Overview
search runs a semantic vector search over all decisions in the workspace. It finds decisions by meaning — not just keyword matching — so “how do we handle auth?” returns JWT decisions even if “authentication” wasn’t the exact word used.
Decisions are embedded with OpenAI’s text-embedding-3-small (1536 dimensions) and indexed in pgvector for fast approximate nearest-neighbor search.
Parameters
Response
Response Fields
Examples
Find auth decisions
Find database choices
Check for existing patterns
When to Call search
- Before implementing something — “did we already decide on this?”
- When unfamiliar with part of the codebase — “what’s the rationale for how this works?”
- Before picking a library — “have we already adopted something for this use case?”
- When debugging — “has anyone dealt with this type of issue before?”
Use natural language queries. The semantic search understands intent — “how do we validate user input?” will find Zod decisions even if you don’t mention Zod.