Protocol_Brief
Challenge
Commit messages are often vague. I wanted to use AI to automatically infer intent and summarize changes accurately.
Solution
A multi-stage agentic pipeline that analyzes diffs and groups them by architectural impact.
“GitScripe was born from my curiosity about LLM agents. I wanted to see if I could build a system that doesn't just list commits, but actually 'understands' the intent behind them. I learned how to orchestrate multiple agents (Analyzer, Summarizer, Critic) and implemented a RAG pipeline so I could chat with my own codebase history.”
- Built a multi-agent pipeline to process and critique Git diffs for better summaries.
- Implemented a RAG (Retrieval-Augmented Generation) system for repository-aware chat.
- Learned background job orchestration with Redis and BullMQ for processing large repos.
- Developed a GitHub-style dark UI to present AI insights in a familiar developer context.