What should I do if ygrep doesn't find what I'm looking for?

If ygrep returns no results, it is possible the file hasn't been indexed yet. In these cases, you should fall back to using standard Grep or Glob tools.

Why should I use ygrep instead of standard grep in Claude Code?

ygrep uses a pre-built index and the Tantivy engine to return results in milliseconds, whereas standard grep must scan every file linearly, which can take significantly longer in large projects.

What is subtoken matching?

Subtoken matching splits identifiers like 'sendEmailRequest' into individual parts, allowing you to find matches regardless of whether the code uses camelCase, snake_case, or separate words.

Does ygrep support regular expressions?

Yes, you can perform powerful regex searches by using the -r flag with your query.

How do I ensure my codebase is indexed for ygrep?

You can initialize or update the search index for your current workspace at any time by running the 'ygrep index' command in the terminal.

Ygrep Fast Code Search

Name: Ygrep Fast Code Search
Author: yetidevworks

byyetidevworks

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Herramientas para Desarrolladores

Accelerates code exploration with a high-speed, indexed search engine providing millisecond results for AI coding assistants.

This skill integrates ygrep, a Rust-based full-text indexing tool powered by Tantivy, into the Claude Code workflow to provide near-instantaneous codebase navigation. It allows Claude to locate functions, variables, and specific code patterns significantly faster than standard linear scanning tools like grep or glob. By supporting advanced features such as subtoken matching for camelCase/snake_case, regex, and path-based filtering, it serves as the high-performance primary search layer for navigating complex repositories efficiently.

Características Principales

01Lightning-fast indexed search delivering results in milliseconds via Rust and Tantivy.

02Customizable context output with before (B), after (A), and surrounding (K) line flags.

0337 GitHub stars

04AI-optimized output format featuring relevance scores and match indicators.

05Smart subtoken matching to easily find camelCase and snake_case identifiers.

06Advanced filtering options for file extensions, path prefixes, and glob patterns.

Casos de Uso

01Exploring unfamiliar repositories by performing multi-word logic searches for related concepts.

02Locating definitions and usages across massive codebases where standard tools are too slow.

03Isolating code changes within specific directories using path-filtered regex searches.

Características Principales

01Lightning-fast indexed search delivering results in milliseconds via Rust and Tantivy.

02Customizable context output with before (B), after (A), and surrounding (K) line flags.

0337 GitHub stars

04AI-optimized output format featuring relevance scores and match indicators.

05Smart subtoken matching to easily find camelCase and snake_case identifiers.

06Advanced filtering options for file extensions, path prefixes, and glob patterns.

Casos de Uso

01Exploring unfamiliar repositories by performing multi-word logic searches for related concepts.

02Locating definitions and usages across massive codebases where standard tools are too slow.

03Isolating code changes within specific directories using path-filtered regex searches.