stym06
Joined 4 years ago
Joined 4 years ago
The idea is simple: take any GitHub URL, add “quick” before github.com, and get AI-generated system design documentation in under 60 seconds.
github.com/vercel/next.js → quickgithub.com/vercel/next.js
The generated docs include a system overview, architecture breakdown, key modules, tech stack, entry points, and dependencies.
There’s also a Q&A chat to ask follow-up questions about the repo.
Why I built this:
I think we’re heading toward a world where most code is written by AI agents, and the bottleneck shifts from writing code to understanding what was written. Traditional docs assume a human author. I wanted something that could explain any codebase instantly, regardless of who (or what) wrote it.
Some details: * Each repo is indexed once and cached permanently * Login required via GitHub OAuth (one free repo per account) * All generated docs are public by default * It’s open source: github.com/stym06/quickgithub
Would love feedback on the quality of the generated docs.
Try it on a repo you know well and tell me where it gets things wrong. that’s the most useful feedback I can get.
An open-source text-to-SQL platform that lets you query data warehouses in plain English. It currently supports ClickHouse.
https://github.com/stym06/kepler
1. Ask a question in natural language 2. Kepler finds relevant tables and recalls past learnings 3. The AI agent generates SQL, executes it read-only, and validates results 4. Results appear with suggested charts when appropriate
It features persistent memory - it learns corrections, schema notes, and patterns across sessions, implemented using Qdrant + Ollama (nomic-embed-text).
Based on a recent research paper published by OpenAI https://openai.com/index/inside-our-in-house-data-agent/
for filters, create a set of pre-defined tags and let the LLM choose one of your pre-defined tags from the paper's summary.