Overview
- Skill Key
- bheemreddy181/qmd-search
- Author
- bheemreddy181
- Source Repo
- openclaw/skills
- Version
- -
- Source Path
- skills/bheemreddy181/qmd-search
- Latest Commit SHA
- 425c3519a461dec1d3b69e50e73dbfbdaf728ac4
Fast local search for markdown files, notes, and docs using qmd CLI. Use instead of `find` for file discovery. Combines BM25 full-text search, vector semantic search, and LLM reranking—all running locally. Use when searching for files, finding code, locating documentation, or discovering content in indexed collections.
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直接复制以下提示词,发送给你的 AI 助手即可完成安装。
请先检查是否已安装 SkillHub 商店,若未安装,请根据 https://skillhub-1388575217.cos.ap-guangzhou.myqcloud.com/install/skillhub.md 安装 SkillHub 商店,然后安装 qmd 技能。 若已安装,则直接安装 qmd 技能。
# qmd — Fast Local Markdown Search ## When to Use - **Finding files** — use instead of `find` across large directories (avoids hangs) - **Searching notes/docs** — semantic or keyword search in indexed collections - **Code discovery** — find implementations, configs, or patterns - **Context gathering** — pull relevant snippets before answering questions ## Quick Reference ### Search (most common) ```bash # Keyword search (BM25) qmd search "alpaca API" -c projects # Semantic search (understands meaning) qmd vsearch "how to implement stop loss" # Combined search with reranking (best quality) qmd query "trading rules for breakouts" # File paths only (fast discovery) qmd search "config" --files -c kell # Full document content qmd search "pattern detection" --full --line-numbers ``` ### Collections ```bash # List collections qmd collection list # Add new collection qmd collection add /path/to/folder --name myproject --mask "*.md,*.py" # Re-index after changes qmd update ``` ### Get Files ```bash # Get full file qmd get myproject/README.md # Get specific lines qmd get myproject/config.py:50 -l 30 # Get multiple files by glob qmd multi-get "*.yaml" -l 50 --max-bytes 10240 ``` ### Output Formats - `--files` — paths + scores (for file discovery) - `--json` — structured with snippets - `--md` — markdown formatted - `-n 10` — limit results ## Tips 1. **Always use collections** (`-c name`) to scope searches 2. **Run `qmd update`** after adding new files 3. **Use `qmd embed`** to enable vector search (one-time, takes a few minutes) 4. **Prefer `qmd search --files`** over `find` for large directories ## Models (auto-downloaded) - Embedding: embeddinggemma-300M - Reranking: qwen3-reranker-0.6b - Generation: Qwen3-0.6B All run locally — no API keys needed.
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