Files
LangBot/skills/skills/langbot-testing/cases/agent-runner-qa-debug-chat.yaml
T
Junyan Chin e9dd584792 feat: MCP server + in-repo skills (agent-friendly platform) (#2269)
* feat(api): support global API key from config.yaml (api.global_api_key)

Accept a config-defined global API key anywhere a web-UI key is accepted
(X-API-Key / Bearer), with no login session and no DB record. Useful for
automated deployments and AI agents (HTTP API + MCP). Defaults to empty
(disabled); does not require the lbk_ prefix.

- templates/config.yaml: add api.global_api_key with security notes
- service/apikey.py: verify_api_key checks global key first (constant-time)
- docs/API_KEY_AUTH.md: document the global key + security guidance
- tests: cover global-key match, prefix-free, fallback-to-db, disabled

* feat(mcp): expose LangBot management as an MCP server at /mcp

Add an MCP (Model Context Protocol) server so external AI agents can manage a
LangBot instance. Reuses the same API-key auth as the HTTP API (including the
config.yaml global API key).

- pkg/api/mcp/server.py: FastMCP server wrapping the service layer; 21 curated
  tools across system/bots/pipelines/models/knowledge/mcp-servers/skills
- pkg/api/mcp/mount.py: ASGI dispatcher fronting Quart; authenticates /mcp
  requests with an API key, runs the streamable-HTTP session manager lifespan
- controller/main.py: serve the wrapped ASGI app via hypercorn (was run_task)
- web: new 'MCP' tab in the API integration dialog showing endpoint, auth, and
  client config; i18n for 8 locales
- tests/manual/mcp_smoke.py: e2e check (401 unauth, list tools, call tools)

Tool surface is intentionally curated (not all ~25 route groups) to keep the
agent surface small, safe, and maintainable. Extend deliberately.

* feat(skills): add in-repo skills/ as the single source of truth

Migrate the agent skills + QA/e2e test harness from the (now archived)
langbot-app/langbot-skills repo into LangBot/skills/, and add four new skills.

Migrated:
- langbot-plugin-dev, langbot-testing (e2e), langbot-env-setup,
  langbot-skills-maintenance, langbot-eba-adapter-dev
- the bin/lbs CLI (src/, test/, scripts/, schemas/, qa-agent-docs/)

New:
- langbot-dev      core backend + web development
- langbot-deploy   Docker/K8s deployment + config.yaml + global API key
- langbot-mcp-ops  operating the LangBot MCP server (/mcp)
- langbot-space-ops operating the Space marketplace MCP server

- src/cli.ts repoRoot(): recognize the skills assets root (skills.index.json +
  bin/lbs) so the CLI works when nested inside the LangBot repo
- README.md: unified skill catalog; skills.index.json regenerated

Parity with source verified: bin/lbs validate + node test suite match the
source repo (only the uncommitted .lbpkg build-artifact fixture differs).

* docs(agents): document agent-facing surfaces + API/MCP/skills sync rule

* docs(readme): add 'Built for AI Agents' section across all locales

Highlight MCP server, in-repo skills (single source of truth), AGENTS.md
sync rule, and llms.txt. Cross-link LangBot Space MCP marketplace.

* style(mcp): fix ruff format + prettier lint in MCP server and API panel

* style(web): prettier format MCP i18n locale entries

* docs(skills): note MCP instance control in dev/testing skills

All development-guidance skills now point to the LangBot instance MCP
server (/mcp) and the Space marketplace MCP server, reusing API keys.
2026-06-20 15:14:47 +08:00

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2.4 KiB
YAML

id: agent-runner-qa-debug-chat
title: "QA AgentRunner returns deterministic output through Debug Chat"
mode: agent-browser
area: pipeline
type: regression
priority: p0
risk: high
ci_eligible: false
tags:
- agent-runner
- pipeline
- debug-chat
- fixture
skills:
- langbot-env-setup
- langbot-testing
env:
- LANGBOT_FRONTEND_URL
- LANGBOT_BACKEND_URL
- LANGBOT_QA_AGENT_RUNNER_PIPELINE_URL
- LANGBOT_QA_AGENT_RUNNER_PIPELINE_NAME
automation: scripts/e2e/pipeline-debug-chat.mjs
automation_env:
- LANGBOT_FRONTEND_URL
- LANGBOT_BACKEND_URL
- LANGBOT_BROWSER_PROFILE
- LANGBOT_CHROMIUM_EXECUTABLE
- LANGBOT_QA_AGENT_RUNNER_PIPELINE_URL
- LANGBOT_QA_AGENT_RUNNER_PIPELINE_NAME
automation_pipeline_url_env: LANGBOT_QA_AGENT_RUNNER_PIPELINE_URL
automation_pipeline_name_env: LANGBOT_QA_AGENT_RUNNER_PIPELINE_NAME
automation_expected_runner_id: "plugin:qa/agent-runner/default"
automation_prompt: "hello-live"
automation_expected_text: "QA_AGENT_RUNNER_OK:hello-live"
automation_response_timeout_ms: "120000"
automation_reset_debug_chat: "1"
setup_automation:
- "case:agent-runner-live-install"
- "node:scripts/e2e/ensure-qa-agent-runner-pipeline.mjs --write-env"
setup_provides_env:
- LANGBOT_QA_AGENT_RUNNER_PIPELINE_URL
- LANGBOT_QA_AGENT_RUNNER_PIPELINE_NAME
steps:
- "Open LANGBOT_FRONTEND_URL."
- "Open the pipeline from LANGBOT_QA_AGENT_RUNNER_PIPELINE_URL or LANGBOT_QA_AGENT_RUNNER_PIPELINE_NAME."
- "Confirm the pipeline AI runner is plugin:qa/agent-runner/default."
- "Open Debug Chat."
- "Send: hello-live."
checks:
- "UI: The user message appears in Debug Chat."
- "UI: A Bot message appears and contains QA_AGENT_RUNNER_OK:hello-live."
- "API diagnostic: pipeline config uses plugin:qa/agent-runner/default."
- "Console: No unexpected frontend runtime errors appear during the send/receive path."
evidence_required:
- ui
- screenshot
- console
- network
- api_diagnostic
diagnostics:
- "This is the deterministic live execution proof that sits after fixture contract and live install."
- "If the runner id mismatch is reported, rerun ensure-qa-agent-runner-pipeline.mjs --write-env."
success_patterns:
- "QA_AGENT_RUNNER_OK:hello-live"
failure_patterns:
- "plugin:qa/agent-runner/default execution failed"
- "Action invoke_llm_stream call timed out"
- "Agent runner temporarily unavailable"
troubleshooting:
- plugin-runtime-timeout