Tired of Explaining Code You Didn't Even Write? Let LLMs Do It.

A developer has released pystdoc, an open-source tool that uses LLMs to automatically analyze codebases and generate structured documentation and explanations. The tool parses code, analyzes symbol relations and call graphs, and produces clear documentation, aiming to save developers time when dealing with unfamiliar code.

We've all been there. A teammate walks over or pings you on Slack with a massive chunk of unfamiliar code and asks: "Hey, can you explain what this does? Also, why does this specific edge case work like this?" Here’s the catch: You didn't write that code. You've never seen it before. Now you’re stuck spending half your afternoon digging through undocumented functions, tracking down call graphs, and trying to reverse-engineer someone else's legacy logic just to answer detailed questions. Let’s be honest: I don't want to waste my time manually reading through unfamiliar codebases. Not when LLMs exist. Manual code spelunking just to write an explanation is tedious work. So, why not let an LLM do the heavy lifting? pystdoc I built pystdoc https://github.com/tab4moji/pystdoc to completely automate this nonsense. It parses your codebase, analyzes symbol relations and call graphs, and uses LLMs to generate structured documentation and explanations for you. Just install it: pip install pystdoc Set up your LLM configuration and run it against the target directory: pystdoc run ./path/to/unfamiliar/code That's it. It analyzes the code and generates clear, detailed explanations and documentation so you don't have to decipher every single line yourself. For advanced configurations, supported languages/parsers, caching, and engine options, check out the project: Give it a try next time someone asks you to explain mystery code. Feedback and PRs are always welcome