Local-first code intelligence graph for MCP and CLI. Builds a persistent map of your codebase so AI coding tools read only what matters, with benchmarked context reductions on reviews and large-repo workflows.
Signatures for entire Python programs. Extract the structure, the frame, the skeleton of your project, to generate API documentation or find breaking changes in your API.
A Github Action for linting C/C++ code integrating clang-tidy and clang-format to collect feedback provided in the form of file-annotations, thread-comments, workflow step-summary, and Pull Request reviews.
A powerful C# Roslyn analyzer that uses static analysis to detect bugs, surface security issues, and enforce best practices—helping developers and AI write more reliable code.
Codebase intelligence for AI and humans: code health scores, auto-generated docs, git analytics, dead code detection, and architectural decisions via MCP.
An AI-powered GitHub code review tool that uses LLMs to detect high-confidence, high-impact issues—such as security vulnerabilities, bugs, and maintainability concerns.