act101

act101 is an AST-aware code transformation and refactoring tool designed for developers and AI agents to perform precise semantic edits and structural analysis. It addresses inefficiencies inherent in whole-file rewrites by providing targeted abstract syntax tree (AST) operations, improving token usage and preserving code formatting. With support for over 160 programming grammars, act101 offers a robust set of 180 refactoring operations and 30 analysis tools in a single native Rust binary.

What Makes act101 Stand Out

• Token-Efficient Code Operations: On average, act101 reduces token consumption by about 85% compared to whole-file based transformations by returning precise structured diffs and avoiding redundant parsing.
• Comprehensive AST Refactoring: It supports rename, extract, inline, move, and import organization through semantic manipulation rather than brittle text replacement.
• Structural Code Analysis: Features 30 structural analysis operations that map code coupling, cycles, boundaries, and health, enabling risk assessment and maintainability insights.
• MCP-Native Architecture: Runs as a single local binary without indexing, caching, or external runtime dependencies, minimizing attack surface and ensuring data privacy as all code remains on the user's machine.
• Agentic Refactoring Support: Enables AI coding agents to transform code semantically by navigating, refactoring, and analyzing codebases with safe checkpoints and undo functionality.

Use Cases

• Developers leveraging AI agents (such as Claude Code, Cursor) to perform safe, token-efficient code refactoring and navigation.
• Teams requiring extensive structural analysis and scalable semantic refactoring to improve codebase health and manage large, multi-language projects.
• Open-source and personal projects benefiting from a free local AST transformation tool without telemetry or cloud-based code processing.

Frequently Asked Questions

What is act101?

act101 is an AST-aware code transformation tool focused on semantic refactoring and structural analysis across more than 160 programming grammars. It enables precise and token-efficient codebase navigation and editing through a single native binary.

How does act101 benefit AI-based coding workflows?

By providing targeted AST operations instead of file-based rewrites, act101 reduces unnecessary token consumption and formatting errors. AI agents gain capabilities for safe refactors, structural insights, and checkpoint-based undo operations, enhancing automated code transformation reliability.

What are the limitations or trade-offs of using act101?

While act101 excels in syntax-aware transformations, it requires AI agents or users to operate within its MCP-native setup and is optimized primarily for environments prioritizing local execution and privacy. Very small repositories or extremely simple codebases may see reduced token savings.

What types of refactoring operations does act101 support?

The tool offers over 180 AST-aware refactoring operations, including renaming identifiers, code extraction, inlining, moving code elements, organizing imports, and code generation based on semantic understanding.

How does act101 ensure data privacy?

All code analysis and transformations occur locally through its single Rust binary without telemetry or external code uploads. License verification may contact servers, but no code data is transmitted remotely, ensuring developer source code remains private.