QMD - Quick Markdown Search

SkillSearch

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

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the QMD - Quick Markdown Search skill

What this skill tells your AI

The instructions your AI receives, as published by pedronauck/skills in skills/curated/qmd/SKILL.md and read by ahel’s review.

Local search engine for markdown content.

Status

!qmd status 2>/dev/null || echo "Not installed: npm install -g @tobilu/qmd"

MCP: query

{
  "searches": [
    { "type": "lex", "query": "CAP theorem consistency" },
    { "type": "vec", "query": "tradeoff between consistency and availability" }
  ],
  "collections": ["docs"],
  "limit": 10
}

Query Types

TypeMethodInput
lexBM25Keywords — exact terms, names, code
vecVectorQuestion — natural language
hydeVectorAnswer — 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:

{
  "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

GoalApproach
Know exact termslex only
Don't know vocabularyUse a single-line query (implicit expand:) or vec
Best recalllex + vec
Complex topiclex + vec + hyde
Ambiguous queryAdd intent to any combination above

First query gets 2x weight in fusion — put your best guess first.

Lex Query Syntax

SyntaxMeaningExample
termPrefix matchperf matches "performance"
"phrase"Exact phrase"rate limiter"
-termExcludeperformance -sports

Note: -term only works in lex queries, not vec/hyde.

Collection Filtering

{ "collections": ["docs"] }              // Single
{ "collections": ["docs", "notes"] }     // Multiple (OR)

Omit to search all collections.

Other MCP Tools

ToolUse
getRetrieve doc by path or #docid
multi_getRetrieve multiple by glob/list
statusCollections and health

CLI

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

curl -X POST http://localhost:8181/query \
  -H "Content-Type: application/json" \
  -d '{"searches": [{"type": "lex", "query": "test"}]}'

Setup

npm install -g @tobilu/qmd
qmd collection add ~/notes --name notes
qmd embed

Signals

GitHub stars
611
Forks
88
Last commit
Sep 2026

ahel review

  • K1binfo
    installs-packages
  • K1binfo
    installs-packages (in references/mcp-setup.md)

Automated review, not a security audit. Ruleset v1+k2.

Others that do the same job

Advanced
Catalog kind
skill
Gateway key
qmd-pedronauck
Source
github.com/pedronauck/skills