Skill · Data AI
Similarity search patterns
Implement efficient similarity search with vector databases. Use when building semantic search, implementing nearest neighbor queries, or optimizing retrieval performance.
How to use it
- Start your plan and connect your AI once
- Add the skill to your AI, one time only: press Copy skill and paste it into your AI's instructions: a project in ChatGPT, Claude or Grok, a Gem in Gemini, an agent in Microsoft 365 Copilot, or a rule in Cursor. It stays there for every new chat. In Kimi, paste it at the start of a new chat.
- Ask for the task in your own words, or say it directly:
Use the Similarity search patterns skill to help me with this.SKILL.md2 files in this skill
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.mdfor 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.