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similarity-search-patterns

similarity-search-patterns

github.com/sickn33Data & databases48.9k158 installsUpdated today
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About similarity-search-patterns

A skill that provides patterns for implementing production similarity search. It is aimed at semantic search, RAG retrieval, and recommendation work, and points to an implementation playbook for detailed examples.

Key features

  1. 01Semantic search patterns
  2. 02RAG retrieval guidance
  3. 03Recommendation system patterns
  4. 04Latency optimization
  5. 05Vector search scaling
  6. 06Semantic and keyword search

Use cases

  1. 01Build a semantic search system
  2. 02Implement RAG retrieval
  3. 03Create a recommendation engine
  4. 04Improve search latency

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/sickn33/agentic-awesome-skills --skill similarity-search-patterns

After installing, type/similarity-search-patternsin Claude Code to confirm it loaded.

Bundled filesresources/implementation-playbook.md

Details

From the project README

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.

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