Agent skill

qmd

Local hybrid search for markdown notes and docs. Use when searching notes, finding related content, or retrieving documents from indexed collections.

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Install this agent skill to your Project

npx add-skill https://github.com/ckorhonen/claude-skills/tree/main/skills/qmd

SKILL.md

qmd - Quick Markdown Search

Local search engine for Markdown notes, docs, and knowledge bases. Index once, search fast.

When to use (trigger phrases)

  • "search my notes / docs / knowledge base"
  • "find related notes"
  • "retrieve a markdown document from my collection"
  • "search local markdown files"

Default behavior (important)

  • Prefer qmd search (BM25). It's typically instant and should be the default.
  • Use qmd vsearch only when keyword search fails and you need semantic similarity (can be very slow on a cold start).
  • Avoid qmd query unless the user explicitly wants the highest quality hybrid results and can tolerate long runtimes/timeouts.

Search modes

Mode Command Speed Use case
BM25 (default) qmd search Instant Keyword matching
Vector qmd vsearch ~1 min cold Semantic similarity
Hybrid qmd query Slowest LLM reranking (skip unless requested)

Common commands

bash
qmd search "query"              # default - fast keyword search
qmd search "query" -c notes     # search specific collection
qmd search "query" -n 10        # more results
qmd search "query" --json       # JSON output
qmd search "query" --all --files --min-score 0.3

Useful options

  • -n <num>: number of results
  • -c, --collection <name>: restrict to a collection
  • --all --min-score <num>: return all matches above a threshold
  • --json / --files: agent-friendly output formats
  • --full: return full document content

Retrieve documents

bash
qmd get "path/to/file.md"       # Full document
qmd get "#docid"                # By ID from search results
qmd multi-get "journals/2025-05*.md"
qmd multi-get "doc1.md, doc2.md, #abc123" --json

Maintenance

bash
qmd status                      # Index health
qmd update                      # Re-index changed files
qmd embed                       # Update embeddings

Setup (if not installed)

bash
# Install
bun install -g https://github.com/tobi/qmd

# Create collection
qmd collection add /path/to/notes --name notes --mask "**/*.md"
qmd context add qmd://notes "Description of this collection"  # optional
qmd embed  # one-time to enable vector + hybrid search

Performance notes

  • qmd search is typically instant
  • qmd vsearch can be ~1 minute on cold start (loads local LLM for query expansion)
  • qmd query adds LLM reranking on top of vsearch, even slower

Common Pitfalls

Search query too vague (irrelevant results)

Problem: Broad queries like "notes" or "project" return hundreds of low-relevance matches.

Solution:

  • Use specific keywords: qmd search "Python async context managers" not qmd search "Python"
  • Combine keywords: qmd search "deadline March quarterly review"
  • Use quotes for exact phrases: qmd search "exact phrase match"
  • Check result scores: qmd search "query" --all --min-score 0.5 to filter low-confidence matches

Index not updated (missing recent files)

Problem: Newly created or recently modified files don't appear in search results.

Solution:

bash
# Check index status
qmd status

# Re-index all changed files
qmd update

# Full re-index if update doesn't help
qmd collection remove <name>
qmd collection add /path/to/notes --name <name> --mask "**/*.md"
qmd embed  # if vector search enabled

Path filters wrong (excluding relevant directories)

Problem: Search doesn't find files because the collection mask is too narrow or collection path is wrong.

Solution:

bash
# List current collections
qmd status

# Verify collection path matches your notes location
# If path changed, re-add collection:
qmd collection remove <old-name>
qmd collection add /path/to/notes --name <name> --mask "**/*.md"

# Common issue: subdirectories excluded by mask
# If notes are in journals/2025/*, use: --mask "**/*.md"
# Not: --mask "*.md" (which only matches top level)

Search timeout on large vaults (performance issues)

Problem: qmd query or qmd vsearch hangs or times out on large knowledge bases (1000+ files).

Solution:

  • Avoid qmd query on large vaults (LLM reranking is too slow)
  • Use qmd search instead (BM25 is fast even on huge collections)
  • If semantic search needed, use qmd vsearch with -n 5 to limit results
  • Restrict search scope with -c <collection> to search one collection instead of all:
    bash
    qmd search "query" -c notes -n 5  # faster than searching all collections
    
  • If vault exceeds 5000 files, consider splitting into multiple collections

Missing configuration (qmd not initialized)

Problem: qmd status shows "No collections" or qmd search returns no results.

Solution:

bash
# Install qmd if missing
bun install -g https://github.com/tobi/qmd

# Set up a collection
qmd collection add /path/to/notes --name notes --mask "**/*.md"

# Enable vector search (optional but recommended)
qmd embed

# Verify setup
qmd status  # Should show your collection with file count

Semantic search returns irrelevant results (vsearch/query)

Problem: Vector search matches by topic but misses what you actually wanted.

Solution:

  • Fall back to qmd search (BM25 keyword matching is more precise for specific terms)
  • Rephrase query to include actual keywords: not "What are my goals?" but "goals quarterly review objectives"
  • Use qmd query if available (adds LLM reranking), but only if you can tolerate slow runtime
  • Use -n 3 to get fewer, higher-confidence matches from vector search

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