Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub ยท Developer Tools
QMD Search
Search markdown knowledge bases efficiently using qmd. Use this when searching Obsidian vaults or markdown collections to find relevant content with minimal token usage.
skill openclawclawhub Free
Search markdown knowledge bases efficiently using qmd. Use this when searching Obsidian vaults or markdown collections to find relevant content with minimal token usage.
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Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- SKILL.md
Validation
- Use the Yavira download entry.
- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
Install with your agent
Agent handoff
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
New install
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
Upgrade existing
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 1.0.0
Provenance
- Publisher
- anshumanbh
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
QMD Search Skill
Search markdown knowledge bases efficiently using qmd, a local indexing tool that uses BM25 + vector embeddings to return only relevant snippets instead of full files.
Why Use This
96% token reduction - Returns relevant snippets instead of reading entire files Instant results - Pre-indexed content means fast searches Local & private - All indexing and search happens locally Hybrid search - BM25 for keyword matching, vector search for semantic similarity
Search (BM25 keyword matching)
qmd search "your query" --collection <name> Fast, accurate keyword-based search. Best for specific terms or phrases.
Vector Search (semantic)
qmd vsearch "your query" --collection <name> Semantic similarity search. Best for conceptual queries where exact words may vary.
Hybrid Search (both + reranking)
qmd hybrid "your query" --collection <name> Combines both approaches with LLM reranking. Most thorough but often overkill.
How to Use
Check if collection exists: qmd collection list Search the collection: # For specific terms qmd search "api authentication" --collection notes # For conceptual queries qmd vsearch "how to handle errors gracefully" --collection notes Read results: qmd returns relevant snippets with file paths and context
Setup (if qmd not installed)
# Install qmd bun install -g https://github.com/tobi/qmd # Add a collection (e.g., Obsidian vault) qmd collection add ~/path/to/vault --name notes # Generate embeddings for vector search qmd embed --collection notes
Invocation Examples
/qmd api authentication # BM25 search for "api authentication" /qmd how to handle errors --semantic # Vector search for conceptual query /qmd --setup # Guide through initial setup
Best Practices
Use BM25 search (qmd search) for specific terms, names, or technical keywords Use vector search (qmd vsearch) when looking for concepts where wording may vary Avoid hybrid search unless you need maximum recall - it's slower Re-run qmd embed after adding significant new content to keep vectors current
Handling Arguments
$ARGUMENTS contains the full search query If --semantic flag is present, use qmd vsearch instead of qmd search If --setup flag is present, guide user through installation and collection setup If --collection <name> is specified, use that collection; otherwise default to checking available collections
Workflow
Parse arguments from $ARGUMENTS Check if qmd is installed (which qmd) If not installed, offer to guide setup If searching: List collections if none specified Run appropriate search command Present results to user with file paths If user wants to read a specific result, use the Read tool on the file path
Category context
Code helpers, APIs, CLIs, browser automation, testing, and developer operations.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
1 Docs
- SKILL.md