act101

act101 — AI agents that refactor and port code across 163 languages The first dev tool that lets an AI agent actually refactor and port code. 163 grammars, 183 refactor operations, 30 analyzers, 8 porting ops — for Claude Code, Cursor, Codex, OpenCode via MCP. Agent refactor Python. Agent port C to Rust. Agent port Ruby to Elixir. 163 grammars, 183 refactor ops, 8 porting ops via MCP. Free for personal use. The first dev tool that lets an AI agent actually refactor and port code. 163 grammars, 183 AST refactor operations, 30 codebase analyzers, 8 porting operations — exposed to Claude Code, Cursor, Codex, and OpenCode through a built-in MCP server. Agent refactor Python. Agent port C to Rust. Agent port Ruby to Elixir.

act101 provides a robust infrastructure for managing the quality of AI-generated code. It addresses the problem of agentic debt, which accumulates with every merge made by coding agents. The software allows users to analyze their code, enact deterministic refactors, and attest each change with a provable verdict and receipt, ensuring high-quality and maintainable codebases. Users install act101 and connect it with their coding agents. The tool analyzes the codebase using 42 analyzers, performs refactoring through 182 operations, and attests changes through a verification gate. Each merge made by the agent is analyzed for behavior changes, ensuring only verified changes proceed, thus providing a 'receipt' of modifications made. act101 is designed for individual engineers, codebase owners, and open-source maintainers. It appeals to those managing AI coding agents, allowing them to verify and attest to changes safely. The product is particularly suited for users who need to maintain high standards of code quality amid rapid iterations by coding agents.