| name | knowledge-base |
| description | Capture, organize, and retrieve operational knowledge + saved web content in a local `knowledge/` directory indexed by QMD. Use for “save this link”, “add to KB”, “remember this”, or “search KB”. |
| metadata | {"openclaw":{"emoji":"📚","requires":{"bins":["qmd"]}}} |
Knowledge Base
Two overlapping functions:
- Operational knowledge — tool quirks, API gotchas, runbooks, decision rationale
- URL/content archive — save articles, YouTube transcripts, PDFs, threads
Everything lives in knowledge/ and is indexed by QMD for fast keyword + semantic search.
Routing
- ✅ Use when the user says: “save this”, “add to KB”, “remember this”, “document this”, “search KB”.
- ❌ Don’t use for simple web-page extraction if the user just wants the answer now → use
web_fetch directly.
Quick start
1) Create the directory scaffold (recommended)
Copy templates into your OpenClaw workspace:
rsync -av templates/knowledge/ ~/.openclaw/workspace/knowledge/
2) Ingest a URL
From your workspace root:
python3 skills/knowledge-base/scripts/ingest.py "https://example.com/article"
python3 skills/knowledge-base/scripts/ingest.py "https://youtube.com/watch?v=..."
python3 skills/knowledge-base/scripts/ingest.py "https://example.com/file.pdf"
Optional metadata (skip LLM calls):
python3 skills/knowledge-base/scripts/ingest.py "<URL>" \
--title "Readable Title" \
--tags "rag,openclaw,workflows" \
--summary "Why this is worth saving"
3) Search
qmd search "meta ads" -c knowledge
qmd vsearch "how do we authenticate jira" -c knowledge
qmd query "slack block streaming" -c knowledge
Notes / Dependencies
- Works with no extra installs for basic HTML pages (urllib fallback).
- Better extraction if you install
trafilatura.
- YouTube transcripts: tries
youtube-transcript-api, falls back to yt-dlp if available.
- PDF text extraction: uses
pdftotext (Poppler).
Keep secrets out of the KB. For credentials, store them in a password manager / keychain and write where to find them, not the values.
