qmd
Local search/indexing CLI (BM25 + vectors + rerank) with MCP mode.
Best use case
qmd is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Local search/indexing CLI (BM25 + vectors + rerank) with MCP mode.
Teams using qmd should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/qmd-1-0-0/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How qmd Compares
| Feature / Agent | qmd | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Local search/indexing CLI (BM25 + vectors + rerank) with MCP mode.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# qmd Use `qmd` to index local files and search them. Indexing - Add collection: `qmd collection add /path --name docs --mask "**/*.md"` - Update index: `qmd update` - Status: `qmd status` Search - BM25: `qmd search "query"` - Vector: `qmd vsearch "query"` - Hybrid: `qmd query "query"` - Get doc: `qmd get docs/path.md:10 -l 40` Notes - Embeddings/rerank use Ollama at `OLLAMA_URL` (default `http://localhost:11434`). - Index lives under `~/.cache/qmd` by default. - MCP mode: `qmd mcp`.
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