skill-search

name	skill-search
description	Find and retrieve available skills using keyword search, semantic search, or LLM-powered task matching. Use when the agent needs to discover, search, or intelligently match skills to tasks. Supports hybrid search (BM25 + semantic), natural language task descriptions, and intelligent skill recommendations.
triggers	["search skills","find a skill","what skills are available","skill for X","suggest skills for","what skill should I use","recommend a skill"]

Skill Search V1.1

Find skills using keyword, semantic, or AI-powered task matching.

Overview

This skill provides three search modes:

1. Keyword Search (Fast BM25) — Match skill names and descriptions
2. Semantic Search (Embeddings) — Find skills by meaning/concept similarity
3. LLM Task Matching (AI-powered) — Describe your task, get skill recommendations

When to Use

• Before starting a new task — check if a relevant skill exists
• When user asks for capabilities — "what can you do with PDFs?"
• To avoid context bloat — find the right skill first, then load only that one
• When unsure which skill applies — use semantic or LLM matching for fuzzy matches

Search Modes

1. Keyword Search (Fast)

./scripts/skill_search.py keyword "weather"
./scripts/skill_search.py keyword "pdf"
./scripts/skill_search.py keyword "image generation"

2. Semantic Search (Meaning-based)

./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"

3. LLM Task Matching (AI-powered)

./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"

4. List All Skills

./scripts/skill_search.py list

Usage Pattern

1. Search: Find skills matching your need (keyword/semantic/LLM)
2. Preview: Read SKILL.md metadata (description, triggers)
3. Load: If it's the right skill, read full body and execute

Example Workflows

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) — Batch-generate images via OpenAI Images API
2. browser (0.65) — 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 — Transcribe audio via OpenAI Audio Transcriptions API (Whisper)
   Confidence: High
   Reason: Task explicitly matches skill purpose

2. sag — ElevenLabs text-to-speech (inverse operation, may be related)
   Confidence: Low
   Reason: Related to audio processing but output not input

Search Index

The skill maintains a local search index at:

• ~/.openclaw/workspace/skills/skill-search/index/skills_index.json — Skill metadata
• ~/.openclaw/workspace/skills/skill-search/index/embeddings.json — Semantic embeddings (lazy-loaded)

Indexing happens automatically on first semantic search if no index exists.

Force reindex:

./scripts/skill_search.py index

Resources

scripts/

• skill_search.py — Main search interface (keyword/semantic/LLM)
• indexer.py — Build/update search index
• embeddings.py — Embedding generation (local miniLM)

index/

• skills_index.json — Searchable skill metadata
• embeddings_cache.json — Pre-computed embeddings for semantic search