreign_response_text}`
+        : reason || "";
+      if (sentAt > 0) sample.response_duration_ms = rounded(performance.now() - sentAt);
+      else sample.response_duration_ms = rounded(performance.now() - startedPerf);
+      const now = Date.now();
+      sample.finished_at = new Date(now).toISOString();
+      sample.finished_epoch_ms = now;
+      try {
+        client?.close();
+      } catch {
+        // Closing a failed socket should not hide the sample result.
+      }
+      resolvePromise(sample);
+    }
+  });
+}
+
+function markFirstAssistantEvent(sample, sentAt) {
+  if (sample.first_assistant_event_ms !== null || sentAt <= 0) return;
+  const now = Date.now();
+  sample.first_assistant_event_at = new Date(now).toISOString();
+  sample.first_assistant_event_epoch_ms = now;
+  sample.first_assistant_event_ms = rounded(performance.now() - sentAt);
+}
+
+function markFirstAssistantContent(sample, sentAt) {
+  if (sample.first_assistant_content_ms !== null || sentAt <= 0) return;
+  const now = Date.now();
+  sample.first_assistant_content_at = new Date(now).toISOString();
+  sample.first_assistant_content_epoch_ms = now;
+  sample.first_assistant_content_ms = rounded(performance.now() - sentAt);
+}
+
+function containsPipelineToken(text, prefix) {
+  const escaped = String(prefix).replace(/[.*+?^${}()|[\]\\]/g, "\\$&");
+  return new RegExp(`${escaped}-\\d{4}`).test(String(text || ""));
+}
+
+function matchesFailureSignal(text, signals) {
+  const lower = String(text || "").toLowerCase();
+  return signals.some((signal) => lower.includes(signal.toLowerCase()));
+}
+
+function openRawWebSocket(wsUrl, handlers) {
+  const parsed = new URL(wsUrl);
+  const secure = parsed.protocol === "wss:";
+  const port = Number(parsed.port || (secure ? 443 : 80));
+  const host = parsed.hostname;
+  const path = `${parsed.pathname}${parsed.search}`;
+  const key = crypto.randomBytes(16).toString("base64");
+  const socket = secure
+    ? tls.connect({ host, port, servername: host })
+    : net.connect({ host, port });
+  let opened = false;
+  let closed = false;
+  let buffer = Buffer.alloc(0);
+
+  socket.setNoDelay(true);
+  socket.on("connect", () => {
+    const originProtocol = secure ? "https" : "http";
+    const request = [
+      `GET ${path} HTTP/1.1`,
+      `Host: ${parsed.host}`,
+      "Upgrade: websocket",
+      "Connection: Upgrade",
+      `Sec-WebSocket-Key: ${key}`,
+      "Sec-WebSocket-Version: 13",
+      `Origin: ${originProtocol}://${parsed.host}`,
+      "",
+      "",
+    ].join("\r\n");
+    socket.write(request);
+  });
+  socket.on("data", (chunk) => {
+    buffer = Buffer.concat([buffer, chunk]);
+    if (!opened) {
+      const headerEnd = buffer.indexOf("\r\n\r\n");
+      if (headerEnd === -1) return;
+      const headerText = buffer.slice(0, headerEnd).toString("utf8");
+      buffer = buffer.slice(headerEnd + 4);
+      if (!/^HTTP\/1\.1 101\b/i.test(headerText)) {
+        handlers.onError(new Error(`Handshake failed: ${headerText.split("\r\n")[0] || "missing status"}`));
+        socket.destroy();
+        return;
+      }
+      opened = true;
+      handlers.onOpen();
+    }
+    processFrames();
+  });
+  socket.on("error", (error) => {
+    if (!closed) handlers.onError(error);
+  });
+  socket.on("close", () => {
+    if (closed) return;
+    closed = true;
+    handlers.onClose({ code: null, reason: "" });
+  });
+
+  function processFrames() {
+    while (true) {
+      const frame = readFrame(buffer);
+      if (!frame) return;
+      buffer = buffer.slice(frame.consumed);
+      if (frame.opcode === 0x1) {
+        handlers.onMessage(frame.payload.toString("utf8"));
+      } else if (frame.opcode === 0x8) {
+        const code = frame.payload.length >= 2 ? frame.payload.readUInt16BE(0) : null;
+        const reason = frame.payload.length > 2 ? frame.payload.slice(2).toString("utf8") : "";
+        closed = true;
+        handlers.onClose({ code, reason });
+        socket.end();
+        return;
+      } else if (frame.opcode === 0x9) {
+        writeFrame(socket, 0xA, frame.payload);
+      }
+    }
+  }
+
+  return {
+    send(text) {
+      if (closed || !opened) return;
+      writeFrame(socket, 0x1, Buffer.from(text, "utf8"));
+    },
+    close() {
+      if (closed) return;
+      closed = true;
+      if (!socket.destroyed) {
+        if (opened) writeFrame(socket, 0x8, Buffer.alloc(0));
+        setTimeout(() => socket.end(), 50).unref();
+      }
+    },
+  };
+}
+
+function readFrame(buffer) {
+  if (buffer.length < 2) return null;
+  const first = buffer[0];
+  const second = buffer[1];
+  const opcode = first & 0x0f;
+  const masked = Boolean(second & 0x80);
+  let length = second & 0x7f;
+  let offset = 2;
+  if (length === 126) {
+    if (buffer.length < offset + 2) return null;
+    length = buffer.readUInt16BE(offset);
+    offset += 2;
+  } else if (length === 127) {
+    if (buffer.length < offset + 8) return null;
+    const high = buffer.readUInt32BE(offset);
+    const low = buffer.readUInt32BE(offset + 4);
+    length = high * 2 ** 32 + low;
+    offset += 8;
+  }
+  let mask = null;
+  if (masked) {
+    if (buffer.length < offset + 4) return null;
+    mask = buffer.slice(offset, offset + 4);
+    offset += 4;
+  }
+  if (buffer.length < offset + length) return null;
+  let payload = buffer.slice(offset, offset + length);
+  if (mask) {
+    payload = Buffer.from(payload);
+    for (let index = 0; index < payload.length; index += 1) {
+      payload[index] ^= mask[index % 4];
+    }
+  }
+  return {
+    opcode,
+    payload,
+    consumed: offset + length,
+  };
+}
+
+function writeFrame(socket, opcode, payload) {
+  const body = Buffer.isBuffer(payload) ? payload : Buffer.from(payload || "");
+  const mask = crypto.randomBytes(4);
+  const headerLength = body.length < 126 ? 2 : body.length <= 0xffff ? 4 : 10;
+  const header = Buffer.alloc(headerLength);
+  header[0] = 0x80 | opcode;
+  if (body.length < 126) {
+    header[1] = 0x80 | body.length;
+  } else if (body.length <= 0xffff) {
+    header[1] = 0x80 | 126;
+    header.writeUInt16BE(body.length, 2);
+  } else {
+    header[1] = 0x80 | 127;
+    header.writeUInt32BE(Math.floor(body.length / 2 ** 32), 2);
+    header.writeUInt32BE(body.length >>> 0, 6);
+  }
+  const masked = Buffer.from(body);
+  for (let index = 0; index < masked.length; index += 1) {
+    masked[index] ^= mask[index % 4];
+  }
+  socket.write(Buffer.concat([header, mask, masked]));
+}
+
+function buildMetrics({ samples, requestsPerPipeline, concurrency, timeoutMs, loadDurationMs, backendUrl, sessionType, fakeProviderState }) {
+  const okSamples = samples.filter((sample) => sample.ok);
+  const statusCounts = {};
+  const byPipeline = {};
+  for (const sample of samples) {
+    statusCounts[sample.status] = (statusCounts[sample.status] || 0) + 1;
+    if (!byPipeline[sample.pipeline_label]) {
+      byPipeline[sample.pipeline_label] = {
+        ok_count: 0,
+        error_count: 0,
+        cross_pipeline_leak_count: 0,
+        timeout_count: 0,
+      };
+    }
+    if (sample.ok) byPipeline[sample.pipeline_label].ok_count += 1;
+    else byPipeline[sample.pipeline_label].error_count += 1;
+    byPipeline[sample.pipeline_label].cross_pipeline_leak_count += sample.cross_pipeline_leak_count || 0;
+    if (sample.status === "timeout") byPipeline[sample.pipeline_label].timeout_count += 1;
+  }
+  const errorCount = samples.length - okSamples.length;
+  return {
+    probe: caseId,
+    backend_url: backendUrl,
+    session_type: sessionType,
+    requests_per_pipeline: requestsPerPipeline,
+    total_requests: requestsPerPipeline * 2,
+    completed_requests: samples.length,
+    concurrency,
+    timeout_ms: timeoutMs,
+    ok_count: okSamples.length,
+    error_count: errorCount,
+    timeout_count: samples.filter((sample) => sample.status === "timeout").length,
+    cross_pipeline_leak_count: samples.reduce((count, sample) => count + (sample.cross_pipeline_leak_count || 0), 0),
+    error_rate: samples.length === 0 ? 1 : rounded(errorCount / samples.length),
+    load_duration_ms: rounded(loadDurationMs),
+    throughput_rps: loadDurationMs <= 0 ? 0 : rounded(okSamples.length / (loadDurationMs / 1000)),
+    status_counts: statusCounts,
+    by_pipeline: byPipeline,
+    connected_ms: stats(samples.map((sample) => sample.connected_ms).filter(Number.isFinite)),
+    first_assistant_event_ms: stats(samples.map((sample) => sample.first_assistant_event_ms).filter(Number.isFinite)),
+    first_assistant_content_ms: stats(samples.map((sample) => sample.first_assistant_content_ms).filter(Number.isFinite)),
+    first_response_ms: stats(okSamples.map((sample) => sample.first_response_ms).filter(Number.isFinite)),
+    response_duration_ms: stats(okSamples.map((sample) => sample.response_duration_ms).filter(Number.isFinite)),
+    fake_provider: summarizeFakeProviderState(fakeProviderState),
+    provider_timing: buildProviderTimingMetrics(samples, fakeProviderState),
+    samples,
+  };
+}
+
+function buildThresholds(metrics) {
+  return {
+    cross_pipeline_leak_count: {
+      actual: metrics.cross_pipeline_leak_count,
+      max: 0,
+      pass: metrics.cross_pipeline_leak_count === 0,
+    },
+    error_rate: {
+      actual: metrics.error_rate,
+      max: maxErrorRate,
+      pass: metrics.error_rate <= maxErrorRate,
+    },
+    response_p95_ms: {
+      actual: metrics.response_duration_ms.p95,
+      max: responseP95BudgetMs,
+      pass: metrics.ok_count > 0 && metrics.response_duration_ms.p95 <= responseP95BudgetMs,
+    },
+  };
+}
+
+function positiveInteger(value, fallback) {
+  const parsed = Number.parseInt(String(value || ""), 10);
+  return Number.isInteger(parsed) && parsed > 0 ? parsed : fallback;
+}
+
+function positiveNumber(value, fallback) {
+  const parsed = Number(value || "");
+  return Number.isFinite(parsed) && parsed >= 0 ? parsed : fallback;
+}
+
+function bool(value, fallback) {
+  if (value === undefined || value === "") return fallback;
+  if (/^(1|true|yes|on)$/i.test(String(value))) return true;
+  if (/^(0|false|no|off)$/i.test(String(value))) return false;
+  return fallback;
+}
+
+function textList(value) {
+  return String(value || "")
+    .split(/\r?\n|,/)
+    .map((item) => item.trim())
+    .filter(Boolean);
+}
+
+function rounded(value) {
+  return Number(value.toFixed(3));
+}
+
+function percentile(values, percentileValue) {
+  if (values.length === 0) return 0;
+  const sorted = [...values].sort((a, b) => a - b);
+  const index = Math.min(sorted.length - 1, Math.ceil((percentileValue / 100) * sorted.length) - 1);
+  return rounded(sorted[index]);
+}
+
+function stats(values) {
+  if (values.length === 0) return { min: 0, p50: 0, p95: 0, p99: 0, max: 0 };
+  return {
+    min: rounded(Math.min(...values)),
+    p50: percentile(values, 50),
+    p95: percentile(values, 95),
+    p99: percentile(values, 99),
+    max: rounded(Math.max(...values)),
+  };
+}
+
+function looksLikeEnvIssue(error) {
+  const message = String(error?.message || error || "");
+  return /fetch failed|ECONNREFUSED|ENOTFOUND|LANGBOT_.*not configured|Could not read recovery_key|Backend did not respond/i.test(message);
+}
+
+function safeReason(value) {
+  return redact(String(value || "")).slice(0, 1000);
+}

skills/skills/langbot-testing/probes/langbot-fault-taxonomy-contract.mjs

@@ -0,0 +1,159 @@
+#!/usr/bin/env node
+
+import { mkdir, writeFile } from "node:fs/promises";
+import { join, resolve } from "node:path";
+import { env, exit } from "node:process";
+
+function pad(value, size = 2) {
+  return String(value).padStart(size, "0");
+}
+
+function localIsoWithOffset(date = new Date()) {
+  const offsetMinutes = -date.getTimezoneOffset();
+  const sign = offsetMinutes >= 0 ? "+" : "-";
+  const absolute = Math.abs(offsetMinutes);
+  return [
+    `${date.getFullYear()}-${pad(date.getMonth() + 1)}-${pad(date.getDate())}`,
+    `T${pad(date.getHours())}:${pad(date.getMinutes())}:${pad(date.getSeconds())}.${pad(date.getMilliseconds(), 3)}`,
+    `${sign}${pad(Math.floor(absolute / 60))}:${pad(absolute % 60)}`,
+  ].join("");
+}
+
+function timestampSlug(date = new Date()) {
+  return date.toISOString().replace(/\.\d{3}Z$/, "Z").replace(/[^0-9A-Za-z]+/g, "-").replace(/^-|-$/g, "");
+}
+
+const scenarios = [
+  {
+    id: "provider-timeout",
+    target: "provider",
+    injected_fault: "fake provider request exceeds the configured timeout",
+    expected_status: "env_issue",
+    recovery_check: "provider route is reachable or the case remains outside product pass/fail",
+    cleanup: "stop fake provider or reset proxy route",
+  },
+  {
+    id: "plugin-runtime-disconnect",
+    target: "plugin-runtime",
+    injected_fault: "runtime control channel disconnects during an action",
+    expected_status: "fail",
+    recovery_check: "runtime reconnects and a deterministic plugin action succeeds",
+    cleanup: "restart the local plugin runtime process",
+  },
+  {
+    id: "mcp-stdio-server-exit",
+    target: "mcp",
+    injected_fault: "stdio server exits mid-call",
+    expected_status: "fail",
+    recovery_check: "server can be registered again and exposes the expected tool",
+    cleanup: "remove temporary MCP server registration",
+  },
+  {
+    id: "operator-missing-login",
+    target: "webui",
+    injected_fault: "browser profile is not authenticated",
+    expected_status: "blocked",
+    recovery_check: "authenticated profile can open the same WebUI origin",
+    cleanup: "no product cleanup; refresh local login state",
+  },
+  {
+    id: "transient-marketplace-timeout",
+    target: "marketplace",
+    injected_fault: "marketplace request times out once and then succeeds",
+    expected_status: "flaky",
+    recovery_check: "rerun passes with the same product revision and no code change",
+    cleanup: "clear retry-only evidence and keep the run classified as flaky",
+  },
+];
+
+function validateScenario(scenario) {
+  const missing = ["id", "target", "injected_fault", "expected_status", "recovery_check", "cleanup"]
+    .filter((key) => !scenario[key]);
+  const allowedStatuses = new Set(["pass", "fail", "blocked", "env_issue", "flaky"]);
+  return {
+    id: scenario.id,
+    pass: missing.length === 0 && allowedStatuses.has(scenario.expected_status),
+    missing,
+    expected_status: scenario.expected_status,
+  };
+}
+
+async function main() {
+  const root = resolve(env.LBS_ROOT || process.cwd());
+  const caseId = "langbot-fault-taxonomy-contract";
+  const runId = env.LBS_RUN_ID || `${timestampSlug()}-${caseId}`;
+  const evidenceDir = resolve(env.LBS_EVIDENCE_DIR || join(root, "reports", "evidence", runId));
+  await mkdir(evidenceDir, { recursive: true });
+
+  const startedAt = new Date();
+  const validations = scenarios.map(validateScenario);
+  const statusCounts = {};
+  for (const scenario of scenarios) {
+    statusCounts[scenario.expected_status] = (statusCounts[scenario.expected_status] || 0) + 1;
+  }
+  const metrics = {
+    probe: caseId,
+    scenario_count: scenarios.length,
+    status_counts: statusCounts,
+    scenarios,
+    validations,
+  };
+  const thresholds = {
+    scenario_count: { actual: scenarios.length, min: 5, pass: scenarios.length >= 5 },
+    invalid_scenario_count: {
+      actual: validations.filter((item) => !item.pass).length,
+      max: 0,
+      pass: validations.every((item) => item.pass),
+    },
+    cleanup_declared_count: {
+      actual: scenarios.filter((item) => item.cleanup).length,
+      min: scenarios.length,
+      pass: scenarios.every((item) => item.cleanup),
+    },
+  };
+  const status = Object.values(thresholds).every((item) => item.pass) ? "pass" : "fail";
+  const metricsPath = join(evidenceDir, "metrics.json");
+  const faultModelPath = join(evidenceDir, "fault-model.json");
+  const automationResultPath = join(evidenceDir, "automation-result.json");
+  const resultPath = join(evidenceDir, "result.json");
+
+  await writeFile(metricsPath, `${JSON.stringify(metrics, null, 2)}\n`, "utf8");
+  await writeFile(faultModelPath, `${JSON.stringify({ scenarios }, null, 2)}\n`, "utf8");
+
+  const finishedAt = new Date();
+  const result = {
+    source: "automation",
+    case_id: caseId,
+    run_id: runId,
+    status,
+    reason: status === "pass"
+      ? "Fault taxonomy contract declares status, recovery, and cleanup for every scenario."
+      : "Fault taxonomy contract is missing required scenario fields.",
+    started_at: startedAt.toISOString(),
+    started_at_local: localIsoWithOffset(startedAt),
+    finished_at: finishedAt.toISOString(),
+    finished_at_local: localIsoWithOffset(finishedAt),
+    duration_ms: finishedAt.getTime() - startedAt.getTime(),
+    metrics_summary: {
+      scenario_count: metrics.scenario_count,
+      status_counts: metrics.status_counts,
+      invalid_scenario_count: thresholds.invalid_scenario_count.actual,
+    },
+    thresholds_summary: thresholds,
+    artifacts: {
+      metrics_json: metricsPath,
+      fault_model_json: faultModelPath,
+      automation_result_json: automationResultPath,
+      result_json: resultPath,
+    },
+    evidence_collected: ["metrics", "filesystem"],
+  };
+
+  const resultText = `${JSON.stringify(result, null, 2)}\n`;
+  await writeFile(automationResultPath, resultText, "utf8");
+  await writeFile(resultPath, resultText, "utf8");
+  console.log(JSON.stringify(result, null, 2));
+  exit(status === "pass" ? 0 : 1);
+}
+
+await main();

