Skill.md
Implement efficient similarity search with vector databases. Use when building semantic search, implementing nearest neighbor queries, or optimizing retrieval performance.
SKILL.md
--- name: similarity-search-patterns description: "Implement efficient similarity search with vector databases. Use when building semantic search, implementing nearest neighbor queries, or optimizing retrieval performance." risk: safe source: community date_added: "2026-02-27" --- # Similarity Search Patterns Patterns for implementing efficient similarity search in production systems. ## Use this skill when - Building semantic search systems - Implementing RAG retrieval - Creating recommendation engines - Optimizing search latency - Scaling to millions of vectors - Combining semantic and keyword search ## Do not use this skill when - The task is unrelated to similarity search patterns - You need a different domain or tool outside this scope ## Instructions - Clarify goals, constraints, and required inputs. - Apply relevant best practices and validate outcomes. - Provide actionable steps and verification. - If detailed examples are required, open `resources/implementation-playbook.md`. ## Resources - `resources/implementation-playbook.md` for detailed patterns and examples. ## Limitations - Use this skill only when the task clearly matches the scope described above. - Do not treat the output as a substitute for environment-specific validation, testing, or expert review. - Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.
Use when building semantic search, implementing nearest neighbor queries, or optimizing retrieval performance.
