Vertex AI RAG Search Skill
Purpose
Search related knowledge from phsysics project's BigQuery (4,362 embeddings) + GCS (context/, decisions/, session_logs/)
Search Method
- •Analyze query and extract keywords
- •BigQuery vector similarity search (COSINE_SIMILARITY)
- •GCS metadata search
- •Integrate and sort results by relevance
Usage Examples
bash
/vertex-search NoiseComputer multiplication rules /vertex-search previous debate results /vertex-search RTL optimization patterns
Output Format
- •Relevance score (0.0-1.0)
- •Content snippet
- •Source (BigQuery/GCS)
- •GitHub link (if available)
- •Timestamp
Configuration
Edit config/vertex_config.yaml to adjust:
- •
similarity_threshold: Minimum relevance (default: 0.7) - •
max_results: Maximum results to return (default: 10)
Implementation
Python script: .claude/skills/vertex-search/vertex_search.py
- •Uses BigQuery client for embedding similarity search
- •Uses GCS client for metadata search
- •Combines results with relevance ranking