skills/skills/langbot-testing/probes/langbot-live-backend-latency.mjs

@@ -0,0 +1,212 @@
+#!/usr/bin/env node
+
+import { mkdir, writeFile } from "node:fs/promises";
+import { join, resolve } from "node:path";
+import { env, exit } from "node:process";
+
+function pad(value, size = 2) {
+  return String(value).padStart(size, "0");
+}
+
+function localIsoWithOffset(date = new Date()) {
+  const offsetMinutes = -date.getTimezoneOffset();
+  const sign = offsetMinutes >= 0 ? "+" : "-";
+  const absolute = Math.abs(offsetMinutes);
+  return [
+    `${date.getFullYear()}-${pad(date.getMonth() + 1)}-${pad(date.getDate())}`,
+    `T${pad(date.getHours())}:${pad(date.getMinutes())}:${pad(date.getSeconds())}.${pad(date.getMilliseconds(), 3)}`,
+    `${sign}${pad(Math.floor(absolute / 60))}:${pad(absolute % 60)}`,
+  ].join("");
+}
+
+function timestampSlug(date = new Date()) {
+  return date.toISOString().replace(/\.\d{3}Z$/, "Z").replace(/[^0-9A-Za-z]+/g, "-").replace(/^-|-$/g, "");
+}
+
+function percentile(values, percentileValue) {
+  if (values.length === 0) return 0;
+  const sorted = [...values].sort((a, b) => a - b);
+  const index = Math.min(sorted.length - 1, Math.ceil((percentileValue / 100) * sorted.length) - 1);
+  return Number(sorted[index].toFixed(3));
+}
+
+function stats(values) {
+  if (values.length === 0) return { min: 0, p50: 0, p95: 0, p99: 0, max: 0 };
+  return {
+    min: Number(Math.min(...values).toFixed(3)),
+    p50: percentile(values, 50),
+    p95: percentile(values, 95),
+    p99: percentile(values, 99),
+    max: Number(Math.max(...values).toFixed(3)),
+  };
+}
+
+function parseJsonList(value, fallback) {
+  if (!value) return fallback;
+  try {
+    const parsed = JSON.parse(value);
+    return Array.isArray(parsed) && parsed.every((item) => typeof item === "string") ? parsed : fallback;
+  } catch {
+    return fallback;
+  }
+}
+
+function joinUrl(baseUrl, path) {
+  const base = baseUrl.replace(/\/+$/, "");
+  const suffix = path.startsWith("/") ? path : `/${path}`;
+  return `${base}${suffix}`;
+}
+
+async function fetchOnce(url, timeoutMs) {
+  const controller = new AbortController();
+  const timeout = setTimeout(() => controller.abort(), timeoutMs);
+  const started = performance.now();
+  try {
+    const response = await fetch(url, { method: "GET", signal: controller.signal });
+    await response.arrayBuffer();
+    const latencyMs = performance.now() - started;
+    return {
+      url,
+      ok: response.status < 500,
+      status: response.status,
+      latency_ms: Number(latencyMs.toFixed(3)),
+      error: "",
+    };
+  } catch (error) {
+    const latencyMs = performance.now() - started;
+    return {
+      url,
+      ok: false,
+      status: 0,
+      latency_ms: Number(latencyMs.toFixed(3)),
+      error: error instanceof Error ? error.message : String(error),
+    };
+  } finally {
+    clearTimeout(timeout);
+  }
+}
+
+async function runBatches(urls, totalRequests, concurrency, timeoutMs) {
+  const queue = Array.from({ length: totalRequests }, (_, index) => urls[index % urls.length]);
+  const results = [];
+  while (queue.length > 0) {
+    const batch = queue.splice(0, concurrency);
+    results.push(...await Promise.all(batch.map((url) => fetchOnce(url, timeoutMs))));
+  }
+  return results;
+}
+
+async function main() {
+  const root = resolve(env.LBS_ROOT || process.cwd());
+  const caseId = "langbot-live-backend-latency";
+  const runId = env.LBS_RUN_ID || `${timestampSlug()}-${caseId}`;
+  const evidenceDir = resolve(env.LBS_EVIDENCE_DIR || join(root, "reports", "evidence", runId));
+  await mkdir(evidenceDir, { recursive: true });
+
+  const startedAt = new Date();
+  const backendUrl = env.LANGBOT_BACKEND_URL || "";
+  const endpoints = parseJsonList(env.LANGBOT_PERF_ENDPOINTS_JSON, ["/healthz"]);
+  const totalRequests = Number(env.LANGBOT_PERF_REQUESTS || "12");
+  const concurrency = Number(env.LANGBOT_PERF_CONCURRENCY || "2");
+  const timeoutMs = Number(env.LANGBOT_PERF_TIMEOUT_MS || "5000");
+  const p95BudgetMs = Number(env.LANGBOT_PERF_BACKEND_P95_MS || "1000");
+  const maxErrorRate = Number(env.LANGBOT_PERF_MAX_ERROR_RATE || "0");
+  const metricsPath = join(evidenceDir, "metrics.json");
+  const networkLogPath = join(evidenceDir, "network.log");
+  const automationResultPath = join(evidenceDir, "automation-result.json");
+  const resultPath = join(evidenceDir, "result.json");
+
+  let status = "fail";
+  let reason = "";
+  let results = [];
+  if (!backendUrl) {
+    status = "env_issue";
+    reason = "LANGBOT_BACKEND_URL is not configured.";
+  } else {
+    const urls = endpoints.map((path) => joinUrl(backendUrl, path));
+    results = await runBatches(urls, totalRequests, concurrency, timeoutMs);
+    const okCount = results.filter((item) => item.ok).length;
+    const errorCount = results.length - okCount;
+    const errorRate = results.length === 0 ? 1 : errorCount / results.length;
+    const latencies = results.filter((item) => item.ok).map((item) => item.latency_ms);
+    const latencyStats = stats(latencies);
+    const allConnectionFailures = results.length > 0 && results.every((item) => item.status === 0);
+    if (allConnectionFailures) {
+      status = "env_issue";
+      reason = `Backend did not respond at ${backendUrl}.`;
+    } else if (latencyStats.p95 <= p95BudgetMs && errorRate <= maxErrorRate) {
+      status = "pass";
+      reason = "Live backend latency probe passed all thresholds.";
+    } else {
+      status = "fail";
+      reason = "Live backend latency probe breached latency or error-rate thresholds.";
+    }
+  }
+
+  const statusCounts = {};
+  for (const item of results) {
+    const key = item.status === 0 ? "network_error" : String(item.status);
+    statusCounts[key] = (statusCounts[key] || 0) + 1;
+  }
+  const okResults = results.filter((item) => item.ok);
+  const metrics = {
+    probe: caseId,
+    backend_url: backendUrl,
+    endpoints,
+    total_requests: totalRequests,
+    concurrency,
+    timeout_ms: timeoutMs,
+    ok_count: okResults.length,
+    error_count: results.length - okResults.length,
+    error_rate: results.length === 0 ? 1 : Number(((results.length - okResults.length) / results.length).toFixed(4)),
+    latency_ms: stats(okResults.map((item) => item.latency_ms)),
+    status_counts: statusCounts,
+  };
+  const thresholds = {
+    backend_p95_ms: { actual: metrics.latency_ms.p95, max: p95BudgetMs, pass: metrics.latency_ms.p95 <= p95BudgetMs },
+    error_rate: { actual: metrics.error_rate, max: maxErrorRate, pass: metrics.error_rate <= maxErrorRate },
+  };
+
+  await writeFile(metricsPath, `${JSON.stringify({ ...metrics, samples: results }, null, 2)}\n`, "utf8");
+  await writeFile(networkLogPath, results.map((item) => JSON.stringify(item)).join("\n") + (results.length > 0 ? "\n" : ""), "utf8");
+
+  const finishedAt = new Date();
+  const result = {
+    source: "automation",
+    case_id: caseId,
+    run_id: runId,
+    status,
+    reason,
+    started_at: startedAt.toISOString(),
+    started_at_local: localIsoWithOffset(startedAt),
+    finished_at: finishedAt.toISOString(),
+    finished_at_local: localIsoWithOffset(finishedAt),
+    duration_ms: finishedAt.getTime() - startedAt.getTime(),
+    url: backendUrl,
+    metrics_summary: {
+      requests: metrics.total_requests,
+      concurrency: metrics.concurrency,
+      ok_count: metrics.ok_count,
+      error_rate: metrics.error_rate,
+      latency_p50_ms: metrics.latency_ms.p50,
+      latency_p95_ms: metrics.latency_ms.p95,
+      status_counts: metrics.status_counts,
+    },
+    thresholds_summary: thresholds,
+    artifacts: {
+      metrics_json: metricsPath,
+      network_log: networkLogPath,
+      automation_result_json: automationResultPath,
+      result_json: resultPath,
+    },
+    evidence_collected: ["metrics", "network", "api_diagnostic", "filesystem"],
+  };
+
+  const resultText = `${JSON.stringify(result, null, 2)}\n`;
+  await writeFile(automationResultPath, resultText, "utf8");
+  await writeFile(resultPath, resultText, "utf8");
+  console.log(JSON.stringify(result, null, 2));
+  exit(status === "pass" ? 0 : status === "env_issue" ? 2 : 1);
+}
+
+await main();

skills/skills/langbot-testing/probes/langbot-live-backend-log-health.mjs

@@ -0,0 +1,205 @@
+#!/usr/bin/env node
+
+import { existsSync, readdirSync, statSync } from "node:fs";
+import { mkdir, readFile, writeFile } from "node:fs/promises";
+import { join, resolve } from "node:path";
+import { env, exit } from "node:process";
+
+function pad(value, size = 2) {
+  return String(value).padStart(size, "0");
+}
+
+function localIsoWithOffset(date = new Date()) {
+  const offsetMinutes = -date.getTimezoneOffset();
+  const sign = offsetMinutes >= 0 ? "+" : "-";
+  const absolute = Math.abs(offsetMinutes);
+  return [
+    `${date.getFullYear()}-${pad(date.getMonth() + 1)}-${pad(date.getDate())}`,
+    `T${pad(date.getHours())}:${pad(date.getMinutes())}:${pad(date.getSeconds())}.${pad(date.getMilliseconds(), 3)}`,
+    `${sign}${pad(Math.floor(absolute / 60))}:${pad(absolute % 60)}`,
+  ].join("");
+}
+
+function timestampSlug(date = new Date()) {
+  return date.toISOString().replace(/\.\d{3}Z$/, "Z").replace(/[^0-9A-Za-z]+/g, "-").replace(/^-|-$/g, "");
+}
+
+function repoRootFromEnv(root) {
+  return env.LANGBOT_REPO ? resolve(env.LANGBOT_REPO) : resolve(root, "..");
+}
+
+function latestBackendLog(root) {
+  const explicit = env.LANGBOT_BACKEND_LOG;
+  if (explicit) return resolve(explicit);
+
+  const logsDir = join(repoRootFromEnv(root), "data", "logs");
+  if (!existsSync(logsDir)) return "";
+  const candidates = readdirSync(logsDir)
+    .filter((name) => /^langbot-.*\.log$/.test(name))
+    .map((name) => join(logsDir, name))
+    .filter((path) => {
+      try {
+        return statSync(path).isFile();
+      } catch {
+        return false;
+      }
+    })
+    .sort((left, right) => statSync(right).mtimeMs - statSync(left).mtimeMs);
+  return candidates[0] || "";
+}
+
+function parseSince(startedAt) {
+  if (env.LANGBOT_BACKEND_LOG_SINCE) return new Date(env.LANGBOT_BACKEND_LOG_SINCE);
+  const lookbackSeconds = Number(env.LANGBOT_BACKEND_LOG_LOOKBACK_SECONDS || "300");
+  return new Date(startedAt.getTime() - lookbackSeconds * 1000);
+}
+
+function parseTimestamp(line, year) {
+  const localMatch = line.match(/^\[(\d{2})-(\d{2}) (\d{2}):(\d{2}):(\d{2})\.(\d{3})\]/);
+  if (localMatch) {
+    const [, month, day, hour, minute, second, millisecond] = localMatch;
+    return new Date(`${year}-${month}-${day}T${hour}:${minute}:${second}.${millisecond}+08:00`);
+  }
+
+  const accessMatch = line.match(/^\[(\d{4})-(\d{2})-(\d{2}) (\d{2}):(\d{2}):(\d{2}) ([+-]\d{4})\]/);
+  if (accessMatch) {
+    const [, fullYear, month, day, hour, minute, second, offset] = accessMatch;
+    const normalizedOffset = `${offset.slice(0, 3)}:${offset.slice(3)}`;
+    return new Date(`${fullYear}-${month}-${day}T${hour}:${minute}:${second}${normalizedOffset}`);
+  }
+
+  return null;
+}
+
+function findingForLine(line, number) {
+  const rules = [
+    { severity: "fail", kind: "python_traceback", pattern: /\bTraceback(?: \(most recent call last\))?/i },
+    { severity: "fail", kind: "unretrieved_task_exception", pattern: /Task exception was never retrieved/i },
+    { severity: "fail", kind: "unawaited_coroutine", pattern: /RuntimeWarning:\s+coroutine .* was never awaited/i },
+    { severity: "fail", kind: "unclosed_client_session", pattern: /Unclosed client session/i },
+    { severity: "fail", kind: "unclosed_connector", pattern: /Unclosed connector/i },
+    { severity: "fail", kind: "import_error", pattern: /\bImportError\b/i },
+    { severity: "fail", kind: "error_log", pattern: /\b(?:ERROR|CRITICAL)\b/ },
+    { severity: "warning", kind: "warning_log", pattern: /\bWARNING\b/ },
+  ];
+
+  for (const rule of rules) {
+    if (rule.pattern.test(line)) {
+      return {
+        severity: rule.severity,
+        kind: rule.kind,
+        line: number,
+        excerpt: line,
+      };
+    }
+  }
+  return null;
+}
+
+function scanLines(text, since, year) {
+  const findings = [];
+  const scanned = [];
+  let includeContinuation = false;
+  const lines = text.split(/\r?\n/);
+  for (const [index, line] of lines.entries()) {
+    const number = index + 1;
+    const timestamp = parseTimestamp(line, year);
+    if (timestamp) includeContinuation = timestamp >= since;
+    if (!includeContinuation) continue;
+    scanned.push({ number, text: line });
+    const finding = findingForLine(line, number);
+    if (finding) findings.push(finding);
+  }
+  return { findings, scanned, total_lines: lines.length };
+}
+
+async function main() {
+  const root = resolve(env.LBS_ROOT || process.cwd());
+  const caseId = "langbot-live-backend-log-health";
+  const runId = env.LBS_RUN_ID || `${timestampSlug()}-${caseId}`;
+  const evidenceDir = resolve(env.LBS_EVIDENCE_DIR || join(root, "reports", "evidence", runId));
+  await mkdir(evidenceDir, { recursive: true });
+
+  const startedAt = new Date();
+  const since = parseSince(startedAt);
+  const logPath = latestBackendLog(root);
+  const metricsPath = join(evidenceDir, "metrics.json");
+  const findingsPath = join(evidenceDir, "findings.json");
+  const scannedLogPath = join(evidenceDir, "scanned-backend.log");
+  const automationResultPath = join(evidenceDir, "automation-result.json");
+  const resultPath = join(evidenceDir, "result.json");
+
+  let status = "fail";
+  let reason = "";
+  let scan = { findings: [], scanned: [], total_lines: 0 };
+  if (!logPath || !existsSync(logPath)) {
+    status = "env_issue";
+    reason = "No LangBot backend log file was found. Set LANGBOT_BACKEND_LOG or LANGBOT_REPO.";
+  } else {
+    const text = await readFile(logPath, "utf8");
+    scan = scanLines(text, since, startedAt.getFullYear());
+    const failCount = scan.findings.filter((item) => item.severity === "fail").length;
+    status = failCount === 0 ? "pass" : "fail";
+    reason = status === "pass"
+      ? "Live backend log health passed; no fail-severity findings in the scanned window."
+      : "Live backend log health found fail-severity backend log findings.";
+  }
+
+  const warningCount = scan.findings.filter((item) => item.severity === "warning").length;
+  const failCount = scan.findings.filter((item) => item.severity === "fail").length;
+  const metrics = {
+    probe: caseId,
+    backend_log: logPath,
+    since: since.toISOString(),
+    scanned_line_count: scan.scanned.length,
+    total_line_count: scan.total_lines,
+    fail_count: failCount,
+    warning_count: warningCount,
+    finding_count: scan.findings.length,
+  };
+  const thresholds = {
+    fail_count: { actual: failCount, max: 0, pass: failCount === 0 },
+  };
+
+  await writeFile(metricsPath, `${JSON.stringify(metrics, null, 2)}\n`, "utf8");
+  await writeFile(findingsPath, `${JSON.stringify(scan.findings, null, 2)}\n`, "utf8");
+  await writeFile(scannedLogPath, scan.scanned.map((item) => `${item.number}: ${item.text}`).join("\n") + (scan.scanned.length > 0 ? "\n" : ""), "utf8");
+
+  const finishedAt = new Date();
+  const result = {
+    source: "automation",
+    case_id: caseId,
+    run_id: runId,
+    status,
+    reason,
+    started_at: startedAt.toISOString(),
+    started_at_local: localIsoWithOffset(startedAt),
+    finished_at: finishedAt.toISOString(),
+    finished_at_local: localIsoWithOffset(finishedAt),
+    duration_ms: finishedAt.getTime() - startedAt.getTime(),
+    url: logPath,
+    metrics_summary: {
+      scanned_line_count: metrics.scanned_line_count,
+      fail_count: metrics.fail_count,
+      warning_count: metrics.warning_count,
+      finding_count: metrics.finding_count,
+    },
+    thresholds_summary: thresholds,
+    artifacts: {
+      metrics_json: metricsPath,
+      findings_json: findingsPath,
+      scanned_backend_log: scannedLogPath,
+      automation_result_json: automationResultPath,
+      result_json: resultPath,
+    },
+    evidence_collected: ["metrics", "backend_log", "filesystem"],
+  };
+
+  const resultText = `${JSON.stringify(result, null, 2)}\n`;
+  await writeFile(automationResultPath, resultText, "utf8");
+  await writeFile(resultPath, resultText, "utf8");
+  console.log(JSON.stringify(result, null, 2));
+  exit(status === "pass" ? 0 : status === "env_issue" ? 2 : 1);
+}
+
+await main();

