Does CodeEagle support multi-repo environments?

Yes, CodeEagle is designed to handle single repos, monorepos, or sets of related repositories to create a unified knowledge graph.

Which programming languages are supported by CodeEagle?

CodeEagle supports a wide range of languages including Go, Python, TypeScript, JavaScript, Java, Rust, C#, Ruby, and various configuration and documentation formats.

What is the primary benefit of using CodeEagle with Claude?

CodeEagle allows Claude to understand a codebase through a pre-indexed knowledge graph, enabling it to perform impact analysis and symbol lookups significantly faster than reading individual source files.

How does the semantic search feature work?

The 'rag' command uses hybrid ranking combining vector similarity, keyword matching, and graph centrality to find the most relevant code entities for a natural language query.

Can CodeEagle help identify unused code?

Yes, it includes a specific 'query unused' command that identifies functions or methods with no incoming call edges in the knowledge graph.

CodeEagle Codebase Intelligence

Name: CodeEagle Codebase Intelligence
Author: imyousuf

byimyousuf

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开发者工具

Navigates and analyzes complex codebases using an indexed knowledge graph to provide instant insights into symbols, dependencies, and impact analysis.

CodeEagle is a powerful codebase intelligence skill that creates a structured knowledge graph of your project, including symbols, interfaces, and cross-service dependencies. It allows developers to perform semantic searches, conduct impact analysis for planned changes, and review designs without the need to manually read through every source file. By leveraging non-coding agents for planning and design, CodeEagle bridges the gap between raw source code and high-level architecture, making it an essential tool for navigating large-scale monorepos and multi-repo environments efficiently.

主要功能

01Graph-based symbol and interface querying across multiple programming languages

02Semantic search (RAG) for finding code by intent rather than exact name

03Deep dependency tracing including call graphs and cross-service API consumers

04Automated impact analysis and change planning via specialized AI agents

05Integrated test coverage reporting and automated dead code detection

061 GitHub stars

使用场景

01Assessing the potential impact and risks of a major refactor or interface change

02Onboarding to a large, unfamiliar codebase by visualizing architecture and dependencies

03Identifying architectural patterns and ensuring API consistency across microservices

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add imyousuf/codeeagle codeeagle

For use in Claude.ai and ChatGPT

Download Skill