Which AI assistants and IDEs does Ohm integrate with?

Ohm is designed to work with GitHub Copilot, Cursor IDE, Cline, and any other MCP-compatible AI assistant, providing seamless integration directly within your development workflow.

How does Ohm ensure refactoring accuracy and safety?

Ohm uses 100% AST-based analysis for accurate refactoring. It also provides safety checks, project backups, and rollback capabilities for automated refactoring applications, ensuring changes are secure.

Ohm is an AI-powered Python assistant for refactoring and code quality analysis. It helps developers improve their Python projects by detecting issues, suggesting fixes, and automating code transformations.

What are Ohm's core capabilities for Python projects?

Ohm excels at 100% AST-based method extraction and symbol renaming, detects architectural issues (like God Objects and SOLID violations), eliminates dead code, identifies duplications, and performs type safety analysis.

Ohm

Name: Ohm
Author: Murugarajr

byMurugarajr

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Security & Testing

Developer Tools

Productivity & Workflow

Provides AI-powered refactoring and code quality analysis for Python projects.

Ohm is an AI-powered assistant designed to enhance Python code quality and refactoring efforts. Leveraging Abstract Syntax Trees (ASTs), it offers highly accurate analysis and transformations. It integrates seamlessly with popular AI assistants like GitHub Copilot, Cursor IDE, and Cline via the Model Context Protocol (MCP), enabling developers to prompt their AI to utilize Ohm's advanced capabilities for tasks such as architecture analysis, dead code elimination, type safety checks, and performance optimization. Ohm automates complex refactoring operations, providing safety features like backups and rollbacks, and contributes to a more maintainable, performant, and robust codebase.

Key Features

01Analyzes type coverage, generates type stubs, and auto-generates characterization tests.

02Performs comprehensive dead code elimination and smart code duplication detection.

032 GitHub stars

04Automates refactoring application with safety checks, backups, and rollback capabilities.

05100% AST-based accurate method extraction and project-wide symbol renaming.

06Detects architectural issues including God Objects, SOLID violations, and tight coupling.

Use Cases

01Automating the detection and resolution of architectural, quality, and performance bottlenecks in Python projects.

02Integrating advanced code analysis into AI-powered development environments like GitHub Copilot.

03Streamlining Python codebase refactoring and quality improvements with AI assistance.