feat(box): configurable sandbox scope and unified skill containers

Replace the per-message session_id with a template-based system
configurable per pipeline via 'Sandbox Scope' in the local-agent panel.
Default scope is per-chat ({launcher_type}_{launcher_id}).

Unify skill exec into the same container as default exec — skills are
mounted at /workspace/.skills/{name}/ via extra_mounts instead of
getting separate containers. All pipeline-bound skills are injected
at container creation time.

- Add box-session-id-template to pipeline metadata (select, 4 options, 8 languages)
- Add resolve_box_session_id() and build_skill_extra_mounts() to BoxService
- Rewrite native.py skill exec path to use execute_tool with shared session
- Update tests for new session_id format
- Add design doc: docs/review/box-session-scope.md

src/langbot/pkg/provider/tools/loaders/skill.py

@@ -1,6 +1,5 @@
 from __future__ import annotations
 
-import os
 import re
 import typing
 
@@ -14,6 +13,8 @@ ACTIVATED_SKILLS_KEY = '_activated_skills'
 PIPELINE_BOUND_SKILLS_KEY = '_pipeline_bound_skills'
 SKILL_MOUNT_PREFIX = '/workspace/.skills'
 _SKILL_MOUNT_PATTERN = re.compile(r'/workspace/\.skills/([A-Za-z0-9_-]+)')
+
+
 def get_virtual_skill_mount_path(skill_name: str) -> str:
     return f'{SKILL_MOUNT_PREFIX}/{skill_name}'
 
@@ -152,5 +153,5 @@ def should_prepare_skill_python_env(package_root: str | None) -> bool:
     return box_workspace.should_prepare_python_env(package_root)
 
 
-def wrap_skill_command_with_python_env(command: str) -> str:
-    return box_workspace.wrap_python_command_with_env(command).rstrip()
+def wrap_skill_command_with_python_env(command: str, *, mount_path: str = '/workspace') -> str:
+    return box_workspace.wrap_python_command_with_env(command, mount_path=mount_path).rstrip()