Knowledge Base

Knowledge Base

Two overlapping functions:

1. Operational knowledge — tool quirks, API gotchas, runbooks, decision rationale
2. 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

# keyword
qmd search "meta ads" -c knowledge

# semantic
qmd vsearch "how do we authenticate jira" -c knowledge

# best quality (hybrid + rerank, if enabled)
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.