How can I find code by behavior instead of name?

Use descriptive phrases like 'validate user credentials' or 'retry failed HTTP requests' rather than exact function names to leverage GrepAI's semantic understanding of code purpose.

What do the different GrepAI scores mean?

Scores above 0.85 indicate a strong match. Scores between 0.70 and 0.84 suggest related code, while scores below 0.60 are considered weak matches that likely require query refinement.

Why should I use English for my search queries?

Most embedding models are trained primarily on English data. Using English queries typically yields the most accurate semantic matches, even if your code comments or variables use other languages.

How long should a GrepAI query be for best results?

The ideal query length is between 3 and 7 words. Queries that are too short are often vague, while queries that are too long can become overly verbose and dilute the search focus.

What is the difference between Grep and GrepAI?

Standard grep searches for exact text matches, while GrepAI uses semantic search to find code based on meaning, intent, and conceptual relationships rather than literal strings.

GrepAI Search Optimization

Name: GrepAI Search Optimization
Author: yoanbernabeu

byyoanbernabeu

•

学習とドキュメンテーション

Enhances semantic code discovery by providing expert guidance and best practices for writing effective GrepAI search queries.

The GrepAI Search Optimization skill transforms how developers navigate complex codebases by shifting the focus from literal text matches to semantic intent. It provides a comprehensive framework for constructing queries that describe behavior rather than implementation, offering specific patterns for finding error handlers, security protocols, and data operations. By implementing these best practices, users can significantly improve the accuracy of their search results, making it easier to understand unfamiliar systems and find specific logic without knowing exact function names.

主な機能

01Pattern library for finding specific code behaviors like error handling and security.

02Semantic search mindset training to focus on intent over implementation details.

03Query writing principles for optimal length and descriptive terminology.

04Iterative refinement strategies to narrow down broad search results.

05Scoring interpretation guide to evaluate the relevance of GrepAI search hits.

069 GitHub stars

ユースケース

01Onboarding to a large, unfamiliar codebase by searching for high-level business logic.

02Improving the precision of AI-driven code analysis by refining semantic queries.

03Locating specific security or error-handling patterns without knowing exact variable names.

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add yoanbernabeu/grepai-skills search

For use in Claude.ai and ChatGPT

Download Skill