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Bullish-Design
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remora

Parse and index repository files for semantic search over code and documentation.

Updated Mar 13, 2026
Search Tags:#semantic search#repository#ai assistance#knowledge extraction#code indexing
One-click install
npx skills add https://github.com/Bullish-Design/remora-test --skill remora
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: remora
Source: https://github.com/Bullish-Design/remora-test/tree/main/.agents/skills/allium
Command: npx skills add https://github.com/Bullish-Design/remora-test --skill remora

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill automates the extraction, indexing, and querying of structured repository metadata to assist in AI-powered code search, comprehension, and onboarding.

Core Features & Use Cases

  • Repository Parsing and Indexing: Reads repository files to create a comprehensive metadata index.
  • Semantic Search: Enables natural language querying over repository content for rapid answers.
  • Use Case: Quickly find all skills related to 'PDF processing' in a large codebase and get detailed summaries.

Quick Start

Use the remora skill to perform a semantic query over the provided GitHub repo to find skills related to PDF extraction.

Frequently Asked Questions about remora

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

FAQPage Schema
How do I perform semantic search over a software repository?▼

Semantic search over a software repository works by parsing and indexing repository files to create a metadata index, enabling natural language querying for rapid code discovery and comprehension.

Can I use natural language queries to find specific code in a large codebase?▼

Yes, you can use natural language queries to find specific code in a large codebase by leveraging an AI-driven repository index that reads Markdown, code, and documentation to return detailed summaries.

How does automated repository parsing improve the developer onboarding process?▼

Automated repository parsing improves developer onboarding by extracting and indexing structured repository metadata, allowing new developers to rapidly discover code functionalities through natural language querying.

What file formats are supported for AI-driven repository analysis and indexing?▼

AI-driven repository analysis and indexing supports parsing repository files including Markdown, code, and documentation to build a comprehensive metadata index for search.

What is the best way to find all skills related to a specific feature in a codebase?▼

The best way to find skills related to a specific feature in a codebase is automating semantic analysis over your repository index to extract detailed summaries and relevant code locations.

Does AI-powered code search work without parsing documentation files?▼

AI-powered code search requires parsing and indexing repository files including documentation, Markdown, and code to ensure accurate knowledge extraction and comprehensive semantic search results.

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