Grepathy: Tracking AI Decisions in Code Reviews
Documents Claude's autonomous coding decisions for transparent team collaboration.
1The AI Decision Documentation Problem
Coding agents make numerous small decisions developers never explicitly approve. These rationales often get lost in chat histories. Grepathy automatically captures this context, making code reviews more transparent.
2How It Works
Grepathy reads local session transcripts, extracts AI decisions, and writes them to markdown files committed with code. This creates permanent documentation of why certain approaches were taken during development.
3Real-World Example
An AI autonomously decided to pre-create guest users in Clerk - a decision not in the original plan. Grepathy would have documented this in the repo with the rationale: 'Simplifies downstream auth checks' and required reviewer attention.
4Privacy & Security
Grepathy never sends chat transcripts off your machine. It shares only sanitized markdown summaries, automatically removing secrets and financial details through deterministic checks before you review and commit.
5Strengths and Limitations
While preserving AI decision rationales helps teams, Grepathy doesn't prevent agents from refactoring important code or make them generally smarter. It only documents context not visible in the code itself.
6Future Impact
By making AI-assisted development more transparent, Grepathy enables teams to better understand and control coding decisions. This creates more reliable development workflows as AI tools become more prevalent.