skills/skills/langbot-testing/probes/langbot-live-control-plane-api.mjs

@@ -0,0 +1,311 @@
+#!/usr/bin/env node
+
+import { mkdir, writeFile } from "node:fs/promises";
+import { join, resolve } from "node:path";
+import { env, exit } from "node:process";
+
+function pad(value, size = 2) {
+  return String(value).padStart(size, "0");
+}
+
+function localIsoWithOffset(date = new Date()) {
+  const offsetMinutes = -date.getTimezoneOffset();
+  const sign = offsetMinutes >= 0 ? "+" : "-";
+  const absolute = Math.abs(offsetMinutes);
+  return [
+    `${date.getFullYear()}-${pad(date.getMonth() + 1)}-${pad(date.getDate())}`,
+    `T${pad(date.getHours())}:${pad(date.getMinutes())}:${pad(date.getSeconds())}.${pad(date.getMilliseconds(), 3)}`,
+    `${sign}${pad(Math.floor(absolute / 60))}:${pad(absolute % 60)}`,
+  ].join("");
+}
+
+function timestampSlug(date = new Date()) {
+  return date.toISOString().replace(/\.\d{3}Z$/, "Z").replace(/[^0-9A-Za-z]+/g, "-").replace(/^-|-$/g, "");
+}
+
+function percentile(values, percentileValue) {
+  if (values.length === 0) return 0;
+  const sorted = [...values].sort((a, b) => a - b);
+  const index = Math.min(sorted.length - 1, Math.ceil((percentileValue / 100) * sorted.length) - 1);
+  return Number(sorted[index].toFixed(3));
+}
+
+function stats(values) {
+  if (values.length === 0) return { min: 0, p50: 0, p95: 0, p99: 0, max: 0 };
+  return {
+    min: Number(Math.min(...values).toFixed(3)),
+    p50: percentile(values, 50),
+    p95: percentile(values, 95),
+    p99: percentile(values, 99),
+    max: Number(Math.max(...values).toFixed(3)),
+  };
+}
+
+function joinUrl(baseUrl, path) {
+  const base = baseUrl.replace(/\/+$/, "");
+  const suffix = path.startsWith("/") ? path : `/${path}`;
+  return `${base}${suffix}`;
+}
+
+function parseJsonObject(value, fallback) {
+  if (!value) return fallback;
+  try {
+    const parsed = JSON.parse(value);
+    return parsed && typeof parsed === "object" && !Array.isArray(parsed) ? parsed : fallback;
+  } catch {
+    return fallback;
+  }
+}
+
+function controlPlaneEndpoints() {
+  return [
+    {
+      id: "healthz",
+      path: "/healthz",
+      expected_status: 200,
+      expected_code: 0,
+      p95_budget_ms: Number(env.LANGBOT_PERF_HEALTHZ_P95_MS || "500"),
+      required_data_fields: [],
+    },
+    {
+      id: "system_info",
+      path: "/api/v1/system/info",
+      expected_status: 200,
+      expected_code: 0,
+      p95_budget_ms: Number(env.LANGBOT_PERF_SYSTEM_INFO_P95_MS || "1000"),
+      required_data_fields: ["version", "edition", "enable_marketplace"],
+    },
+  ];
+}
+
+async function fetchEndpoint(backendUrl, endpoint, timeoutMs) {
+  const url = joinUrl(backendUrl, endpoint.path);
+  const controller = new AbortController();
+  const timeout = setTimeout(() => controller.abort(), timeoutMs);
+  const started = performance.now();
+  let bodyText = "";
+  let json = null;
+  let jsonValid = false;
+  let error = "";
+
+  try {
+    const response = await fetch(url, {
+      method: "GET",
+      headers: { "accept": "application/json" },
+      signal: controller.signal,
+    });
+    bodyText = await response.text();
+    try {
+      json = bodyText ? JSON.parse(bodyText) : null;
+      jsonValid = json !== null;
+    } catch (parseError) {
+      error = parseError instanceof Error ? parseError.message : String(parseError);
+    }
+
+    const data = json && typeof json === "object" && json.data && typeof json.data === "object" ? json.data : {};
+    const missingFields = endpoint.required_data_fields.filter((field) => !(field in data));
+    const statusOk = response.status === endpoint.expected_status;
+    const codeOk = !json || typeof json !== "object" ? false : json.code === endpoint.expected_code;
+    const shapeOk = jsonValid && missingFields.length === 0;
+    const latencyMs = performance.now() - started;
+    return {
+      endpoint_id: endpoint.id,
+      path: endpoint.path,
+      url,
+      status: response.status,
+      ok: statusOk && codeOk && shapeOk,
+      status_ok: statusOk,
+      code_ok: codeOk,
+      json_valid: jsonValid,
+      missing_fields: missingFields,
+      response_code: json && typeof json === "object" ? json.code : null,
+      latency_ms: Number(latencyMs.toFixed(3)),
+      error,
+    };
+  } catch (fetchError) {
+    const latencyMs = performance.now() - started;
+    return {
+      endpoint_id: endpoint.id,
+      path: endpoint.path,
+      url,
+      status: 0,
+      ok: false,
+      status_ok: false,
+      code_ok: false,
+      json_valid: false,
+      missing_fields: endpoint.required_data_fields,
+      response_code: null,
+      latency_ms: Number(latencyMs.toFixed(3)),
+      error: fetchError instanceof Error ? fetchError.message : String(fetchError),
+    };
+  } finally {
+    clearTimeout(timeout);
+  }
+}
+
+async function runBatches(backendUrl, endpoints, totalRequests, concurrency, timeoutMs) {
+  const queue = Array.from({ length: totalRequests }, (_, index) => endpoints[index % endpoints.length]);
+  const results = [];
+  while (queue.length > 0) {
+    const batch = queue.splice(0, concurrency);
+    results.push(...await Promise.all(batch.map((endpoint) => fetchEndpoint(backendUrl, endpoint, timeoutMs))));
+  }
+  return results;
+}
+
+function endpointMetrics(endpoints, results) {
+  return Object.fromEntries(endpoints.map((endpoint) => {
+    const samples = results.filter((item) => item.endpoint_id === endpoint.id);
+    const okSamples = samples.filter((item) => item.ok);
+    return [
+      endpoint.id,
+      {
+        path: endpoint.path,
+        requests: samples.length,
+        ok_count: okSamples.length,
+        error_rate: samples.length === 0 ? 1 : Number(((samples.length - okSamples.length) / samples.length).toFixed(4)),
+        latency_ms: stats(okSamples.map((item) => item.latency_ms)),
+        p95_budget_ms: endpoint.p95_budget_ms,
+      },
+    ];
+  }));
+}
+
+async function main() {
+  const root = resolve(env.LBS_ROOT || process.cwd());
+  const caseId = "langbot-live-control-plane-api";
+  const runId = env.LBS_RUN_ID || `${timestampSlug()}-${caseId}`;
+  const evidenceDir = resolve(env.LBS_EVIDENCE_DIR || join(root, "reports", "evidence", runId));
+  await mkdir(evidenceDir, { recursive: true });
+
+  const startedAt = new Date();
+  const backendUrl = env.LANGBOT_BACKEND_URL || "";
+  const endpoints = controlPlaneEndpoints();
+  const configuredBudgets = parseJsonObject(env.LANGBOT_CONTROL_PLANE_P95_BUDGETS_JSON, {});
+  for (const endpoint of endpoints) {
+    const budget = configuredBudgets[endpoint.id];
+    if (typeof budget === "number" && Number.isFinite(budget)) endpoint.p95_budget_ms = budget;
+  }
+  const totalRequests = Number(env.LANGBOT_CONTROL_PLANE_REQUESTS || "20");
+  const concurrency = Number(env.LANGBOT_CONTROL_PLANE_CONCURRENCY || "4");
+  const timeoutMs = Number(env.LANGBOT_CONTROL_PLANE_TIMEOUT_MS || "5000");
+  const maxErrorRate = Number(env.LANGBOT_CONTROL_PLANE_MAX_ERROR_RATE || "0");
+  const metricsPath = join(evidenceDir, "metrics.json");
+  const endpointsPath = join(evidenceDir, "endpoints.json");
+  const networkLogPath = join(evidenceDir, "network.log");
+  const automationResultPath = join(evidenceDir, "automation-result.json");
+  const resultPath = join(evidenceDir, "result.json");
+
+  let status = "fail";
+  let reason = "";
+  let results = [];
+  if (!backendUrl) {
+    status = "env_issue";
+    reason = "LANGBOT_BACKEND_URL is not configured.";
+  } else {
+    results = await runBatches(backendUrl, endpoints, totalRequests, concurrency, timeoutMs);
+    const allConnectionFailures = results.length > 0 && results.every((item) => item.status === 0);
+    if (allConnectionFailures) {
+      status = "env_issue";
+      reason = `Backend did not respond at ${backendUrl}.`;
+    }
+  }
+
+  const okResults = results.filter((item) => item.ok);
+  const statusCounts = {};
+  for (const item of results) {
+    const key = item.status === 0 ? "network_error" : String(item.status);
+    statusCounts[key] = (statusCounts[key] || 0) + 1;
+  }
+  const perEndpoint = endpointMetrics(endpoints, results);
+  const responseShapeFailures = results.filter((item) => !item.json_valid || item.missing_fields.length > 0 || !item.code_ok).length;
+  const errorRate = results.length === 0 ? 1 : Number(((results.length - okResults.length) / results.length).toFixed(4));
+  const thresholds = {
+    error_rate: { actual: errorRate, max: maxErrorRate, pass: errorRate <= maxErrorRate },
+    response_shape_failures: { actual: responseShapeFailures, max: 0, pass: responseShapeFailures === 0 },
+  };
+  for (const endpoint of endpoints) {
+    const actual = perEndpoint[endpoint.id].latency_ms.p95;
+    thresholds[`${endpoint.id}_p95_ms`] = {
+      actual,
+      max: endpoint.p95_budget_ms,
+      pass: actual <= endpoint.p95_budget_ms,
+    };
+  }
+
+  if (status !== "env_issue") {
+    const passed = Object.values(thresholds).every((item) => item.pass);
+    status = passed ? "pass" : "fail";
+    reason = passed
+      ? "Live control-plane API probe passed all thresholds."
+      : "Live control-plane API probe breached shape, latency, or error-rate thresholds.";
+  }
+
+  const metrics = {
+    probe: caseId,
+    backend_url: backendUrl,
+    total_requests: totalRequests,
+    concurrency,
+    timeout_ms: timeoutMs,
+    ok_count: okResults.length,
+    error_count: results.length - okResults.length,
+    error_rate: errorRate,
+    status_counts: statusCounts,
+    response_shape_failures: responseShapeFailures,
+    endpoints: perEndpoint,
+  };
+
+  await writeFile(metricsPath, `${JSON.stringify({ ...metrics, samples: results }, null, 2)}\n`, "utf8");
+  await writeFile(endpointsPath, `${JSON.stringify(endpoints, null, 2)}\n`, "utf8");
+  await writeFile(networkLogPath, results.map((item) => JSON.stringify(item)).join("\n") + (results.length > 0 ? "\n" : ""), "utf8");
+
+  const finishedAt = new Date();
+  const result = {
+    source: "automation",
+    case_id: caseId,
+    run_id: runId,
+    status,
+    reason,
+    started_at: startedAt.toISOString(),
+    started_at_local: localIsoWithOffset(startedAt),
+    finished_at: finishedAt.toISOString(),
+    finished_at_local: localIsoWithOffset(finishedAt),
+    duration_ms: finishedAt.getTime() - startedAt.getTime(),
+    url: backendUrl,
+    metrics_summary: {
+      requests: metrics.total_requests,
+      concurrency: metrics.concurrency,
+      ok_count: metrics.ok_count,
+      error_rate: metrics.error_rate,
+      response_shape_failures: metrics.response_shape_failures,
+      endpoints: Object.fromEntries(Object.entries(metrics.endpoints).map(([id, value]) => [
+        id,
+        {
+          path: value.path,
+          ok_count: value.ok_count,
+          error_rate: value.error_rate,
+          latency_p50_ms: value.latency_ms.p50,
+          latency_p95_ms: value.latency_ms.p95,
+        },
+      ])),
+      status_counts: metrics.status_counts,
+    },
+    thresholds_summary: thresholds,
+    artifacts: {
+      metrics_json: metricsPath,
+      endpoints_json: endpointsPath,
+      network_log: networkLogPath,
+      automation_result_json: automationResultPath,
+      result_json: resultPath,
+    },
+    evidence_collected: ["metrics", "network", "api_diagnostic", "filesystem"],
+  };
+
+  const resultText = `${JSON.stringify(result, null, 2)}\n`;
+  await writeFile(automationResultPath, resultText, "utf8");
+  await writeFile(resultPath, resultText, "utf8");
+  console.log(JSON.stringify(result, null, 2));
+  exit(status === "pass" ? 0 : status === "env_issue" ? 2 : 1);
+}
+
+await main();

