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qmd Search
作者
bheemreddy181
· GitHub ↗
· v1.1.0
3431
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版本数
在 OpenClaw 中安装
/install qmd-search
功能描述
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.
使用说明 (SKILL.md)
qmd — Fast Local Markdown Search
When to Use
- Finding files — use instead of
findacross 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
- Always use collections (
-c name) to scope searches - Run
qmd updateafter adding new files - Use
qmd embedto enable vector search (one-time, takes a few minutes) - Prefer
qmd search --filesoverfindfor large directories
Models (auto-downloaded)
- Embedding: embeddinggemma-300M
- Reranking: qwen3-reranker-0.6b
- Generation: Qwen3-0.6B
All run locally — no API keys needed.
安全使用建议
Before installing, verify these things with the publisher: (1) Confirm whether the qmd CLI is required and provide explicit 'required binaries' metadata (the SKILL.md assumes qmd is present). (2) Document install steps or a trusted source for the qmd binary and for the models (where the 'auto-downloaded' models come from—e.g., official releases, Hugging Face, or a vendor mirror). Unspecified model downloads can pull large binaries from arbitrary hosts and consume disk/network; ask how downloads are authenticated and where they are stored. (3) Understand which directories the skill will index and ensure you are comfortable granting the agent read access to those paths. (4) If you need higher assurance, request a homepage or source repo for the skill so you can inspect install scripts. If the publisher provides a clear install manifest and trusted model sources (or states qmd is preinstalled in your environment), this assessment could be downgraded to benign.
功能分析
Type: OpenClaw Skill
Name: qmd-search
Version: 1.1.0
The skill bundle describes a local markdown search tool (`qmd`). All instructions and command examples in `SKILL.md` are consistent with its stated purpose of searching local files, managing collections, and retrieving file content. There is no evidence of data exfiltration, malicious execution, persistence mechanisms, prompt injection attempts against the agent, or obfuscation. The mention of 'auto-downloaded' models is a standard practice for local LLM-powered tools and does not indicate malicious intent within the provided content.
能力评估
Purpose & Capability
The SKILL.md clearly expects the qmd CLI and local model runtimes (embeddinggemma-300M, qwen3-reranker-0.6b, Qwen3-0.6B). However, the registry metadata declares no required binaries, no install instructions, and no homepage/source. A user installing this skill would legitimately need qmd and model runtime support, so the omission is an incoherence that should be explained by the publisher.
Instruction Scope
The runtime instructions stay within the stated purpose (searching/indexing local files and returning snippets). They do imply the agent will read files in user-specified collections (expected for a search tool). The document also mentions 'models (auto-downloaded)' — the instructions do not specify where these downloads come from or whether they require network access or extra permissions.
Install Mechanism
There is no install spec (instruction-only), which is low-risk generally, but the SKILL.md claims models are auto-downloaded and run locally. The skill does not document the source of those model downloads (no URLs, releases, or registries). Unspecified automatic downloads of large model binaries increase risk (arbitrary network fetch & disk writes) and should be documented.
Credentials
The skill declares no required environment variables, credentials, or config paths and the instructions do not reference any secrets or unrelated env vars. That absence is proportionate to the stated purpose.
Persistence & Privilege
The skill is not marked 'always' and does not request persistent system privileges. As an instruction-only skill it does not modify other skills' configs or demand elevated privileges.
如何使用
- 确保已安装 OpenClaw(本地或 Docker 部署)
- 在对话框中输入安装命令:
/install qmd-search - 安装完成后,直接呼叫该 Skill 的名称或使用
/qmd-search触发 - 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.1.0
Updated skill with comprehensive docs
v1.0.0
Initial release: fast local markdown search with BM25, vector search, and LLM reranking
元数据
常见问题
qmd Search 是什么?
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. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 3431 次。
如何安装 qmd Search?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install qmd-search」即可一键安装,无需额外配置。
qmd Search 是免费的吗?
是的,qmd Search 完全免费(开源免费),可自由下载、安装和使用。
qmd Search 支持哪些平台?
qmd Search 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。
谁开发了 qmd Search?
由 bheemreddy181(@bheemreddy181)开发并维护,当前版本 v1.1.0。
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