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name: knowledge-searching description: Retrieves implementation knowledge, code examples, and documentation references. Use to inform technical decision-making when the user requires specific library usage, framework patterns, or syntax details. Trigger on requests to 'search docs', 'find code examples', or 'check implementation details'.

Knowledge Searching

Overview

Retrieves implementation knowledge to inform decision-making across the software development lifecycle.

Use this skill when you need:

• Implementation details for specific libraries/frameworks
• Code examples for patterns or features
• Documentation references libraries/frameworks usage

Announce at start: "I'm using the knowledge-research skill to gather implementation details."

Core Functions

Searching Specific Documentation:

1. Get sources → rag_get_available_sources() - Returns list with id, title, url
2. Find source ID → Match to documentation (e.g., "Supabase docs" → "src_abc123")
3. Search → rag_search_knowledge_base(query="vector functions", source_id="src_abc123")

General Research:

Copy# Search knowledge base (2-5 keywords only!)
rag_search_knowledge_base(query="authentication JWT", match_count=5)

# Find code examples
rag_search_code_examples(query="React hooks", match_count=3)

Query Guidelines

✅ Good Queries (2-5 keywords)

• "authentication JWT"
• "vector functions"
• "React hooks"
• "Go context timeout"
• "SQL row level security"

❌ Bad Queries (too long/verbose)

• "How do I implement JWT authentication in Go?"
• "What are the best practices for vector similarity search?"
• "Show me examples of React hooks for state management"

Rule: Keep queries SHORT and keyword-focused for optimal search results.