skills/skills/langbot-testing/probes/langbot-overhead-accounting-contract.mjs

@@ -0,0 +1,162 @@
+#!/usr/bin/env node
+
+import { mkdir, writeFile } from "node:fs/promises";
+import { join, resolve } from "node:path";
+import { env, exit } from "node:process";
+
+function pad(value, size = 2) {
+  return String(value).padStart(size, "0");
+}
+
+function localIsoWithOffset(date = new Date()) {
+  const offsetMinutes = -date.getTimezoneOffset();
+  const sign = offsetMinutes >= 0 ? "+" : "-";
+  const absolute = Math.abs(offsetMinutes);
+  return [
+    `${date.getFullYear()}-${pad(date.getMonth() + 1)}-${pad(date.getDate())}`,
+    `T${pad(date.getHours())}:${pad(date.getMinutes())}:${pad(date.getSeconds())}.${pad(date.getMilliseconds(), 3)}`,
+    `${sign}${pad(Math.floor(absolute / 60))}:${pad(absolute % 60)}`,
+  ].join("");
+}
+
+function timestampSlug(date = new Date()) {
+  return date.toISOString().replace(/\.\d{3}Z$/, "Z").replace(/[^0-9A-Za-z]+/g, "-").replace(/^-|-$/g, "");
+}
+
+function percentile(values, percentileValue) {
+  if (values.length === 0) return 0;
+  const sorted = [...values].sort((a, b) => a - b);
+  const index = Math.min(sorted.length - 1, Math.ceil((percentileValue / 100) * sorted.length) - 1);
+  return Number(sorted[index].toFixed(3));
+}
+
+function stats(values) {
+  return {
+    min: Number(Math.min(...values).toFixed(3)),
+    p50: percentile(values, 50),
+    p95: percentile(values, 95),
+    p99: percentile(values, 99),
+    max: Number(Math.max(...values).toFixed(3)),
+  };
+}
+
+function threshold(actual, limit, operator) {
+  const pass = operator === "<=" ? actual <= limit : actual >= limit;
+  return { actual, [operator === "<=" ? "max" : "min"]: limit, pass };
+}
+
+function makeSample(index) {
+  const ingress = 1 + (index % 5) * 0.22;
+  const pipeline = 2.8 + (index % 7) * 0.31;
+  const persistence = 1.1 + (index % 4) * 0.2;
+  const pluginIpc = 1.9 + (index % 6) * 0.27;
+  const rag = index % 3 === 0 ? 4.4 : 0.8 + (index % 5) * 0.18;
+  const streaming = 1.5 + (index % 8) * 0.24;
+  const provider = 80 + (index % 13) * 11;
+  const externalTool = index % 4 === 0 ? 25 + (index % 9) * 3 : 0;
+  const network = 8 + (index % 10) * 1.7;
+  const overhead = ingress + pipeline + persistence + pluginIpc + rag + streaming;
+  const external = provider + externalTool + network;
+  const total = overhead + external;
+  return {
+    index,
+    segments_ms: {
+      ingress,
+      pipeline,
+      persistence,
+      plugin_ipc: pluginIpc,
+      rag,
+      streaming,
+      provider,
+      external_tool: externalTool,
+      network,
+    },
+    langbot_overhead_ms: Number(overhead.toFixed(3)),
+    external_latency_ms: Number(external.toFixed(3)),
+    e2e_latency_ms: Number(total.toFixed(3)),
+    accounting_gap_ms: Number((total - external - overhead).toFixed(6)),
+  };
+}
+
+async function main() {
+  const root = resolve(env.LBS_ROOT || process.cwd());
+  const caseId = "langbot-overhead-accounting-contract";
+  const runId = env.LBS_RUN_ID || `${timestampSlug()}-${caseId}`;
+  const evidenceDir = resolve(env.LBS_EVIDENCE_DIR || join(root, "reports", "evidence", runId));
+  await mkdir(evidenceDir, { recursive: true });
+
+  const startedAt = new Date();
+  const sampleCount = Number(env.LANGBOT_PERF_CONTRACT_SAMPLES || "80");
+  const overheadP95BudgetMs = Number(env.LANGBOT_PERF_OVERHEAD_P95_MS || "25");
+  const samples = Array.from({ length: sampleCount }, (_, index) => makeSample(index));
+  const overheads = samples.map((sample) => sample.langbot_overhead_ms);
+  const e2e = samples.map((sample) => sample.e2e_latency_ms);
+  const external = samples.map((sample) => sample.external_latency_ms);
+  const gaps = samples.map((sample) => Math.abs(sample.accounting_gap_ms));
+  const memory = process.memoryUsage();
+
+  const metrics = {
+    probe: caseId,
+    sample_count: sampleCount,
+    langbot_overhead_ms: stats(overheads),
+    e2e_latency_ms: stats(e2e),
+    external_latency_ms: stats(external),
+    accounting_gap_max_ms: Number(Math.max(...gaps).toFixed(6)),
+    samples,
+  };
+  const thresholds = {
+    sample_count: threshold(sampleCount, 50, ">="),
+    langbot_overhead_p95_ms: threshold(metrics.langbot_overhead_ms.p95, overheadP95BudgetMs, "<="),
+    accounting_gap_max_ms: threshold(metrics.accounting_gap_max_ms, 0.001, "<="),
+  };
+  const status = Object.values(thresholds).every((item) => item.pass) ? "pass" : "fail";
+  const metricsPath = join(evidenceDir, "metrics.json");
+  const thresholdsPath = join(evidenceDir, "thresholds.json");
+  const resourceLogPath = join(evidenceDir, "resource-log.json");
+  const automationResultPath = join(evidenceDir, "automation-result.json");
+  const resultPath = join(evidenceDir, "result.json");
+
+  await writeFile(metricsPath, `${JSON.stringify(metrics, null, 2)}\n`, "utf8");
+  await writeFile(thresholdsPath, `${JSON.stringify(thresholds, null, 2)}\n`, "utf8");
+  await writeFile(resourceLogPath, `${JSON.stringify({ memory, pid: process.pid }, null, 2)}\n`, "utf8");
+
+  const finishedAt = new Date();
+  const result = {
+    source: "automation",
+    case_id: caseId,
+    run_id: runId,
+    status,
+    reason: status === "pass"
+      ? "Overhead accounting contract passed all thresholds."
+      : "Overhead accounting contract breached one or more thresholds.",
+    started_at: startedAt.toISOString(),
+    started_at_local: localIsoWithOffset(startedAt),
+    finished_at: finishedAt.toISOString(),
+    finished_at_local: localIsoWithOffset(finishedAt),
+    duration_ms: finishedAt.getTime() - startedAt.getTime(),
+    metrics_summary: {
+      sample_count: metrics.sample_count,
+      langbot_overhead_p95_ms: metrics.langbot_overhead_ms.p95,
+      e2e_latency_p95_ms: metrics.e2e_latency_ms.p95,
+      external_latency_p95_ms: metrics.external_latency_ms.p95,
+      accounting_gap_max_ms: metrics.accounting_gap_max_ms,
+    },
+    thresholds_summary: thresholds,
+    artifacts: {
+      metrics_json: metricsPath,
+      thresholds_json: thresholdsPath,
+      resource_log_json: resourceLogPath,
+      automation_result_json: automationResultPath,
+      result_json: resultPath,
+    },
+    evidence_collected: ["metrics", "resource_log", "filesystem"],
+  };
+
+  const resultText = `${JSON.stringify(result, null, 2)}\n`;
+  await writeFile(automationResultPath, resultText, "utf8");
+  await writeFile(resultPath, resultText, "utf8");
+  console.log(JSON.stringify(result, null, 2));
+  exit(status === "pass" ? 0 : 1);
+}
+
+await main();

skills/skills/langbot-testing/probes/lib/fake-provider-timing.mjs

@@ -0,0 +1,134 @@
+export function summarizeFakeProviderState(state) {
+  if (!state) return null;
+  const recentRequests = Array.isArray(state.recent_requests) ? state.recent_requests : [];
+  const chatRequests = recentRequests.filter((request) => String(request?.path || "").includes("/chat/completions"));
+  const successfulRequests = chatRequests.filter((request) => request?.status === "ok");
+  const faultRequests = chatRequests.filter((request) => (
+    request?.should_fail === true
+      || request?.status === "http_fault"
+      || (Number.isFinite(request?.http_status) && request.http_status >= 400)
+  ));
+
+  return {
+    status: state.status || "unknown",
+    url: state.url || "",
+    request_count: Number.isFinite(state.request_count) ? state.request_count : recentRequests.length,
+    recent_request_count: recentRequests.length,
+    chat_request_count: chatRequests.length,
+    fault_count: faultRequests.length,
+    streamed_request_count: chatRequests.filter((request) => request?.stream === true).length,
+    duration_ms: stats(chatRequests.map((request) => numberOrNull(request?.duration_ms)).filter(Number.isFinite)),
+    successful_duration_ms: stats(successfulRequests.map((request) => numberOrNull(request?.duration_ms)).filter(Number.isFinite)),
+    first_chunk_ms: stats(successfulRequests.map((request) => numberOrNull(request?.first_chunk_ms)).filter(Number.isFinite)),
+    first_content_chunk_ms: stats(successfulRequests.map((request) => numberOrNull(request?.first_content_chunk_ms)).filter(Number.isFinite)),
+    content_chunk_count: stats(successfulRequests.map((request) => numberOrNull(request?.content_chunk_count)).filter(Number.isFinite)),
+    config: state.config || {},
+  };
+}
+
+export function buildProviderTimingMetrics(samples, state) {
+  const recentRequests = Array.isArray(state?.recent_requests) ? state.recent_requests : [];
+  const byExpectedText = new Map();
+  for (const request of recentRequests) {
+    const expected = String(request?.expected_text || "");
+    if (!expected) continue;
+    if (!byExpectedText.has(expected)) byExpectedText.set(expected, []);
+    byExpectedText.get(expected).push(request);
+  }
+
+  const segments = [];
+  const missingExpectedText = [];
+  for (const sample of samples) {
+    const expected = String(sample?.expected_text || "");
+    if (!expected) continue;
+    const request = (byExpectedText.get(expected) || []).shift();
+    if (!request) {
+      missingExpectedText.push(expected);
+      continue;
+    }
+    const segment = buildTimingSegment(sample, request);
+    if (segment) segments.push(segment);
+  }
+
+  const values = (key) => segments.map((segment) => numberOrNull(segment[key])).filter(Number.isFinite);
+  return {
+    matched_request_count: segments.length,
+    missing_provider_match_count: missingExpectedText.length,
+    missing_expected_text: missingExpectedText.slice(0, 20),
+    send_to_provider_start_ms: stats(values("send_to_provider_start_ms")),
+    provider_duration_ms: stats(values("provider_duration_ms")),
+    provider_finish_to_ws_final_ms: stats(values("provider_finish_to_ws_final_ms")),
+    langbot_overhead_estimate_ms: stats(values("langbot_overhead_estimate_ms")),
+    e2e_minus_provider_ms: stats(values("e2e_minus_provider_ms")),
+    provider_first_content_to_ws_first_content_ms: stats(values("provider_first_content_to_ws_first_content_ms")),
+    segments,
+  };
+}
+
+function buildTimingSegment(sample, request) {
+  const sentEpochMs = numberOrNull(sample.sent_epoch_ms);
+  const finishedEpochMs = numberOrNull(sample.finished_epoch_ms);
+  const providerStartedEpochMs = numberOrNull(request.started_epoch_ms);
+  const providerFinishedEpochMs = numberOrNull(request.finished_epoch_ms);
+  const providerFirstContentEpochMs = numberOrNull(request.first_content_chunk_epoch_ms);
+  const wsFirstContentEpochMs = numberOrNull(sample.first_assistant_content_epoch_ms);
+  const responseDurationMs = numberOrNull(sample.response_duration_ms);
+  const providerDurationMs = numberOrNull(request.duration_ms);
+
+  const sendToProviderStartMs = finiteDelta(providerStartedEpochMs, sentEpochMs);
+  const providerFinishToWsFinalMs = finiteDelta(finishedEpochMs, providerFinishedEpochMs);
+  const e2eMinusProviderMs = Number.isFinite(responseDurationMs) && Number.isFinite(providerDurationMs)
+    ? rounded(responseDurationMs - providerDurationMs)
+    : null;
+  const overheadEstimateMs = Number.isFinite(sendToProviderStartMs) && Number.isFinite(providerFinishToWsFinalMs)
+    ? rounded(sendToProviderStartMs + providerFinishToWsFinalMs)
+    : e2eMinusProviderMs;
+
+  return {
+    sample_index: sample.index,
+    pipeline_label: sample.pipeline_label || "",
+    expected_text: sample.expected_text || "",
+    provider_request_id: request.id || "",
+    provider_request_number: request.request_number ?? null,
+    response_duration_ms: responseDurationMs,
+    provider_duration_ms: providerDurationMs,
+    send_to_provider_start_ms: sendToProviderStartMs,
+    provider_finish_to_ws_final_ms: providerFinishToWsFinalMs,
+    langbot_overhead_estimate_ms: overheadEstimateMs,
+    e2e_minus_provider_ms: e2eMinusProviderMs,
+    provider_first_content_to_ws_first_content_ms: finiteDelta(wsFirstContentEpochMs, providerFirstContentEpochMs),
+    provider_status: request.status || "",
+    provider_http_status: request.http_status ?? null,
+  };
+}
+
+function finiteDelta(left, right) {
+  return Number.isFinite(left) && Number.isFinite(right) ? rounded(left - right) : null;
+}
+
+export function stats(values) {
+  if (values.length === 0) return { min: 0, p50: 0, p95: 0, p99: 0, max: 0 };
+  return {
+    min: rounded(Math.min(...values)),
+    p50: percentile(values, 50),
+    p95: percentile(values, 95),
+    p99: percentile(values, 99),
+    max: rounded(Math.max(...values)),
+  };
+}
+
+export function percentile(values, percentileValue) {
+  if (values.length === 0) return 0;
+  const sorted = [...values].sort((a, b) => a - b);
+  const index = Math.min(sorted.length - 1, Math.ceil((percentileValue / 100) * sorted.length) - 1);
+  return rounded(sorted[index]);
+}
+
+export function rounded(value) {
+  return Number(value.toFixed(3));
+}
+
+function numberOrNull(value) {
+  const number = Number(value);
+  return Number.isFinite(number) ? number : null;
+}

