2.6 KiB
2.6 KiB
summary, read_when
| summary | read_when | ||||
|---|---|---|---|---|---|
| Search and retrieve TekDek knowledge base using qmd (BM25 + semantic search + reranking) |
|
QMD — TekDek Knowledge Base
qmd is our local search engine. It indexes all markdown docs in the workspace and knowledge base, and supports keyword, semantic, and hybrid search with reranking.
Collections
- workspace (
qmd://workspace/) — Core agent files: IDENTITY.md, MEMORY.md, SOUL.md, USER.md, daily logs, etc. - knowledge (
qmd://knowledge/) — TekDek KB: personas, projects, storylines, brands, operations
Knowledge Base Structure
/data/.openclaw/workspace/knowledge/
├── personas/ — One .md file per Coder persona
├── projects/ — One .md file per TekDek project
├── storyline/ — Storyline arcs, relationship dynamics
├── brands/ — Per-persona brand guides
└── operations/ — Processes, decisions, meeting notes
Search Commands
# Fast keyword search
qmd search "query"
# Semantic/vector search
qmd vsearch "query"
# Best quality: hybrid + reranking (use this for most queries)
qmd query "query"
# Search within a specific collection
qmd search "query" -c knowledge
qmd query "persona quirks" -c knowledge
# Get a specific file
qmd get "knowledge/personas/example.md"
# Export results for agent use
qmd query "topic" --json -n 10
qmd query "topic" --all --files --min-score 0.4
MCP Tools (available via MCP server)
query— Hybrid search with reranking (best quality)get— Retrieve document by path or docidmulti_get— Batch retrieve by glob or docidsstatus— Index health and collection info
Adding Knowledge
When new TekDek content is created (new persona, project, storyline beat, etc.), create a markdown file in the appropriate knowledge/ subdirectory, then re-index:
qmd collection sync workspace
qmd collection sync knowledge
# Then re-embed if needed:
qmd embed
Re-indexing
Run after adding/changing files:
qmd collection sync workspace && qmd collection sync knowledge
qmd embed # slow on CPU — only run when needed
Tips
qmd queryis best quality but slowest (uses LLM reranking)qmd searchis fast and good for known termsqmd vsearchis good for fuzzy/conceptual queries- Always check
qmd statusif results seem stale - The MCP server (
qmd mcp) can be used for tighter tool integration