| name | knowledgebase-search |
| description | Shared workflow for knowledgebase retrieval using docs_tools and injected OpenClaw context. |
Shared Knowledgebase Search Skill
When To Use
- You are not fully certain and need internal facts before responding.
- The task references runbooks/policies/procedures that may exist in team docs.
- Files were recently added to
agents/shared/knowledgebase.
Required Retrieval Path (OpenHands / Terminal-capable agents)
- Rebuild index after KB updates.
- Search with
search_docs (BM25 + fallback keyword scoring).
- Read source file with
get_doc_content.
- Cite file path + evidence snippet in your response.
uv run python - <<'PY'
from agent_service.shared.docs_tools import rebuild_index, search_docs
print(rebuild_index())
print(search_docs("<query>", max_results=5))
PY
uv run python - <<'PY'
from agent_service.shared.docs_tools import get_doc_content
print(get_doc_content("agents/shared/knowledgebase/<domain>/<file>.md"))
PY
OpenClaw Runtime Behavior
- OpenClaw agents do not call
docs_tools directly as an MCP function.
openclaw-svc injects this skill plus retrieved KB context into the task before execution.- If injected KB context is missing or insufficient, explicitly state that and request a KB update instead of guessing.
Guardrails
- Use indexed retrieval (
search_docs) as the canonical knowledge lookup path.
- Do not answer from memory when a KB lookup can verify the claim.