skills/skills/langbot-testing/references/performance-reliability-testing.md

@@ -0,0 +1,285 @@
+# Performance And Reliability Testing
+
+Use this reference when a QA request asks whether LangBot is fast enough,
+stable under load, or resilient to controlled faults.
+
+These probes are manual/non-required QA gates unless a case or suite explicitly
+states otherwise. They depend on a live local backend, mutable QA fixtures, and
+operator-selected environment variables, so do not promote them to required CI
+checks until fake-provider isolation, ownership markers, and cleanup are in
+place.
+
+## Scope
+
+Treat `skills/` as the QA control plane:
+
+- Cases define intent, readiness, thresholds, and required evidence.
+- Probe scripts collect metrics, traces, resource logs, and artifacts.
+- Reports classify the same run as `pass`, `fail`, `blocked`,
+  `env_issue`, or `flaky`.
+
+Do not turn `skills/` into a load generator or chaos engine. Call a focused
+tool from a `mode: probe` case when the test needs one, for example k6,
+Locust, pytest-benchmark, Playwright trace collection, Toxiproxy, Docker, or a
+Kubernetes disruption tool.
+
+## LangBot Performance Model
+
+For LangBot, performance is the cost LangBot adds around external systems:
+
+```text
+LangBot overhead = end-to-end latency - provider latency - external tool latency - network/fault injection latency
+```
+
+Measure user experience and internal composition separately:
+
+- WebUI load and interaction latency.
+- Debug Chat send-to-first-visible-token and send-to-completion latency.
+- Pipeline, RAG, plugin runtime, MCP, AgentRunner, and persistence segment
+  latency.
+- Queue wait time, concurrency, throughput, timeout rate, and p95/p99 latency.
+- Startup, plugin install, knowledge-base ingestion, migration, and recovery
+  time.
+
+Do not report a single message round-trip time as "LangBot performance" unless
+the report also explains external provider/tool/network time.
+
+## Evidence Contract
+
+Performance and reliability cases should declare the evidence they need:
+
+- `metrics`: machine-readable latency, throughput, error-rate, or recovery
+  metrics, usually `metrics.json`.
+- `resource_log`: CPU, memory, process, connection, queue, or file descriptor
+  samples.
+- `trace`: browser, HTTP, database, or runtime trace artifacts.
+- `profile`: CPU, memory, or flamegraph profile artifacts.
+- `backend_log`, `network`, `api_diagnostic`, and `filesystem` as supporting
+  evidence when relevant.
+
+Automation should write `automation-result.json` with these fields when
+available:
+
+```json
+{
+  "status": "pass",
+  "reason": "Probe passed all thresholds.",
+  "metrics_summary": {
+    "langbot_overhead_p95_ms": 12.4,
+    "error_rate": 0
+  },
+  "thresholds_summary": {
+    "langbot_overhead_p95_ms": { "actual": 12.4, "max": 50, "pass": true }
+  },
+  "artifacts": {
+    "metrics_json": "/path/to/metrics.json"
+  },
+  "evidence_collected": ["metrics", "filesystem"]
+}
+```
+
+Synthetic contract probes are useful for checking the QA harness, but they are
+not live product performance results. Label them as contract probes in the case
+title, checks, and report.
+
+## Chaos And Reliability Rules
+
+Chaos tests must be narrow and reversible:
+
+- Declare the fault model in `fault_model_json`.
+- Record blast radius, target component, injection method, duration, and abort
+  conditions.
+- Capture recovery checks and cleanup steps in the case.
+- Classify unavailable dependencies as `env_issue` unless the target behavior
+  is LangBot's handling of that dependency failure.
+- Do not run destructive fault injection against a shared or production-like
+  instance without explicit operator approval.
+
+Recommended first fault models:
+
+- Provider timeout or HTTP 429 from a fake provider endpoint.
+- Plugin runtime disconnect/reconnect in a local instance.
+- MCP stdio server exits mid-call.
+- RAG parser fixture fails once and recovers on retry.
+- Backend API endpoint returns 5xx from a controlled local proxy.
+
+## Starter Live Probes
+
+The starter gate separates QA-harness contracts from live product checks:
+
+- `langbot-overhead-accounting-contract` verifies that reports can carry
+  overhead accounting metrics. It uses deterministic synthetic samples and is
+  not live product performance.
+- `langbot-fault-taxonomy-contract` verifies that fault scenarios declare
+  expected status, recovery, and cleanup before destructive chaos tests are
+  added.
+- `langbot-live-backend-latency` checks the unauthenticated `/healthz`
+  endpoint for basic backend responsiveness.
+- `langbot-live-control-plane-api` checks `/healthz` and
+  `/api/v1/system/info` for HTTP 200, JSON `code: 0`, response shape, and
+  per-endpoint p95 latency.
+- `langbot-live-backend-log-health` scans the recent backend log window for
+  fail-severity runtime findings. It is the reliability guard that should fail
+  the gate when HTTP probes pass but backend logs contain Traceback, ImportError,
+  ERROR, unclosed sessions, or unawaited coroutine signals.
+
+Do not treat these starter live probes as Debug Chat or model-provider
+performance. They are control-plane readiness checks; user-facing performance
+needs browser/WebSocket/message-path measurements.
+
+## Debug Chat Load And Fake Provider Baseline
+
+Use `langbot-fake-provider-debug-chat-load` before real-provider load checks.
+The setup automation starts a local OpenAI-compatible fake provider, registers
+it as a normal LangBot provider/model, configures a local-agent pipeline, resets
+Debug Chat, and then drives concurrent WebSocket messages through the live
+backend.
+
+This is not a mocked backend test. It still exercises:
+
+- provider/model persistence and runtime reload;
+- LiteLLM OpenAI-compatible requester path;
+- local-agent runner selection and pipeline execution;
+- Debug Chat WebSocket adapter and broadcast behavior;
+- backend concurrency, timeout, and error-rate accounting.
+
+The fake provider is deterministic and can inject controlled latency or faults
+with `LANGBOT_FAKE_PROVIDER_*` variables, so it is the baseline for LangBot
+message-path overhead. A fake-provider process keeps process-global config,
+request counters, and recent request history; run fake-provider probes serially
+or give each run its own provider instance. Concurrent probes against the same
+fake-provider URL can reset or reconfigure each other's metrics.
+
+The probe uses unique expected response tokens per
+request because Debug Chat broadcasts messages to every connection in the same
+session; unique tokens prevent one connection from counting another
+connection's response as its own.
+
+When the fake provider is used, reports also include provider-side timing in
+`metrics.json`:
+
+- `fake_provider.duration_ms` and `fake_provider.first_content_chunk_ms`
+  measure the controlled provider itself.
+- `provider_timing.send_to_provider_start_ms` estimates WebSocket ingress,
+  pipeline dispatch, runner setup, and requester time before the provider
+  receives the request.
+- `provider_timing.provider_finish_to_ws_final_ms` estimates the path from
+  provider completion back to the final Debug Chat WebSocket response.
+- `provider_timing.langbot_overhead_estimate_ms` is the sum of those two
+  LangBot-side segments when wall-clock timestamps can be matched by the
+  unique expected response token.
+
+After the baseline passes, run `langbot-fake-provider-debug-chat-slow-load` to
+keep the same live backend path while injecting deterministic streaming latency.
+Run `langbot-fake-provider-debug-chat-fault-recovery` to inject bounded HTTP
+provider failures and require both observed failures and later successful
+requests. The fault-recovery case is deliberately sequential because failed
+Debug Chat responses do not carry a unique success token that can be attributed
+to one concurrent connection.
+
+Run `langbot-fake-provider-debug-chat-cross-pipeline-isolation` separately via
+`langbot-debug-chat-isolation-gate`. Current LangBot releases may fail it because
+of product bug [#2286](https://github.com/langbot-app/LangBot/issues/2286), where
+Debug Chat replies can read singleton WebSocket proxy pipeline state after a
+later message overwrites it. Treat that failure as regression evidence for the
+product fix rather than as a fake-provider latency finding.
+
+Use `langbot-space-debug-chat-concurrency-smoke` after the fake-provider
+baseline. It runs a deliberately small real Space-provider batch and reports
+user-visible latency, not pure LangBot overhead. Space/model/network failures
+are dependency findings until the fake baseline shows the same symptom.
+If a Space smoke passes but log guard finds telemetry posting Tracebacks,
+classify that separately as `telemetry-proxy-noise` instead of clearing the
+proxy or treating the Debug Chat path as failed.
+
+Useful commands:
+
+```bash
+rtk bin/lbs test run langbot-fake-provider-debug-chat-load --run-id langbot-fake-load-local
+rtk bin/lbs test run langbot-fake-provider-debug-chat-slow-load --run-id langbot-fake-slow-local
+rtk bin/lbs test run langbot-fake-provider-debug-chat-fault-recovery --run-id langbot-fake-fault-local
+rtk bin/lbs suite run langbot-debug-chat-isolation-gate --run-id langbot-debug-chat-isolation-local --include-manual-check
+rtk bin/lbs test run langbot-space-debug-chat-concurrency-smoke --run-id langbot-space-smoke-local
+rtk bin/lbs suite run langbot-debug-chat-load-gate --run-id langbot-debug-chat-load-local --include-manual-check
+```
+
+## Gate Layers
+
+Use the smallest gate that answers the quality question:
+
+- `langbot-performance-contract-gate`: fast synthetic checks for report shape,
+  threshold accounting, and fault taxonomy. Good for PR feedback when no live
+  service is running.
+- `langbot-live-backend-gate`: live backend `/healthz`,
+  `/api/v1/system/info`, and backend log health. Good after starting a local
+  LangBot backend.
+- `langbot-user-path-performance-gate`: browser-visible user path performance,
+  starting with Pipeline Debug Chat send-to-visible-completion latency. Run it
+  only when the browser profile and target pipeline are ready.
+- `langbot-debug-chat-load-gate`: manual WebSocket Debug Chat load checks,
+  starting with controlled fake-provider baseline, slow-provider, and
+  fault-recovery profiles, plus an optional low-volume real Space-provider
+  smoke. Run fake-provider cases serially when they share a provider URL.
+- `langbot-debug-chat-isolation-gate`: manual cross-pipeline Debug Chat
+  isolation regression gate. Current releases may fail because of #2286; keep it
+  separate from the normal load gate until that product fix lands.
+- `langbot-performance-reliability-gate`: combined starter gate for synthetic
+  contracts plus live backend checks.
+
+Keep environment diagnostics separate from product regressions. For example, a
+SOCKS proxy without Python `socksio` support should be fixed or clearly
+classified by `bin/lbs env doctor`; do not hide the resulting backend
+Traceback in reports.
+
+## Debug Chat Performance
+
+`pipeline-debug-chat-performance` reuses the browser Debug Chat automation and
+adds `metrics.json`, `metrics_summary`, and `thresholds_summary` to
+`automation-result.json`.
+
+Current metric:
+
+```text
+response_duration_ms = prompt send -> expected assistant response visible and stable
+```
+
+This is a user-path metric, not pure LangBot overhead. If it regresses, inspect
+provider latency, model route health, plugin/runtime logs, WebSocket behavior,
+and browser console/network evidence before attributing the whole duration to
+LangBot.
+
+### User-Path Gate Runbook
+
+1. Start the backend and frontend. The frontend must be launched with
+   `VITE_API_BASE_URL="$LANGBOT_BACKEND_URL"` so browser API calls reach the
+   backend.
+2. Run `node scripts/e2e/ensure-local-agent-pipeline.mjs --write-env`. The
+   setup refreshes the local QA login, skips the wizard, prepares a Debug Chat
+   pipeline, scans Space models, tests candidates, writes tested fallback
+   models, and writes the selected pipeline/model env values to
+   `skills/.env.local`.
+3. If setup returns `env_issue`, read `model_tests` and provider errors first.
+   A missing Space key, failed Space scan, or unavailable model route is not a
+   LangBot performance regression.
+4. Run
+   `bin/lbs suite run langbot-user-path-performance-gate --include-manual-check`.
+5. Interpret `response_p95_ms` as browser-visible send-to-completion time. It
+   includes provider latency; use backend logs and model test evidence to
+   separate LangBot overhead from the external model route.
+
+The setup keeps a `max-round` value in the generated pipeline config only
+because the current backend truncator still reads that field directly. Do not
+use it as a quality requirement for future local-agent behavior.
+
+## Running The First Gate
+
+Start with the reusable suite:
+
+```bash
+rtk bin/lbs suite plan langbot-performance-reliability-gate
+rtk bin/lbs suite start langbot-performance-reliability-gate --run-id langbot-perf-rel-local
+```
+
+Run synthetic contract probes first. Run live probes only after the selected
+backend/frontend instance is reachable and the run owner accepts any fault
+scope.

skills/skills/langbot-testing/suites/langbot-debug-chat-isolation-gate.yaml

@@ -0,0 +1,13 @@
+id: langbot-debug-chat-isolation-gate
+title: "LangBot Debug Chat isolation gate"
+description: "Manual/non-required cross-pipeline Debug Chat isolation gate. Current releases may fail this gate because of product bug #2286; use it as regression evidence after the routing fix lands."
+type: reliability
+priority: p1
+tags:
+  - reliability
+  - debug-chat
+  - websocket
+  - isolation
+  - concurrency
+cases:
+  - langbot-fake-provider-debug-chat-cross-pipeline-isolation

skills/skills/langbot-testing/suites/langbot-debug-chat-load-gate.yaml

@@ -0,0 +1,15 @@
+id: langbot-debug-chat-load-gate
+title: "LangBot Debug Chat load gate"
+description: "Manual/non-required message-path load checks for Pipeline Debug Chat: controlled fake-provider baseline, slow-provider and fault-recovery profiles, plus optional real Space-provider smoke. Cross-pipeline isolation is split into langbot-debug-chat-isolation-gate because current releases may fail it due to product bug #2286."
+type: performance
+priority: p1
+tags:
+  - performance
+  - debug-chat
+  - websocket
+  - load
+cases:
+  - langbot-fake-provider-debug-chat-load
+  - langbot-fake-provider-debug-chat-slow-load
+  - langbot-fake-provider-debug-chat-fault-recovery
+  - langbot-space-debug-chat-concurrency-smoke

skills/skills/langbot-testing/suites/langbot-live-backend-gate.yaml

@@ -0,0 +1,14 @@
+id: langbot-live-backend-gate
+title: "LangBot live backend reliability gate"
+description: "Live backend control-plane responsiveness and runtime log health checks for a locally running LangBot instance."
+type: reliability
+priority: p1
+tags:
+  - performance
+  - reliability
+  - live-backend
+  - metrics
+cases:
+  - langbot-live-backend-latency
+  - langbot-live-control-plane-api
+  - langbot-live-backend-log-health

skills/skills/langbot-testing/suites/langbot-performance-contract-gate.yaml

@@ -0,0 +1,13 @@
+id: langbot-performance-contract-gate
+title: "LangBot performance contract gate"
+description: "Fast synthetic contract checks for performance metric accounting and non-destructive reliability fault taxonomy."
+type: contract
+priority: p1
+tags:
+  - performance
+  - reliability
+  - contract
+  - metrics
+cases:
+  - langbot-overhead-accounting-contract
+  - langbot-fault-taxonomy-contract

skills/skills/langbot-testing/suites/langbot-performance-reliability-gate.yaml

@@ -0,0 +1,16 @@
+id: langbot-performance-reliability-gate
+title: "LangBot performance and reliability starter gate"
+description: "Starter gate for LangBot performance accounting, live backend control-plane latency, and non-destructive fault taxonomy checks."
+type: reliability
+priority: p1
+tags:
+  - performance
+  - reliability
+  - metrics
+  - chaos
+cases:
+  - langbot-overhead-accounting-contract
+  - langbot-fault-taxonomy-contract
+  - langbot-live-backend-latency
+  - langbot-live-control-plane-api
+  - langbot-live-backend-log-health

skills/skills/langbot-testing/suites/langbot-user-path-performance-gate.yaml

@@ -0,0 +1,12 @@
+id: langbot-user-path-performance-gate
+title: "LangBot user-path performance gate"
+description: "Browser-visible performance checks for user-facing LangBot paths such as Pipeline Debug Chat."
+type: performance
+priority: p1
+tags:
+  - performance
+  - browser
+  - debug-chat
+  - user-path
+cases:
+  - pipeline-debug-chat-performance

skills/skills/langbot-testing/troubleshooting/telemetry-proxy-noise.yaml

@@ -0,0 +1,23 @@
+id: telemetry-proxy-noise
+title: "Telemetry posting fails through the proxy while the target flow succeeds"
+date: 2026-06-25
+category: env_issue
+symptoms:
+  - "The target Debug Chat or provider smoke request completes successfully."
+  - "The same log window contains a Traceback for telemetry posting."
+  - "The traceback references the Space telemetry endpoint."
+patterns:
+  - "Failed to post telemetry"
+  - "https://space.langbot.app/api/v1/telemetry"
+  - "httpx.ConnectError"
+likely_causes:
+  - "The backend process inherited proxy settings that are required for model/provider access but unreliable for telemetry posting."
+  - "The telemetry endpoint is temporarily unreachable through the local proxy route."
+  - "TLS or proxy negotiation failed for the non-critical telemetry request."
+fix_steps:
+  - "Keep the proxy configuration needed for model/provider access; do not clear it only to hide telemetry noise."
+  - "Check that uppercase and lowercase proxy variables are consistent before rerunning a live Space smoke."
+  - "Classify the target flow and log-health result separately: a successful Debug Chat run can still have an environment log-health finding."
+verification: "A rerun shows the target case success patterns and no telemetry Traceback in the scanned log window, or the report explicitly records the telemetry issue as environment noise."
+related_cases:
+  - langbot-space-debug-chat-concurrency-smoke

skills/src/commands/env.ts

@@ -1,5 +1,7 @@
 import { existsSync } from "node:fs";
+import { spawnSync } from "node:child_process";
 import { Socket } from "node:net";
+import { join } from "node:path";
 import type { CommandContext } from "../types.ts";
 import { parseOptions } from "../cli.ts";
 import { loadEnv } from "../fs.ts";
@@ -88,6 +90,37 @@ function compareProxyPair(env: Record<string, string>, upper: string, lower: str
   return null;
 }
 
+function envValue(env: Record<string, string>, key: string): string {
+  return process.env[key] ?? env[key] ?? "";
+}
+
+function activeSocksProxy(env: Record<string, string>): { key: string; value: string } | null {
+  for (const key of ["ALL_PROXY", "all_proxy", "HTTPS_PROXY", "https_proxy", "HTTP_PROXY", "http_proxy"]) {
+    const value = envValue(env, key);
+    if (/^socks/i.test(value)) return { key, value };
+  }
+  return null;
+}
+
+function checkSocksio(env: Record<string, string>): string | null {
+  const proxy = activeSocksProxy(env);
+  if (!proxy) return null;
+
+  const repo = env.LANGBOT_REPO;
+  const python = repo ? join(repo, ".venv", "bin", "python") : "";
+  if (!python || !existsSync(python)) {
+    return `SOCKS proxy ${proxy.key} is configured (${redactEnvValue(proxy.key, proxy.value)}), but LangBot venv python was not found; after creating the venv, verify it can import socksio.`;
+  }
+
+  const result = spawnSync(python, ["-c", "import socksio"], {
+    encoding: "utf8",
+    timeout: 5000,
+  });
+  if (result.status === 0) return null;
+
+  return `SOCKS proxy ${proxy.key} is configured (${redactEnvValue(proxy.key, proxy.value)}), but ${python} cannot import socksio; run \`${python} -m pip install socksio\` or start LangBot without SOCKS proxy env.`;
+}
+
 export async function commandEnvDoctor(ctx: CommandContext): Promise<number> {
   const env = loadEnv(ctx.root);
   const failures: string[] = [];
@@ -117,6 +150,8 @@ export async function commandEnvDoctor(ctx: CommandContext): Promise<number> {
   ]) {
     if (mismatch) failures.push(mismatch);
   }
+  const socksioFailure = checkSocksio(env);
+  if (socksioFailure) failures.push(socksioFailure);
 
   for (const [label, result] of await Promise.all([
     checkUrl("LANGBOT_BACKEND_URL", env.LANGBOT_BACKEND_URL).then((result) => ["LANGBOT_BACKEND_URL", result] as const),

skills/src/commands/suite.ts

@@ -465,6 +465,41 @@ function outputTail(value: string | Buffer | null | undefined): string {
   return String(value ?? "").trim().slice(-4000);
 }
 
+function exitStatusFromResultStatus(status: string): number {
+  if (status === "pass") return 0;
+  if (status === "blocked" || status === "env_issue" || status === "flaky") return 2;
+  return 1;
+}
+
+function executionStatusFromExitStatus(status: number): string {
+  if (status === 0) return "ok";
+  if (status === 2) return "classified";
+  return "nonzero";
+}
+
+function executionFromCaseResultFile(caseItem: Record<string, unknown>): Record<string, unknown> | null {
+  const resultPath = join(String(caseItem.evidence_dir), "result.json");
+  if (!existsSync(resultPath)) return null;
+  try {
+    const parsed = JSON.parse(readFileSync(resultPath, "utf8")) as Record<string, unknown>;
+    if (
+      parsed.case_id !== caseItem.id ||
+      parsed.run_id !== caseItem.run_id ||
+      typeof parsed.status !== "string"
+    ) return null;
+    const exitStatus = exitStatusFromResultStatus(parsed.status);
+    return {
+      status: executionStatusFromExitStatus(exitStatus),
+      exit_status: exitStatus,
+      reason: typeof parsed.reason === "string" ? parsed.reason : "result.json completed",
+      result_status: parsed.status,
+      result_json: resultPath,
+    };
+  } catch {
+    return null;
+  }
+}
+
 function executionProblemStatus(executions: Array<Record<string, unknown>>): string {
   const statuses = executions.map((item) => String(item.status));
   if (statuses.includes("nonzero")) return "fail";
@@ -523,12 +558,18 @@ export function commandSuiteRun(ctx: CommandContext): number {
       encoding: "utf8",
       stdio: options.json === true ? "pipe" : "inherit",
     });
-    const status = result.error ? 1 : result.status ?? 1;
+    const fileExecution = result.error ? executionFromCaseResultFile(caseItem) : null;
+    const status = typeof fileExecution?.exit_status === "number"
+      ? fileExecution.exit_status
+      : result.error ? 1 : result.status ?? 1;
     executions.push({
       id: caseItem.id,
-      status: status === 0 ? "ok" : "nonzero",
+      status: fileExecution?.status ?? executionStatusFromExitStatus(status),
       exit_status: status,
-      reason: result.error?.message || "",
+      reason: fileExecution?.reason ?? result.error?.message ?? "",
+      result_status: fileExecution?.result_status,
+      result_json: fileExecution?.result_json,
+      spawn_error: fileExecution && result.error ? result.error.message : undefined,
       stdout: outputTail(result.stdout),
       stderr: outputTail(result.stderr),
     });

skills/src/commands/test.ts

@@ -271,7 +271,7 @@ function reportTemplate(mode: string): Record<string, string> {
       target_tested: "Probe target, endpoint, file, command, or service actually checked",
       execution_path: "automation script | shell command | direct API | other",
       probe_result: "What the probe observed",
-      logs_or_artifacts: "Log, filesystem, API, or other artifact paths collected",
+      metrics_or_artifacts: "Metrics, logs, filesystem artifacts, traces, or profiles collected",
       diagnostics: "Extra diagnostics used, if any",
       matched_troubleshooting: "Troubleshooting ids matched, if any",
       assets_to_update: "New case/reference/troubleshooting entries to add",
@@ -320,7 +320,7 @@ function manualEvidenceTemplate(mode: string): ManualEvidenceTemplate {
       target_tested: "TODO: probe target, endpoint, file, command, or service actually checked",
       execution_path: "TODO: automation script | shell command | direct API | other",
       probe_result: "TODO: observed probe result",
-      logs_or_artifacts: "TODO: evidence paths or skipped reason",
+      metrics_or_artifacts: "TODO: metrics, logs, filesystem artifacts, traces, or profiles collected",
       diagnostics: "TODO: additional diagnostics used, if any",
       matched_troubleshooting: "TODO: troubleshooting ids matched, if any",
       assets_to_update: "TODO: case/reference/troubleshooting updates to make",
@@ -1099,6 +1099,41 @@ function executionTail(value: string | Buffer | null | undefined): string {
   return String(value ?? "").trim().slice(-4000);
 }
 
