AI Decision System
Replayable, offline-verifiable records for AI-assisted go/no-go decisions: experiment promotions, typed model answers and human-approved actions.
Map unfamiliar code into evidence-backed specifications, then synthesize confirmed designs into a traceable project plan.
Translation pending
Developer toolsJavaScript · TypeScriptGitHub @HuginnIndustriesOnlineOwner unconfirmed
Have you tried it? One tap is enough. No sign-in needed.
Evidence-backed reverse engineering and human-gated software planning for Pi and MCP coding agents.
Taken from the repository README
Loading the full README. The saved excerpt is shown below.
Understand an unfamiliar codebase with an AI agent — and get a validated spec you can rebuild from. CodeCartographer turns a repository into layered architecture, behavioral contracts, defect findings, and a language-agnostic reimplementation spec, with each phase validated before the next one runs. Works with Pi, Claude Code, Cursor, Codex, or any MCP-capable agent.
Asking an LLM to "analyze this repo" loses context halfway through, hallucinates findings, and leaves no artifact the next session can pick up. CodeCartographer fixes three things:Read the full README ↗The full README is unavailable right now. Read it at the original link. The saved excerpt is shown below.
Understand an unfamiliar codebase with an AI agent — and get a validated spec you can rebuild from. CodeCartographer turns a repository into layered architecture, behavioral contracts, defect findings, and a language-agnostic reimplementation spec, with each phase validated before the next one runs. Works with Pi, Claude Code, Cursor, Codex, or any MCP-capable agent.
Asking an LLM to "analyze this repo" loses context halfway through, hallucinates findings, and leaves no artifact the next session can pick up. CodeCartographer fixes three things:Read the full README ↗