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qmd Search

该 Skill 指导使用 qmd 命令行工具在本地索引集合中检索 Markdown、笔记与文档,结合 BM25 全文、向量语义与 LLM 重排序,可按 collection 限定范围,输出文件路径、片段或 JSON/Markdown 结果;模型本地运行、无需 API Key。

bheemreddy181
bheemreddy181
热度 75.41
最近更新 2026-05-11 15:50:57
分类:搜索依赖:代码执行 / 读写文件应用场景:研究 / 笔记整理

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add qmd-search
Metadata
name
qmd
description
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.

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)

# 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

# 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

# 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.