+function exitStatusFromResultStatus(status: string): number {
+  if (status === "pass") return 0;
+  if (status === "blocked" || status === "env_issue" || status === "flaky") return 2;
+  return 1;
+}
+
+function executionStatusFromExitStatus(status: number): string {
+  if (status === 0) return "ok";
+  if (status === 2) return "classified";
+  return "nonzero";
+}
+
+function executionFromAutomationResultFile(
+  evidenceDir: string,
+  caseId: string,
+  runId: string,
+): { status: string; exit_status: number; reason: string; result_status: string; path: string } | null {
+  const resultPath = join(evidenceDir, "automation-result.json");
+  if (!existsSync(resultPath)) return null;
+  try {
+    const parsed = JSON.parse(readFileSync(resultPath, "utf8")) as Record<string, unknown>;
+    if (parsed.case_id !== caseId || parsed.run_id !== runId || typeof parsed.status !== "string") return null;
+    const exitStatus = exitStatusFromResultStatus(parsed.status);
+    return {
+      status: executionStatusFromExitStatus(exitStatus),
+      exit_status: exitStatus,
+      reason: typeof parsed.reason === "string" ? parsed.reason : "automation-result.json completed",
+      result_status: parsed.status,
+      path: resultPath,
+    };
+  } catch {
+    return null;
+  }
+}
+
 function runSetupAutomation(
   ctx: CommandContext,
   item: StructuredItem,
@@ -1224,6 +1259,30 @@ export function commandTestRun(ctx: CommandContext): number {
   });
 
   if (result.error) {
+    const fileExecution = executionFromAutomationResultFile(
+      run.automation.evidence_dir,
+      String(run.case.id),
+      run.run_id,
+    );
+    if (fileExecution) {
+      if (options.json !== true) {
+        console.error(`WARN: automation spawn reported an error, but ${fileExecution.path} completed: ${result.error.message}`);
+      }
+      if (options.json === true) {
+        console.log(JSON.stringify({
+          run,
+          setup_executions: setupExecutions,
+          automation_execution: {
+            ...fileExecution,
+            spawn_error: result.error.message,
+            stdout: executionTail(result.stdout),
+            stderr: executionTail(result.stderr),
+          },
+          exit_status: fileExecution.exit_status,
+        }, null, 2));
+      }
+      return fileExecution.exit_status;
+    }
     if (options.json !== true) console.error(`ERROR: failed to run automation: ${result.error.message}`);
     if (options.json === true) {
       console.log(JSON.stringify({
@@ -1247,7 +1306,7 @@ export function commandTestRun(ctx: CommandContext): number {
       run,
       setup_executions: setupExecutions,
       automation_execution: {
-        status: status === 0 ? "ok" : "nonzero",
+        status: executionStatusFromExitStatus(status),
         exit_status: status,
         stdout: executionTail(result.stdout),
         stderr: executionTail(result.stderr),
@@ -1311,6 +1370,7 @@ function renderMarkdownReport(report: TestReport): string {
   const environment = report.environment;
   const logGuard = report.log_guard;
   const troubleshooting = report.troubleshooting;
+  const automation = report.automation_result;
   const lines: string[] = [];
 
   lines.push(`# Test Report: ${reportCase.id}`);
@@ -1323,20 +1383,41 @@ function renderMarkdownReport(report: TestReport): string {
   lines.push(`Type: ${reportCase.type}`);
   lines.push("");
   lines.push("## Result");
+  if (automation.status === "loaded" && automation.result) {
+    lines.push(`- result: ${automation.result}`);
+    if (automation.reason) lines.push(`- reason: ${automation.reason}`);
+    if (automation.url) lines.push(`- target_tested: ${automation.url}`);
+    if (automation.path) lines.push(`- automation_result: ${automation.path}`);
+    if (automation.artifacts) lines.push(`- artifacts: ${JSON.stringify(automation.artifacts)}`);
+  } else {
     lines.push(`- result: ${evidence.result}`);
     for (const [key, value] of Object.entries(evidence)) {
       if (key !== "result") lines.push(`- ${key}: ${value}`);
     }
+  }
   lines.push("");
   lines.push("## Automation Result");
-  lines.push(`- status: ${report.automation_result.status}`);
+  lines.push(`- status: ${automation.status}`);
-  if (report.automation_result.path) lines.push(`- path: ${report.automation_result.path}`);
+  if (automation.path) lines.push(`- path: ${automation.path}`);
-  if (report.automation_result.result) lines.push(`- result: ${report.automation_result.result}`);
+  if (automation.result) lines.push(`- result: ${automation.result}`);
-  if (report.automation_result.reason) lines.push(`- reason: ${report.automation_result.reason}`);
+  if (automation.reason) lines.push(`- reason: ${automation.reason}`);
-  if (report.automation_result.started_at_local) lines.push(`- started_at_local: ${report.automation_result.started_at_local}`);
+  if (automation.duration_ms !== undefined) lines.push(`- duration_ms: ${automation.duration_ms}`);
-  if (report.automation_result.finished_at_local) lines.push(`- finished_at_local: ${report.automation_result.finished_at_local}`);
+  if (automation.started_at_local) lines.push(`- started_at_local: ${automation.started_at_local}`);
-  if (report.automation_result.url) lines.push(`- url: ${report.automation_result.url}`);
+  if (automation.finished_at_local) lines.push(`- finished_at_local: ${automation.finished_at_local}`);
-  if (report.automation_result.expected_text) lines.push(`- expected_text: ${report.automation_result.expected_text}`);
+  if (automation.url) lines.push(`- url: ${automation.url}`);
+  if (automation.expected_text) lines.push(`- expected_text: ${automation.expected_text}`);
+  if (automation.metrics_summary) {
+    lines.push("- metrics_summary:");
+    lines.push(`  ${JSON.stringify(automation.metrics_summary)}`);
+  }
+  if (automation.thresholds_summary) {
+    lines.push("- thresholds_summary:");
+    lines.push(`  ${JSON.stringify(automation.thresholds_summary)}`);
+  }
+  if (automation.artifacts) {
+    lines.push("- artifacts:");
+    lines.push(`  ${JSON.stringify(automation.artifacts)}`);
+  }
   lines.push("");
   lines.push("## Environment");
   for (const [key, value] of Object.entries(environment)) lines.push(`- ${key}=${value}`);

skills/src/commands/validate.ts

@@ -126,6 +126,9 @@ function validateCaseItem(root: string, item: StructuredItem, skillNames: Set<st
     ...validateEnvKeyScalar(item, "automation_pipeline_url_env"),
     ...validateEnvKeyScalar(item, "automation_pipeline_name_env"),
     ...validateJsonScalar(item, "automation_filesystem_checks_json"),
+    ...validateJsonScalar(item, "metrics_thresholds_json"),
+    ...validateJsonScalar(item, "load_profile_json"),
+    ...validateJsonScalar(item, "fault_model_json"),
     ...listValue(item.fields, "setup_automation").flatMap((entry) => (
       validateSetupAutomationEntry(root, entry, caseIds).map((error) => `${item.path}: ${error}`)
     )),
@@ -183,10 +186,62 @@ function validateCaseItem(root: string, item: StructuredItem, skillNames: Set<st
   if (timeout && (!/^\d+$/.test(timeout) || Number.parseInt(timeout, 10) <= 0)) {
     errors.push(`${item.path}: 'automation_response_timeout_ms' must be a positive integer string`);
   }
+  for (const key of [
+    "automation_debug_chat_load_requests",
+    "automation_debug_chat_load_concurrency",
+    "automation_debug_chat_load_timeout_ms",
+    "automation_debug_chat_load_response_p95_ms",
+    "automation_debug_chat_load_first_response_p95_ms",
+  ]) {
+    const value = scalar(item.fields, key);
+    if (value && (!/^\d+$/.test(value) || Number.parseInt(value, 10) <= 0)) {
+      errors.push(`${item.path}: '${key}' must be a positive integer string`);
+    }
+  }
+  for (const key of [
+    "automation_debug_chat_load_min_error_count",
+    "automation_debug_chat_load_min_ok_count",
+    "automation_debug_chat_load_min_provider_fault_count",
+    "automation_fake_provider_first_token_delay_ms",
+    "automation_fake_provider_chunk_delay_ms",
+    "automation_fake_provider_chunk_count",
+    "automation_fake_provider_fail_first_n",
+    "automation_fake_provider_fail_every_n",
+  ]) {
+    const value = scalar(item.fields, key);
+    if (value && (!/^\d+$/.test(value) || Number.parseInt(value, 10) < 0)) {
+      errors.push(`${item.path}: '${key}' must be a non-negative integer string`);
+    }
+  }
+  for (const key of ["automation_debug_chat_load_max_error_rate", "automation_debug_chat_load_min_error_rate"]) {
+    const value = scalar(item.fields, key);
+    if (value && (!/^(?:0(?:\.\d+)?|1(?:\.0+)?)$/.test(value))) {
+      errors.push(`${item.path}: '${key}' must be a number string between 0 and 1`);
+    }
+  }
+  const fakeProviderFaultStatus = scalar(item.fields, "automation_fake_provider_fault_status");
+  if (fakeProviderFaultStatus) {
+    const parsed = Number.parseInt(fakeProviderFaultStatus, 10);
+    if (!/^\d+$/.test(fakeProviderFaultStatus) || parsed < 400 || parsed > 599) {
+      errors.push(`${item.path}: 'automation_fake_provider_fault_status' must be an HTTP 4xx or 5xx status string`);
+    }
+  }
   const streamOutput = scalar(item.fields, "automation_stream_output");
   if (streamOutput && !["0", "1", "false", "true"].includes(streamOutput)) {
     errors.push(`${item.path}: 'automation_stream_output' must be one of 0, 1, false, or true`);
   }
+  for (const key of [
+    "automation_debug_chat_load_stream",
+    "automation_debug_chat_load_reset",
+    "automation_debug_chat_load_fail_on_final_mismatch",
+    "automation_fake_provider_fail_after_first_chunk",
+    "automation_fake_provider_dynamic_response",
+  ]) {
+    const value = scalar(item.fields, key);
+    if (value && !["0", "1", "false", "true"].includes(value)) {
+      errors.push(`${item.path}: '${key}' must be one of 0, 1, false, or true`);
+    }
+  }
   const imageBase64Fixture = scalar(item.fields, "automation_image_base64_fixture");
   if (imageBase64Fixture && !existsSync(join(root, imageBase64Fixture))) {
     errors.push(`${item.path}: automation image fixture does not exist: ${imageBase64Fixture}`);

skills/src/constants.ts

@@ -9,7 +9,18 @@ export const requiredEnvKeys = [
 ];
 
 export const caseModeValues = ["agent-browser", "probe"];
-export const caseTypeValues = ["smoke", "regression", "feature", "provider", "exploratory"];
+export const caseTypeValues = [
+  "smoke",
+  "regression",
+  "feature",
+  "provider",
+  "exploratory",
+  "contract",
+  "performance",
+  "reliability",
+  "chaos",
+  "security",
+];
 export const casePriorityValues = ["p0", "p1", "p2"];
 export const caseRiskValues = ["low", "medium", "high"];
 export const caseEvidenceValues = [
@@ -21,10 +32,24 @@ export const caseEvidenceValues = [
   "frontend_log",
   "api_diagnostic",
   "filesystem",
+  "metrics",
+  "trace",
+  "profile",
+  "resource_log",
 ];
 export const testResultStatusValues = ["pass", "fail", "blocked", "env_issue", "flaky"];
 export const troubleshootingCategoryValues = ["product", "env_issue", "external_dependency", "blocked", "flaky"];
-export const suiteTypeValues = ["smoke", "regression", "release_gate", "exploratory"];
+export const suiteTypeValues = [
+  "smoke",
+  "regression",
+  "release_gate",
+  "exploratory",
+  "contract",
+  "performance",
+  "reliability",
+  "chaos",
+  "security",
+];
 export const suiteRequiredStrings = ["id", "title", "description", "type", "priority"];
 export const suiteRequiredLists = ["tags", "cases"];
 

skills/src/log-guard.ts

@@ -91,6 +91,7 @@ export type AutomationResultEvidence = {
   path?: string;
   result?: string;
   reason?: string;
+  duration_ms?: number;
   started_at?: string;
   started_at_local?: string;
   finished_at?: string;
@@ -98,6 +99,9 @@ export type AutomationResultEvidence = {
   url?: string;
   prompt?: string;
   expected_text?: string;
+  metrics_summary?: Record<string, unknown>;
+  thresholds_summary?: Record<string, unknown>;
+  artifacts?: Record<string, unknown>;
 };
 
 type MutableScanState = {
@@ -594,6 +598,18 @@ function stringField(data: Record<string, unknown>, key: string): string | undef
   return typeof value === "string" && value.trim() ? value : undefined;
 }
 
+function numberField(data: Record<string, unknown>, key: string): number | undefined {
+  const value = data[key];
+  return typeof value === "number" && Number.isFinite(value) ? value : undefined;
+}
+
+function objectField(data: Record<string, unknown>, key: string): Record<string, unknown> | undefined {
+  const value = data[key];
+  return value && typeof value === "object" && !Array.isArray(value)
+    ? value as Record<string, unknown>
+    : undefined;
+}
+
 function evidenceDirFromOptions(options: Record<string, string | boolean>): string | undefined {
   const explicit = typeof options["evidence-dir"] === "string" ? options["evidence-dir"] : undefined;
   if (explicit) return resolve(explicit);
@@ -628,6 +644,7 @@ export function readAutomationResultEvidence(options: Record<string, string | bo
       path: resultPath,
       result: stringField(result, "status"),
       reason: stringField(result, "reason"),
+      duration_ms: numberField(result, "duration_ms"),
       started_at: stringField(result, "started_at"),
       started_at_local: stringField(result, "started_at_local"),
       finished_at: stringField(result, "finished_at"),
@@ -635,6 +652,9 @@ export function readAutomationResultEvidence(options: Record<string, string | bo
       url: stringField(result, "url"),
       prompt: redactSecrets(stringField(result, "prompt") ?? ""),
       expected_text: stringField(result, "expected_text"),
+      metrics_summary: objectField(result, "metrics_summary"),
+      thresholds_summary: objectField(result, "thresholds_summary"),
+      artifacts: objectField(result, "artifacts"),
     };
   } catch (error) {
     return { status: "invalid", path: resultPath, reason: String(error) };

skills/src/readiness.ts

@@ -114,6 +114,32 @@ export function automationEnvDefaults(item: StructuredItem, env: EnvSource = pro
     ["automation_expected_runner_id", "LANGBOT_E2E_EXPECTED_RUNNER_ID"],
     ["automation_reset_debug_chat", "LANGBOT_E2E_RESET_DEBUG_CHAT"],
     ["automation_debug_chat_session_type", "LANGBOT_E2E_DEBUG_CHAT_SESSION_TYPE"],
+    ["automation_debug_chat_response_p95_ms", "LANGBOT_E2E_DEBUG_CHAT_RESPONSE_P95_MS"],
+    ["automation_debug_chat_max_error_rate", "LANGBOT_E2E_DEBUG_CHAT_MAX_ERROR_RATE"],
+    ["automation_debug_chat_load_requests", "LANGBOT_DEBUG_CHAT_LOAD_REQUESTS"],
+    ["automation_debug_chat_load_concurrency", "LANGBOT_DEBUG_CHAT_LOAD_CONCURRENCY"],
+    ["automation_debug_chat_load_timeout_ms", "LANGBOT_DEBUG_CHAT_LOAD_TIMEOUT_MS"],
+    ["automation_debug_chat_load_response_p95_ms", "LANGBOT_DEBUG_CHAT_LOAD_RESPONSE_P95_MS"],
+    ["automation_debug_chat_load_first_response_p95_ms", "LANGBOT_DEBUG_CHAT_LOAD_FIRST_RESPONSE_P95_MS"],
+    ["automation_debug_chat_load_max_error_rate", "LANGBOT_DEBUG_CHAT_LOAD_MAX_ERROR_RATE"],
+    ["automation_debug_chat_load_min_error_rate", "LANGBOT_DEBUG_CHAT_LOAD_MIN_ERROR_RATE"],
+    ["automation_debug_chat_load_min_error_count", "LANGBOT_DEBUG_CHAT_LOAD_MIN_ERROR_COUNT"],
+    ["automation_debug_chat_load_min_ok_count", "LANGBOT_DEBUG_CHAT_LOAD_MIN_OK_COUNT"],
+    ["automation_debug_chat_load_min_provider_fault_count", "LANGBOT_DEBUG_CHAT_LOAD_MIN_PROVIDER_FAULT_COUNT"],
+    ["automation_debug_chat_load_expected_prefix", "LANGBOT_DEBUG_CHAT_LOAD_EXPECTED_PREFIX"],
+    ["automation_debug_chat_load_prompt_template", "LANGBOT_DEBUG_CHAT_LOAD_PROMPT_TEMPLATE"],
+    ["automation_debug_chat_load_stream", "LANGBOT_DEBUG_CHAT_LOAD_STREAM"],
+    ["automation_debug_chat_load_reset", "LANGBOT_DEBUG_CHAT_LOAD_RESET"],
+    ["automation_debug_chat_load_fail_on_final_mismatch", "LANGBOT_DEBUG_CHAT_LOAD_FAIL_ON_FINAL_MISMATCH"],
+    ["automation_fake_provider_response_text", "LANGBOT_FAKE_PROVIDER_RESPONSE_TEXT"],
+    ["automation_fake_provider_first_token_delay_ms", "LANGBOT_FAKE_PROVIDER_FIRST_TOKEN_DELAY_MS"],
+    ["automation_fake_provider_chunk_delay_ms", "LANGBOT_FAKE_PROVIDER_CHUNK_DELAY_MS"],
+    ["automation_fake_provider_chunk_count", "LANGBOT_FAKE_PROVIDER_CHUNK_COUNT"],
+    ["automation_fake_provider_fail_first_n", "LANGBOT_FAKE_PROVIDER_FAIL_FIRST_N"],
+    ["automation_fake_provider_fail_every_n", "LANGBOT_FAKE_PROVIDER_FAIL_EVERY_N"],
+    ["automation_fake_provider_fault_status", "LANGBOT_FAKE_PROVIDER_FAULT_STATUS"],
+    ["automation_fake_provider_fail_after_first_chunk", "LANGBOT_FAKE_PROVIDER_FAIL_AFTER_FIRST_CHUNK"],
+    ["automation_fake_provider_dynamic_response", "LANGBOT_FAKE_PROVIDER_DYNAMIC_RESPONSE"],
     ["automation_filesystem_checks_json", "LANGBOT_E2E_FILESYSTEM_CHECKS_JSON"],
     ["automation_plugin_package", "LANGBOT_E2E_PLUGIN_PACKAGE"],
     ["automation_expected_plugin_id", "LANGBOT_E2E_EXPECTED_PLUGIN_ID"],

