qmd

Original：🇺🇸 English

Translated

Search markdown knowledge bases, notes, and documentation using QMD. Use when users ask to search notes, find documents, or look up information.

2installs

Sourcepedronauck/skills

Added on2026-04-05

NPX Install

npx skill4agent add pedronauck/skills qmd

SKILL.md Content

View Translation Comparison →

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

qmd

NPX Install

Tags

SKILL.md Content

QMD - Quick Markdown Search

Status

MCP:
`query`

Query Types

Writing Good Queries

Intent (Disambiguation)

Combining Types

Lex Query Syntax

Collection Filtering

Other MCP Tools

CLI

HTTP API

Setup