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kb/SKILL.md
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2026-03-23 20:38:42 +00:00

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# kb-search skill
Search the user's personal knowledge base containing PDFs, markdown documents, code snippets, and text notes.
## When to use
- User asks a question that might be answered by their stored documents, notes, or code
- User explicitly says "check my notes", "search kb", "look in my knowledge base", "what do my docs say about..."
- User references documents or notes they've previously stored
- User asks "how do I..." style questions that their knowledge base likely covers
## Available commands
### Search (primary)
```bash
kb search "<query>" --top 10 --format json
```
Returns JSON with ranked results combining full-text and semantic search.
**Flags:**
- `--top N` — number of results (default: 10)
- `--tags tag1,tag2` — filter by tags (AND logic)
- `--type pdf|markdown|code|note` — filter by document type
- `--format json|human` — output format (always use json)
- `--fts-only` — keyword search only (skip semantic)
- `--vec-only` — semantic search only (skip keyword)
- `--threshold FLOAT` — minimum score cutoff
### Other useful commands
```bash
kb list --format json # List all documents
kb list --type pdf --format json # List only PDFs
kb tags --format json # List tags with counts
kb info <doc_id> --format json # Document details
kb status --format json # DB stats
```
## Output format (search)
```json
{
"query": "how to install git",
"results": [
{
"chunk_id": 1423,
"score": 0.031,
"score_breakdown": {"fts": 0.016, "vector": 0.015},
"text": "To install the latest version of git from source...",
"source": {
"document_id": 42,
"title": "Git Admin Guide",
"path": "/home/user/docs/git-admin.pdf",
"type": "pdf",
"page": 12,
"chunk_index": 3,
"total_chunks": 28,
"tags": ["git", "admin"]
}
}
],
"total_matches": 47,
"returned": 10
}
```
## How to answer
1. Run `kb search "<query>" --top 10 --format json`
2. Read the returned chunks
3. Synthesise a natural language answer from the top results
4. **ALWAYS cite sources**: "According to [title] (p.X)..." or "From [title], section [header]..."
5. If results have low scores (all below 0.01) or `returned: 0`, tell the user: "I couldn't find anything in your knowledge base about this"
6. If initial results seem off-target, try refining the query and searching again
## Multi-query strategy
For complex questions, search multiple times with different queries:
- Decompose the question into sub-queries
- Run each query separately
- Combine and deduplicate results across queries
- Synthesise a unified answer citing all relevant sources
Example:
```
User: "What's the difference between git rebase and merge?"
Query 1: kb search "git rebase explanation" --top 5 --format json
Query 2: kb search "git merge explanation" --top 5 --format json
Query 3: kb search "git rebase vs merge" --top 5 --format json
```
## Filtering
Use filters when the question implies a specific domain:
- Code question → `--type code`
- From a specific topic → `--tags <topic>`
- Check available tags first: `kb tags --format json`
## Important notes
- Always use `--format json` for machine parsing
- The `score` field is relative, not absolute — compare scores within a result set
- `source.page` is only present for PDF documents
- `source.section_header` is only present for markdown documents with headers
- Results are already ranked by relevance (hybrid FTS + vector search)