skills/test/lbs-cli.test.ts

@@ -1,6 +1,6 @@
 import assert from "node:assert/strict";
 import { test } from "node:test";
-import { appendFileSync, existsSync, mkdtempSync, mkdirSync, readFileSync, rmSync, writeFileSync } from "node:fs";
+import { appendFileSync, chmodSync, existsSync, mkdtempSync, mkdirSync, readFileSync, rmSync, writeFileSync } from "node:fs";
 import { spawnSync } from "node:child_process";
 import { tmpdir } from "node:os";
 import { join } from "node:path";
@@ -676,6 +676,82 @@ test("suite run JSON captures failed case output", () => {
   }
 });
 
+test("suite run preserves classified env_issue automation results", () => {
+  const tmp = mkdtempSync(join(tmpdir(), "lbs-suite-run-env-issue-"));
+  try {
+    const skillDir = join(tmp, "skills", "langbot-testing");
+    const casesDir = join(skillDir, "cases");
+    const suitesDir = join(skillDir, "suites");
+    const scriptsDir = join(tmp, "scripts");
+    mkdirSync(casesDir, { recursive: true });
+    mkdirSync(suitesDir, { recursive: true });
+    mkdirSync(scriptsDir, { recursive: true });
+    writeFileSync(join(skillDir, "SKILL.md"), "---\nname: langbot-testing\ndescription: Testing.\n---\n\n# Testing\n");
+    writeFileSync(join(tmp, "skills", ".env"), "");
+    writeFileSync(
+      join(casesDir, "env-case.yaml"),
+      [
+        "id: env-case",
+        "title: Env Case",
+        "mode: probe",
+        "area: qa",
+        "type: smoke",
+        "priority: p2",
+        "risk: low",
+        "ci_eligible: true",
+        "automation: scripts/env-issue.mjs",
+        "evidence_required:",
+        "  - filesystem",
+      ].join("\n"),
+    );
+    writeFileSync(
+      join(suitesDir, "mini.yaml"),
+      [
+        "id: mini",
+        "title: Mini",
+        "description: Mini suite.",
+        "type: smoke",
+        "priority: p2",
+        "tags:",
+        "  - qa",
+        "cases:",
+        "  - env-case",
+      ].join("\n"),
+    );
+    writeFileSync(
+      join(scriptsDir, "env-issue.mjs"),
+      [
+        "import { mkdirSync, writeFileSync } from 'node:fs';",
+        "import { join } from 'node:path';",
+        "mkdirSync(process.env.LBS_EVIDENCE_DIR, { recursive: true });",
+        "const result = {",
+        "  case_id: process.env.LBS_CASE_ID,",
+        "  run_id: process.env.LBS_RUN_ID,",
+        "  status: 'env_issue',",
+        "  reason: 'backend not reachable',",
+        "  evidence_collected: ['filesystem']",
+        "};",
+        "writeFileSync(join(process.env.LBS_EVIDENCE_DIR, 'result.json'), JSON.stringify(result));",
+        "writeFileSync(join(process.env.LBS_EVIDENCE_DIR, 'automation-result.json'), JSON.stringify({ ...result, source: 'automation' }));",
+        "process.exit(2);",
+      ].join("\n"),
+    );
+
+    const result = capture(() => commandSuiteRun({
+      root: tmp,
+      args: ["suite", "run", "mini", "--run-id", "mini-run", "--evidence-dir", join(tmp, "evidence"), "--json"],
+    }));
+
+    assert.equal(result.code, 2);
+    const payload = JSON.parse(result.output);
+    assert.equal(payload.executions[0].status, "classified");
+    assert.equal(payload.report.status, "env_issue");
+    assert.equal(payload.report.execution_status, "ok");
+  } finally {
+    rmSync(tmp, { recursive: true, force: true });
+  }
+});
+
 test("suite run failure cannot be masked by stale pass result", () => {
   const tmp = mkdtempSync(join(tmpdir(), "lbs-suite-run-stale-pass-"));
   try {
@@ -1369,6 +1445,56 @@ test("env doctor does not require proxy variables", async () => {
   }
 });
 
+test("env doctor reports missing socksio for active SOCKS proxy", async () => {
+  const tmp = mkdtempSync(join(tmpdir(), "lbs-env-doctor-socksio-"));
+  const originalAllProxy = process.env.ALL_PROXY;
+  const originalAllProxyLower = process.env.all_proxy;
+  try {
+    delete process.env.ALL_PROXY;
+    delete process.env.all_proxy;
+    const skillsDir = join(tmp, "skills");
+    const repoDir = join(tmp, "LangBot");
+    const webDir = join(repoDir, "web");
+    const venvBin = join(repoDir, ".venv", "bin");
+    const browserProfile = join(tmp, "browser-profile");
+    const chromium = join(tmp, "chromium");
+    mkdirSync(skillsDir, { recursive: true });
+    mkdirSync(webDir, { recursive: true });
+    mkdirSync(venvBin, { recursive: true });
+    mkdirSync(browserProfile, { recursive: true });
+    writeFileSync(chromium, "");
+    const python = join(venvBin, "python");
+    writeFileSync(python, "#!/bin/sh\nexit 1\n");
+    chmodSync(python, 0o755);
+    writeFileSync(
+      join(skillsDir, ".env"),
+      [
+        "LANGBOT_BACKEND_URL=http://127.0.0.1:59996",
+        "LANGBOT_FRONTEND_URL=http://127.0.0.1:59996",
+        "LANGBOT_DEV_FRONTEND_URL=http://127.0.0.1:59996",
+        `LANGBOT_REPO=${repoDir}`,
+        `LANGBOT_WEB_REPO=${webDir}`,
+        `LANGBOT_BROWSER_PROFILE=${browserProfile}`,
+        `LANGBOT_CHROMIUM_EXECUTABLE=${chromium}`,
+        "ALL_PROXY=socks5://127.0.0.1:7890",
+      ].join("\n"),
+    );
+
+    const result = await captureAsync(() => commandEnvDoctor({ root: tmp, args: ["env", "doctor"] }));
+
+    assert.equal(result.code, 1);
+    assert.match(result.output, /FAIL: SOCKS proxy ALL_PROXY is configured/);
+    assert.match(result.output, /cannot import socksio/);
+    assert.match(result.output, /-m pip install socksio/);
+  } finally {
+    if (originalAllProxy === undefined) delete process.env.ALL_PROXY;
+    else process.env.ALL_PROXY = originalAllProxy;
+    if (originalAllProxyLower === undefined) delete process.env.all_proxy;
+    else process.env.all_proxy = originalAllProxyLower;
+    rmSync(tmp, { recursive: true, force: true });
+  }
+});
+
 test("env show redacts secret-like values by default", () => {
   const tmp = mkdtempSync(join(tmpdir(), "lbs-env-show-redact-"));
   try {
@@ -2521,6 +2647,38 @@ test("test report renders a reusable evidence template", () => {
   assert.match(result.output, /no log files provided/);
 });
 
+test("test report promotes loaded automation evidence into result section", () => {
+  const tmp = mkdtempSync(join(tmpdir(), "lbs-report-automation-"));
+  try {
+    writeFileSync(
+      join(tmp, "automation-result.json"),
+      JSON.stringify({
+        status: "pass",
+        reason: "latency thresholds passed",
+        url: "http://127.0.0.1:5300",
+        artifacts: { metrics_json: join(tmp, "metrics.json") },
+      }),
+    );
+
+    const result = capture(() => commandTestReport(ctx([
+      "test",
+      "report",
+      "langbot-live-backend-latency",
+      "--evidence-dir",
+      tmp,
+      "--no-auto-log",
+    ])));
+
+    assert.equal(result.code, 0);
+    assert.match(result.output, /## Result\n- result: pass\n- reason: latency thresholds passed/);
+    assert.match(result.output, /- target_tested: http:\/\/127\.0\.0\.1:5300/);
+    assert.doesNotMatch(result.output, /target_tested: TODO/);
+    assert.match(result.output, /## Automation Result/);
+  } finally {
+    rmSync(tmp, { recursive: true, force: true });
+  }
+});
+
 test("validate rejects dangling case references and missing automation scripts", () => {
   const tmp = mkdtempSync(join(tmpdir(), "lbs-validate-strict-"));
   try {

src/langbot/pkg/api/http/controller/groups/box.py

@@ -1,6 +1,9 @@
 from __future__ import annotations
 
+from langbot.pkg.utils import constants
+
 from .. import group
+from .box_visibility import should_hide_box_runtime_status
 
 
 @group.group_class('box', '/api/v1/box')
@@ -9,6 +12,7 @@ class BoxRouterGroup(group.RouterGroup):
         @self.route('/status', methods=['GET'], auth_type=group.AuthType.USER_TOKEN)
         async def _() -> str:
             status = await self.ap.box_service.get_status()
+            status['hidden'] = should_hide_box_runtime_status(constants.edition, status.get('enabled'))
             return self.success(data=status)
 
         @self.route('/sessions', methods=['GET'], auth_type=group.AuthType.USER_TOKEN)

src/langbot/pkg/api/http/controller/groups/box_visibility.py

@@ -0,0 +1,5 @@
+from __future__ import annotations
+
+
+def should_hide_box_runtime_status(edition: str, box_enabled: bool | None) -> bool:
+    return edition == 'cloud' and box_enabled is False

src/langbot/pkg/api/http/controller/groups/monitoring.py

@@ -138,6 +138,39 @@ class MonitoringRouterGroup(group.RouterGroup):
                 }
             )
 
+        @self.route('/tool-calls', methods=['GET'], auth_type=group.AuthType.USER_TOKEN)
+        async def get_tool_calls() -> str:
+            """Get tool call records"""
+            bot_ids = quart.request.args.getlist('botId')
+            pipeline_ids = quart.request.args.getlist('pipelineId')
+            session_ids = quart.request.args.getlist('sessionId')
+            start_time_str = quart.request.args.get('startTime')
+            end_time_str = quart.request.args.get('endTime')
+            limit = int(quart.request.args.get('limit', 100))
+            offset = int(quart.request.args.get('offset', 0))
+
+            start_time = parse_iso_datetime(start_time_str)
+            end_time = parse_iso_datetime(end_time_str)
+
+            tool_calls, total = await self.ap.monitoring_service.get_tool_calls(
+                bot_ids=bot_ids if bot_ids else None,
+                pipeline_ids=pipeline_ids if pipeline_ids else None,
+                session_ids=session_ids if session_ids else None,
+                start_time=start_time,
+                end_time=end_time,
+                limit=limit,
+                offset=offset,
+            )
+
+            return self.success(
+                data={
+                    'tool_calls': tool_calls,
+                    'total': total,
+                    'limit': limit,
+                    'offset': offset,
+                }
+            )
+
         @self.route('/embedding-calls', methods=['GET'], auth_type=group.AuthType.USER_TOKEN)
         async def get_embedding_calls() -> str:
             """Get embedding call records"""
@@ -284,6 +317,16 @@ class MonitoringRouterGroup(group.RouterGroup):
                 offset=0,
             )
 
+            # Get tool calls
+            tool_calls, tool_calls_total = await self.ap.monitoring_service.get_tool_calls(
+                bot_ids=bot_ids if bot_ids else None,
+                pipeline_ids=pipeline_ids if pipeline_ids else None,
+                start_time=start_time,
+                end_time=end_time,
+                limit=limit,
+                offset=0,
+            )
+
             # Get sessions
             sessions, sessions_total = await self.ap.monitoring_service.get_sessions(
                 bot_ids=bot_ids if bot_ids else None,
@@ -318,12 +361,14 @@ class MonitoringRouterGroup(group.RouterGroup):
                     'overview': overview,
                     'messages': messages,
                     'llmCalls': llm_calls,
+                    'toolCalls': tool_calls,
                     'embeddingCalls': embedding_calls,
                     'sessions': sessions,
                     'errors': errors,
                     'totalCount': {
                         'messages': messages_total,
                         'llmCalls': llm_calls_total,
+                        'toolCalls': tool_calls_total,
                         'embeddingCalls': embedding_calls_total,
                         'sessions': sessions_total,
                         'errors': errors_total,

src/langbot/pkg/api/http/controller/groups/pipelines/pipelines.py

@@ -86,6 +86,10 @@ class PipelinesRouterGroup(group.RouterGroup):
                         'available_plugins': plugins,
                         'bound_mcp_servers': extensions_prefs.get('mcp_servers', []),
                         'available_mcp_servers': mcp_servers,
+                        'bound_mcp_resources': extensions_prefs.get('mcp_resources', []),
+                        'mcp_resource_agent_read_enabled': extensions_prefs.get(
+                            'mcp_resource_agent_read_enabled', True
+                        ),
                         'bound_skills': extensions_prefs.get('skills', []),
                         'available_skills': available_skills,
                     }
@@ -99,6 +103,8 @@ class PipelinesRouterGroup(group.RouterGroup):
                 bound_plugins = json_data.get('bound_plugins', [])
                 bound_mcp_servers = json_data.get('bound_mcp_servers', [])
                 bound_skills = json_data.get('bound_skills', [])
+                bound_mcp_resources = json_data.get('bound_mcp_resources')
+                mcp_resource_agent_read_enabled = json_data.get('mcp_resource_agent_read_enabled')
 
                 await self.ap.pipeline_service.update_pipeline_extensions(
                     pipeline_uuid,
@@ -108,6 +114,8 @@ class PipelinesRouterGroup(group.RouterGroup):
                     enable_all_mcp_servers,
                     bound_skills=bound_skills,
                     enable_all_skills=enable_all_skills,
+                    bound_mcp_resources=bound_mcp_resources,
+                    mcp_resource_agent_read_enabled=mcp_resource_agent_read_enabled,
                 )
 
                 return self.success()

src/langbot/pkg/api/http/controller/groups/platform/bots.py

@@ -18,7 +18,6 @@ class BotsRouterGroup(group.RouterGroup):
         @self.route('/<bot_uuid>', methods=['GET', 'PUT', 'DELETE'], auth_type=group.AuthType.USER_TOKEN_OR_API_KEY)
         async def _(bot_uuid: str) -> str:
             if quart.request.method == 'GET':
-                # 返回运行时信息，包括webhook地址等
                 bot = await self.ap.bot_service.get_runtime_bot_info(bot_uuid)
                 if bot is None:
                     return self.http_status(404, -1, 'bot not found')
@@ -37,30 +36,21 @@ class BotsRouterGroup(group.RouterGroup):
             from_index = json_data.get('from_index', -1)
             max_count = json_data.get('max_count', 10)
             logs, total_count = await self.ap.bot_service.list_event_logs(bot_uuid, from_index, max_count)
-            return self.success(
+            return self.success(data={'logs': logs, 'total_count': total_count})
-                data={
-                    'logs': logs,
-                    'total_count': total_count,
-                }
-            )
 
         @self.route('/<bot_uuid>/send_message', methods=['POST'], auth_type=group.AuthType.API_KEY)
         async def _(bot_uuid: str) -> str:
-            """Send message to a specific target via bot"""
             json_data = await quart.request.json
             target_type = json_data.get('target_type')
             target_id = json_data.get('target_id')
             message_chain_data = json_data.get('message_chain')
 
-            # Validate required fields
             if not target_type:
                 return self.http_status(400, -1, 'target_type is required')
             if not target_id:
                 return self.http_status(400, -1, 'target_id is required')
             if not message_chain_data:
                 return self.http_status(400, -1, 'message_chain is required')
-
-            # Validate target_type
             if target_type not in ['person', 'group']:
                 return self.http_status(400, -1, 'target_type must be either "person" or "group"')
 
