Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Find and retrieve available skills using keyword search, semantic search, or LLM-powered task matching. Use when the agent needs to discover, search, or inte...
Find and retrieve available skills using keyword search, semantic search, or LLM-powered task matching. Use when the agent needs to discover, search, or inte...
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Then review README.md for any prerequisites, environment setup, or post-install checks. Tell me what you changed and call out any manual steps you could not complete.
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. Then review README.md for any prerequisites, environment setup, or post-install checks. Summarize what changed and any follow-up checks I should run.
Find skills using keyword, semantic, or AI-powered task matching.
This skill provides three search modes: Keyword Search (Fast BM25) โ Match skill names and descriptions Semantic Search (Embeddings) โ Find skills by meaning/concept similarity LLM Task Matching (AI-powered) โ Describe your task, get skill recommendations
Before starting a new task โ check if a relevant skill exists When user asks for capabilities โ "what can you do with PDFs?" To avoid context bloat โ find the right skill first, then load only that one When unsure which skill applies โ use semantic or LLM matching for fuzzy matches
./scripts/skill_search.py keyword "weather" ./scripts/skill_search.py keyword "pdf" ./scripts/skill_search.py keyword "image generation"
./scripts/skill_search.py semantic "automate web browsing" ./scripts/skill_search.py semantic "create images with AI" ./scripts/skill_search.py semantic "search my past conversations"
./scripts/skill_search.py suggest "I need to transcribe a podcast episode" ./scripts/skill_search.py suggest "Help me generate product photos" ./scripts/skill_search.py suggest "Search through my old emails"
./scripts/skill_search.py list
Search: Find skills matching your need (keyword/semantic/LLM) Preview: Read SKILL.md metadata (description, triggers) Load: If it's the right skill, read full body and execute
User: "I need to generate some images" Agent: Uses semantic search ./scripts/skill_search.py semantic "generate images AI" Output: Top matches (semantic): 1. openai-image-gen (0.87) โ Batch-generate images via OpenAI Images API 2. browser (0.65) โ Control web browser via Playwright Agent: Reads SKILL.md, confirms fit, executes User: "What skill should I use for transcribing audio?" Agent: Uses LLM suggest ./scripts/skill_search.py suggest "transcribe audio" Output: Recommended skills for "transcribe audio": 1. openai-whisper-api โ Transcribe audio via OpenAI Audio Transcriptions API (Whisper) Confidence: High Reason: Task explicitly matches skill purpose 2. sag โ ElevenLabs text-to-speech (inverse operation, may be related) Confidence: Low Reason: Related to audio processing but output not input
The skill maintains a local search index at: ~/.openclaw/workspace/skills/skill-search/index/skills_index.json โ Skill metadata ~/.openclaw/workspace/skills/skill-search/index/embeddings.json โ Semantic embeddings (lazy-loaded) Indexing happens automatically on first semantic search if no index exists. Force reindex: ./scripts/skill_search.py index
skill_search.py โ Main search interface (keyword/semantic/LLM) indexer.py โ Build/update search index embeddings.py โ Embedding generation (local miniLM)
skills_index.json โ Searchable skill metadata embeddings_cache.json โ Pre-computed embeddings for semantic search
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