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생산성 및 협업 · SKILL.md

persistence-rag-workspaces

persistence-rag-workspaces

Maintain LangBot persistence, Alembic migrations, Workspace tenancy, cloud directory state, RAG knowledge bases, vector backends, storage, monitoring, and telemetry workflows.

Independent GitHub snapshot · Automated classification · Original documentation governs

Skill 문서

GitHub

name: persistence-rag-workspaces description: "Maintain LangBot persistence, Alembic migrations, Workspace tenancy, cloud directory state, RAG knowledge bases, vector backends, storage, monitoring, and telemetry workflows." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

Persistence, RAG, Workspaces, and Monitoring

Use this sub-skill for database models, migrations, tenant scoping, Workspace collaboration, cloud directory/launch behavior, RAG/knowledge-base operations, vector backends, file storage, monitoring exports, and telemetry.

Read First

Hard Rules

  • New schema changes use Alembic under the current Alembic versions directory; do not add new legacy dbmXXX migrations.
  • Tenant services must accept a RequestContext or trusted execution context and fail closed when context is missing.
  • API keys are bound to one Workspace; do not let request headers switch an API key's tenant.
  • Vector/database service-backed tests are optional unless the task changes that backend; SQLite and unit tests cover the general path.

Focused Checks

python scripts/select_langbot_checks.py persistence-rag
uv run pytest tests/integration/persistence/test_migrations.py -q --tb=short
uv run pytest tests/unit_tests/vector/test_mgr.py tests/unit_tests/vector/test_vdb_filter_conversion.py -q --tb=short
uv run pytest tests/unit_tests/storage/test_storage_manager.py tests/unit_tests/rag/test_runtime_service.py -q --tb=short
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