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mgrep-code-search

Perform semantic search across codebases and documents using natural-language queries.

281|25|Updated Jan 20, 2026
Search Tags:#codebase#repository#nlp#developer-tools#grep#semantic-search#code-search
One-click install
npx skills add https://github.com/intellectronica/agent-skills --skill mgrep-code-search
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: mgrep-code-search
Source: https://github.com/intellectronica/agent-skills/tree/main/plugins/mgrep-code-search/skills
Command: npx skills add https://github.com/intellectronica/agent-skills --skill mgrep-code-search

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Large codebases often overwhelm developers when trying to find where a concept or feature is implemented. mgrep-code-search provides semantic search across code, text, PDFs, and images using natural-language queries to locate relevant code quickly.

Core Features & Use Cases

  • Semantic search across codebases to understand where and how features are implemented.
  • Indexing and watching large repositories to keep results up-to-date and in sync.
  • Ideal for exploring unfamiliar codebases, tracing implementation details, and validating API usage.

Quick Start

Index a repository with the watch command, then run a semantic search with your natural-language query.

Frequently Asked Questions about mgrep-code-search

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I search a large codebase when traditional grep fails to find the implementation?▼

You can use semantic code search to query large repositories with natural language, locating concepts and features where traditional grep fails. Indexing the codebase first allows you to explore unfamiliar directories and trace implementation details efficiently.

Can I search for code using natural language queries instead of exact string matches?▼

Yes, semantic code search accepts natural-language queries to locate relevant code, text, PDFs, and images. This allows you to find where and how features are implemented without knowing exact variable names or string patterns beforehand.

How do I index a large repository to keep code search results up-to-date?▼

Index a repository using the watch command to keep search results up-to-date and in sync. This monitors the codebase so subsequent natural-language queries return current results across nested directories and many files.

Does semantic code search respect gitignore patterns when indexing files?▼

Yes, semantic code search respects both .gitignore and .mgrepignore patterns when indexing files. This ensures ignored files are excluded from the index, keeping search results focused on relevant repository content.

What is the best way to explore an unfamiliar codebase and trace implementation details?▼

Semantic code search is ideal for exploring unfamiliar codebases by running natural-language queries to locate where and how features are implemented. Indexing the repository first enables you to trace implementation details and validate API usage across large repositories.

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