act101
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.
$147
▲ +184%> Problem
Coding agents are excellent but inefficient coders. They waste countless tokens guessing about your codebase and its structure. They have limited context which make it difficult for them to complete complex refactorings correctly. And the situation gets even worse with any kind of architecture analysis or language migration The problem isn't the LLM. It's the tooling. act101 provides tree- and graph- based tools for codebase navigation, refactoring, analysis, and modernization across 163 grammars, allowing your coding agents to handle the most complex projects reliably.
> Customer
agentic developers, software teams, enterprise software vendors, vibe-coders
> Origin
1.5M LOC Rust developed with Claude Code, OpenCode, and OpenAI Codex using Claude, GPT, GLM and Kimi models.
> Key insight
I was working on another project and made a critical mistake - I forgot to specify a multi-tenant architecture in my spec and the agent gave me exactly what I asked for. The fix would have been quick and easy with a refactoring tool. Instead the agent spent 8 hours and millions of tokens refactoring by hand. I started work on act101 the next day.
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