qmd
Search markdown knowledge bases, notes, and documentation using QMD. Use when users ask to search notes, find documents, or look up information.
What this skill does
# QMD - Quick Markdown Search
Local search engine for markdown content.
## Status
!`qmd status 2>/dev/null || echo "Not installed: npm install -g @tobilu/qmd"`
## MCP: `query`
```json
{
"searches": [
{ "type": "lex", "query": "CAP theorem consistency" },
{ "type": "vec", "query": "tradeoff between consistency and availability" }
],
"collections": ["docs"],
"limit": 10
}
```
### Query Types
| Type | Method | Input |
|------|--------|-------|
| `lex` | BM25 | Keywords — exact terms, names, code |
| `vec` | Vector | Question — natural language |
| `hyde` | Vector | Answer — hypothetical result (50-100 words) |
### Writing Good Queries
**lex (keyword)**
- 2-5 terms, no filler words
- Exact phrase: `"connection pool"` (quoted)
- Exclude terms: `performance -sports` (minus prefix)
- Code identifiers work: `handleError async`
**vec (semantic)**
- Full natural language question
- Be specific: `"how does the rate limiter handle burst traffic"`
- Include context: `"in the payment service, how are refunds processed"`
**hyde (hypothetical document)**
- Write 50-100 words of what the *answer* looks like
- Use the vocabulary you expect in the result
**expand (auto-expand)**
- Use a single-line query (implicit) or `expand: question` on its own line
- Lets the local LLM generate lex/vec/hyde variations
- Do not mix `expand:` with other typed lines — it's either a standalone expand query or a full query document
### Intent (Disambiguation)
When a query term is ambiguous, add `intent` to steer results:
```json
{
"searches": [
{ "type": "lex", "query": "performance" }
],
"intent": "web page load times and Core Web Vitals"
}
```
Intent affects expansion, reranking, chunk selection, and snippet extraction. It does not search on its own — it's a steering signal that disambiguates queries like "performance" (web-perf vs team health vs fitness).
### Combining Types
| Goal | Approach |
|------|----------|
| Know exact terms | `lex` only |
| Don't know vocabulary | Use a single-line query (implicit `expand:`) or `vec` |
| Best recall | `lex` + `vec` |
| Complex topic | `lex` + `vec` + `hyde` |
| Ambiguous query | Add `intent` to any combination above |
First query gets 2x weight in fusion — put your best guess first.
### Lex Query Syntax
| Syntax | Meaning | Example |
|--------|---------|---------|
| `term` | Prefix match | `perf` matches "performance" |
| `"phrase"` | Exact phrase | `"rate limiter"` |
| `-term` | Exclude | `performance -sports` |
Note: `-term` only works in lex queries, not vec/hyde.
### Collection Filtering
```json
{ "collections": ["docs"] } // Single
{ "collections": ["docs", "notes"] } // Multiple (OR)
```
Omit to search all collections.
## Other MCP Tools
| Tool | Use |
|------|-----|
| `get` | Retrieve doc by path or `#docid` |
| `multi_get` | Retrieve multiple by glob/list |
| `status` | Collections and health |
## CLI
```bash
qmd query "question" # Auto-expand + rerank
qmd query $'lex: X\nvec: Y' # Structured
qmd query $'expand: question' # Explicit expand
qmd query --json --explain "q" # Show score traces (RRF + rerank blend)
qmd search "keywords" # BM25 only (no LLM)
qmd get "#abc123" # By docid
qmd multi-get "journals/2026-*.md" -l 40 # Batch pull snippets by glob
qmd multi-get notes/foo.md,notes/bar.md # Comma-separated list, preserves order
```
## HTTP API
```bash
curl -X POST http://localhost:8181/query \
-H "Content-Type: application/json" \
-d '{"searches": [{"type": "lex", "query": "test"}]}'
```
## Setup
```bash
npm install -g @tobilu/qmd
qmd collection add ~/notes --name notes
qmd embed
```
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