@@ -72,3 +62,29 @@ class BotsRouterGroup(group.RouterGroup):
 
                 traceback.print_exc()
                 return self.http_status(500, -1, f'Failed to send message: {str(e)}')
+
+        # ============ Bot Admins ============
+
+        @self.route('/<bot_uuid>/admins', methods=['GET', 'POST'], auth_type=group.AuthType.USER_TOKEN_OR_API_KEY)
+        async def _(bot_uuid: str) -> str:
+            if quart.request.method == 'GET':
+                admins = await self.ap.bot_service.get_bot_admins(bot_uuid)
+                return self.success(data={'admins': admins})
+            elif quart.request.method == 'POST':
+                json_data = await quart.request.json
+                launcher_type = json_data.get('launcher_type', '').strip()
+                launcher_id = str(json_data.get('launcher_id', '')).strip()
+                if not launcher_type or not launcher_id:
+                    return self.http_status(400, -1, 'launcher_type and launcher_id are required')
+                try:
+                    admin_id = await self.ap.bot_service.add_bot_admin(bot_uuid, launcher_type, launcher_id)
+                    return self.success(data={'id': admin_id})
+                except Exception as e:
+                    return self.http_status(409, -1, str(e))
+
+        @self.route(
+            '/<bot_uuid>/admins/<int:admin_id>', methods=['DELETE'], auth_type=group.AuthType.USER_TOKEN_OR_API_KEY
+        )
+        async def _(bot_uuid: str, admin_id: int) -> str:
+            await self.ap.bot_service.delete_bot_admin(bot_uuid, admin_id)
+            return self.success()

src/langbot/pkg/api/http/controller/groups/resources/mcp.py

@@ -2,6 +2,7 @@ from __future__ import annotations
 
 import quart
 import traceback
+from urllib.parse import unquote
 
 
 from ... import group
@@ -28,11 +29,11 @@ class MCPRouterGroup(group.RouterGroup):
                     traceback.print_exc()
                     return self.http_status(500, -1, f'Failed to create MCP server: {str(e)}')
 
-        @self.route('/servers/<server_name>', methods=['GET', 'PUT', 'DELETE'], auth_type=group.AuthType.USER_TOKEN)
+        @self.route(
+            '/servers/<path:server_name>', methods=['GET', 'PUT', 'DELETE'], auth_type=group.AuthType.USER_TOKEN
+        )
         async def _(server_name: str) -> str:
             """获取、更新或删除MCP服务器配置"""
-            from urllib.parse import unquote
-
             server_name = unquote(server_name)
 
             server_data = await self.ap.mcp_service.get_mcp_server_by_name(server_name)
@@ -57,12 +58,72 @@ class MCPRouterGroup(group.RouterGroup):
                 except Exception as e:
                     return self.http_status(500, -1, f'Failed to delete MCP server: {str(e)}')
 
-        @self.route('/servers/<server_name>/test', methods=['POST'], auth_type=group.AuthType.USER_TOKEN)
+        @self.route('/servers/<path:server_name>/test', methods=['POST'], auth_type=group.AuthType.USER_TOKEN)
         async def _(server_name: str) -> str:
             """测试MCP服务器连接"""
-            from urllib.parse import unquote
-
             server_name = unquote(server_name)
             server_data = await quart.request.json
             task_id = await self.ap.mcp_service.test_mcp_server(server_name=server_name, server_data=server_data)
             return self.success(data={'task_id': task_id})
+
+        @self.route('/servers/<path:server_name>/resources', methods=['GET'], auth_type=group.AuthType.USER_TOKEN)
+        async def _(server_name: str) -> str:
+            """Get resources from an MCP server"""
+            server_name = unquote(server_name)
+            try:
+                resources = await self.ap.mcp_service.get_mcp_server_resources(server_name)
+                templates = await self.ap.mcp_service.get_mcp_server_resource_templates(server_name)
+                runtime_info = await self.ap.mcp_service.get_runtime_info(server_name)
+                return self.success(
+                    data={
+                        'resources': resources,
+                        'resource_templates': templates,
+                        'resource_capabilities': (runtime_info or {}).get('resource_capabilities', {}),
+                    }
+                )
+            except Exception as e:
+                return self.http_status(500, -1, f'Failed to get resources: {str(e)}')
+
+        @self.route(
+            '/servers/<path:server_name>/resource-templates', methods=['GET'], auth_type=group.AuthType.USER_TOKEN
+        )
+        async def _(server_name: str) -> str:
+            """Get resource templates from an MCP server"""
+            server_name = unquote(server_name)
+            try:
+                templates = await self.ap.mcp_service.get_mcp_server_resource_templates(server_name)
+                return self.success(data={'resource_templates': templates})
+            except Exception as e:
+                return self.http_status(500, -1, f'Failed to get resource templates: {str(e)}')
+
+        @self.route('/servers/<path:server_name>/logs', methods=['GET'], auth_type=group.AuthType.USER_TOKEN)
+        async def _(server_name: str) -> str:
+            """Get logs from an MCP server"""
+            server_name = unquote(server_name)
+            try:
+                limit = int(quart.request.args.get('limit', 200))
+            except (TypeError, ValueError):
+                limit = 200
+            limit = min(limit, 500)
+            level = quart.request.args.get('level') or None
+            logs = await self.ap.mcp_service.get_mcp_server_logs(server_name, limit=limit, level=level)
+            return self.success(data={'logs': logs})
+
+        @self.route('/servers/<path:server_name>/resources/read', methods=['POST'], auth_type=group.AuthType.USER_TOKEN)
+        async def _(server_name: str) -> str:
+            """Read a resource from an MCP server"""
+            server_name = unquote(server_name)
+            data = await quart.request.json
+            uri = data.get('uri')
+            if not uri:
+                return self.http_status(400, -1, 'URI is required')
+            try:
+                envelope = await self.ap.mcp_service.read_mcp_server_resource_envelope(
+                    server_name,
+                    uri,
+                    max_bytes=data.get('max_bytes'),
+                    include_blob=bool(data.get('include_blob', False)),
+                )
+                return self.success(data=envelope)
+            except Exception as e:
+                return self.http_status(500, -1, f'Failed to read resource: {str(e)}')

src/langbot/pkg/api/http/controller/groups/resources/tools.py

@@ -1,5 +1,7 @@
 from __future__ import annotations
 
+import quart
+
 from ... import group
 
 
@@ -9,25 +11,41 @@ class ToolsRouterGroup(group.RouterGroup):
         @self.route('', methods=['GET'], auth_type=group.AuthType.USER_TOKEN)
         async def _() -> str:
             """获取所有可用工具列表"""
-            tools = await self.ap.tool_mgr.get_all_tools()
+            pipeline_uuid = quart.request.args.get('pipeline_uuid') or quart.request.args.get('pipeline_id')
+            bound_plugins: list[str] | None = None
+            bound_mcp_servers: list[str] | None = None
 
-            tool_list = []
+            if pipeline_uuid:
-            for tool in tools:
+                pipeline = await self.ap.pipeline_service.get_pipeline(pipeline_uuid)
-                tool_list.append(
+                if pipeline is None:
-                    {
+                    return self.http_status(404, -1, 'pipeline not found')
-                        'name': tool.name,
+
-                        'description': tool.description,
+                extensions_prefs = pipeline.get('extensions_preferences', {}) or {}
-                        'human_desc': tool.human_desc,
+                if not extensions_prefs.get('enable_all_plugins', True):
-                        'parameters': tool.parameters,
+                    bound_plugins = [
+                        f'{plugin.get("author", "")}/{plugin.get("name", "")}'
+                        for plugin in extensions_prefs.get('plugins', [])
+                        if isinstance(plugin, dict) and plugin.get('name')
+                    ]
+                if not extensions_prefs.get('enable_all_mcp_servers', True):
+                    bound_mcp_servers = [
+                        server for server in (extensions_prefs.get('mcp_servers', []) or []) if isinstance(server, str)
+                    ]
+
+            return self.success(
+                data={
+                    'tools': await self.ap.tool_mgr.get_tool_catalog(
+                        bound_plugins,
+                        bound_mcp_servers,
+                        include_skill_authoring=True,
+                    )
                 }
             )
 
-            return self.success(data={'tools': tool_list})
-
         @self.route('/<tool_name>', methods=['GET'], auth_type=group.AuthType.USER_TOKEN)
         async def _(tool_name: str) -> str:
             """获取特定工具详情"""
-            tools = await self.ap.tool_mgr.get_all_tools()
+            tools = await self.ap.tool_mgr.get_all_tools(include_skill_authoring=True)
 
             for tool in tools:
                 if tool.name == tool_name:

src/langbot/pkg/api/http/controller/groups/survey.py

@@ -1,3 +1,5 @@
+import base64
+
 import quart
 
 from .. import group
@@ -30,6 +32,50 @@ class SurveyRouterGroup(group.RouterGroup):
                 return self.fail(2, 'Failed to submit response')
             return self.fail(3, 'Survey not available')
 
+        @self.route('/feedback', methods=['POST'], auth_type=group.AuthType.USER_TOKEN)
+        async def _feedback(user_email: str) -> str:
+            """Submit on-demand user feedback from the sidebar."""
+            json_data = await quart.request.get_json(silent=True) or {}
+            content = str(json_data.get('content', '')).strip()
+            attachments = json_data.get('attachments', [])
+
+            if not content:
+                return self.fail(1, 'content required')
+            if len(content) > 5000:
+                return self.fail(2, 'content too long')
+            if not isinstance(attachments, list):
+                return self.fail(3, 'attachments must be an array')
+            if len(attachments) > 3:
+                return self.fail(4, 'too many attachments')
+
+            normalized_attachments = []
+            for item in attachments:
+                if not isinstance(item, dict):
+                    continue
+                data_url = str(item.get('data_url', ''))
+                mime_type = str(item.get('mime_type', ''))[:128]
+                name = str(item.get('name', ''))[:255]
+                if not data_url.startswith('data:image/'):
+                    continue
+                try:
+                    payload = data_url.split(',', 1)[1]
+                    if len(base64.b64decode(payload, validate=True)) > 1024 * 1024:
+                        return self.fail(5, 'attachment too large')
+                except Exception:
+                    return self.fail(5, 'attachment too large')
+                normalized_attachments.append({'name': name, 'mime_type': mime_type, 'data_url': data_url})
+
+            if self.ap.survey:
+                ok = await self.ap.survey.submit_feedback(
+                    content=content,
+                    attachments=normalized_attachments,
+                    user_email=user_email,
+                )
+                if ok:
+                    return self.success()
+                return self.fail(6, 'Failed to submit feedback')
+            return self.fail(7, 'Survey not available')
+
         @self.route('/dismiss', methods=['POST'], auth_type=group.AuthType.USER_TOKEN)
         async def _dismiss() -> str:
             """Dismiss survey."""

src/langbot/pkg/api/http/controller/groups/user.py

@@ -195,6 +195,13 @@ class UserRouterGroup(group.RouterGroup):
         @self.route('/set-password', methods=['POST'], auth_type=group.AuthType.USER_TOKEN)
         async def _(user_email: str) -> str:
             """Set password for Space account (first time) or change password"""
+            # Check if modifying login info is allowed
+            allow_modify_login_info = self.ap.instance_config.data.get('system', {}).get(
+                'allow_modify_login_info', True
+            )
+            if not allow_modify_login_info:
+                return self.http_status(403, -1, 'Modifying login info is disabled')
+
             json_data = await quart.request.json
             new_password = json_data.get('new_password')
             current_password = json_data.get('current_password')

src/langbot/pkg/api/http/service/bot.py

@@ -199,3 +199,35 @@ class BotService:
 
         # Send message via adapter
         await runtime_bot.adapter.send_message(target_type, str(target_id), message_chain)
+
+    # ============ Bot Admins ============
+
+    async def get_bot_admins(self, bot_uuid: str) -> list[dict]:
+        from ....entity.persistence import bot as persistence_bot
+
+        result = await self.ap.persistence_mgr.execute_async(
+            sqlalchemy.select(persistence_bot.BotAdmin).where(persistence_bot.BotAdmin.bot_uuid == bot_uuid)
+        )
+        return [{'id': r.id, 'launcher_type': r.launcher_type, 'launcher_id': r.launcher_id} for r in result.all()]
+
+    async def add_bot_admin(self, bot_uuid: str, launcher_type: str, launcher_id: str) -> int:
+        from ....entity.persistence import bot as persistence_bot
+
+        result = await self.ap.persistence_mgr.execute_async(
+            sqlalchemy.insert(persistence_bot.BotAdmin).values(
+                bot_uuid=bot_uuid,
+                launcher_type=launcher_type,
+                launcher_id=launcher_id,
+            )
+        )
+        return result.inserted_primary_key[0]
+
+    async def delete_bot_admin(self, bot_uuid: str, admin_id: int) -> None:
+        from ....entity.persistence import bot as persistence_bot
+
+        await self.ap.persistence_mgr.execute_async(
+            sqlalchemy.delete(persistence_bot.BotAdmin).where(
+                persistence_bot.BotAdmin.bot_uuid == bot_uuid,
+                persistence_bot.BotAdmin.id == admin_id,
+            )
+        )

src/langbot/pkg/api/http/service/maintenance.py

@@ -243,6 +243,7 @@ class MaintenanceService:
         tables = {
             'messages': persistence_monitoring.MonitoringMessage.id,
             'llm_calls': persistence_monitoring.MonitoringLLMCall.id,
+            'tool_calls': persistence_monitoring.MonitoringToolCall.id,
             'embedding_calls': persistence_monitoring.MonitoringEmbeddingCall.id,
             'errors': persistence_monitoring.MonitoringError.id,
             'sessions': persistence_monitoring.MonitoringSession.session_id,

src/langbot/pkg/api/http/service/mcp.py

@@ -48,6 +48,17 @@ class MCPService:
             if total_extensions >= max_extensions:
                 raise ValueError(f'Maximum number of extensions ({max_extensions}) reached')
 
+        server_name = str(server_data.get('name') or '').strip()
+        if not server_name:
+            raise ValueError('MCP server name is required')
+        server_data['name'] = server_name
+
+        existing_result = await self.ap.persistence_mgr.execute_async(
+            sqlalchemy.select(persistence_mcp.MCPServer).where(persistence_mcp.MCPServer.name == server_name)
+        )
+        if existing_result.first() is not None:
+            raise ValueError(f'MCP server already exists: {server_name}')
+
         server_data['uuid'] = str(uuid.uuid4())
         await self.ap.persistence_mgr.execute_async(sqlalchemy.insert(persistence_mcp.MCPServer).values(server_data))
 
@@ -136,6 +147,32 @@ class MCPService:
             if server_name in self.ap.tool_mgr.mcp_tool_loader.sessions:
                 await self.ap.tool_mgr.mcp_tool_loader.remove_mcp_server(server_name)
 
+    async def get_mcp_server_resources(self, server_name: str) -> list[dict]:
+        """Get resources from a specific MCP server."""
+        return await self.ap.tool_mgr.mcp_tool_loader.get_resources(server_name)
+
+    async def get_mcp_server_resource_templates(self, server_name: str) -> list[dict]:
+        """Get resource templates from a specific MCP server."""
+        return await self.ap.tool_mgr.mcp_tool_loader.get_resource_templates(server_name)
+
+    async def read_mcp_server_resource_envelope(
+        self,
+        server_name: str,
+        uri: str,
+        *,
+        max_bytes: int | None = None,
+        include_blob: bool = False,
+    ) -> dict:
+        """Read a resource from a specific MCP server with metadata."""
+        kwargs = {'include_blob': include_blob, 'source': 'ui_preview'}
+        if max_bytes is not None:
+            kwargs['max_bytes'] = max_bytes
+        return await self.ap.tool_mgr.mcp_tool_loader.read_resource_envelope(server_name, uri, **kwargs)
+
+    async def read_mcp_server_resource(self, server_name: str, uri: str) -> list[dict]:
+        """Read a resource from a specific MCP server."""
+        return await self.ap.tool_mgr.mcp_tool_loader.read_resource(server_name, uri)
+
     async def test_mcp_server(self, server_name: str, server_data: dict) -> int:
         """测试 MCP 服务器连接并返回任务 ID"""
 
@@ -151,10 +188,22 @@ class MCPService:
             persisted_session = runtime_mcp_session
 
             async def _refresh_and_report() -> None:
-                if persisted_session.status == MCPSessionStatus.ERROR:
+                # Testing a persisted server should REUSE its live shared-session
+                # process, not rebuild it. Try a lightweight refresh (a real
+                # list_tools probe over the existing connection) first; only fall
+                # back to a full start() when the session has no live connection
+                # to probe (never connected, or the process is actually gone).
+                needs_start = persisted_session.status == MCPSessionStatus.ERROR or persisted_session.session is None
+                if needs_start:
                     await persisted_session.start()
                 else:
+                    try:
                         await persisted_session.refresh()
+                    except Exception:
+                        # The live connection was stale/dropped: reconnect once
+                        # (reusing the live managed process where possible) and
+                        # re-probe, instead of reporting a false failure.
+                        await persisted_session.start()
                 # Surface the discovered tools so the config page can render them
                 # even for an already-hosted server.
                 ctx.metadata['runtime_info'] = persisted_session.get_runtime_info_dict()
@@ -195,3 +244,19 @@ class MCPService:
             context=ctx,
         )
         return wrapper.id
+
+    async def get_mcp_server_logs(self, server_name: str, limit: int = 200, level: str | None = None) -> list[dict]:
+        """Get recent log lines captured from the MCP server's stderr."""
+        session = self.ap.tool_mgr.mcp_tool_loader.get_session(server_name)
+        if not session:
+            return []
+
+        # Get logs from the session's buffer
+        logs = list(session._log_buffer)
+
+        # Filter by level if specified
+        if level:
+            logs = [log for log in logs if log.get('level') == level]
+
+        # Return the most recent 'limit' logs
+        return logs[-limit:]