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

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?

Introducing pystdoc

I built 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.

How simple is it?

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.

Links & Docs

For advanced configurations, supported languages/parsers, caching, and engine options, check out the project:

• 📦 PyPI: pypi.org/project/pystdoc
• 🐙 GitHub: github.com/tab4moji/pystdoc

Give it a try next time someone asks you to explain mystery code. Feedback and PRs are always welcome!