1. d-yoda Jan 5, 2026 parent

   I built a GitHub App that monitors your Python codebase for quality issues.

   It reviews PRs and runs weekly audits on the entire repo. When it finds problems, it posts them as comments or Issues with concrete suggestions.

   I open-sourced pyscn ([https://github.com/ludo-technologies/pyscn](https://github.com/ludo-technologies/pyscn)) a few months ago. I liked what it could do, but wanted to make it more accessible and more powerful. Combining it with an LLM felt like the right next step. pyscn-bot is the result.

   It catches things like complex functions, dead code, and duplicated logic. It can also analyze your entire codebase architecture, something most review bots can't do since they only look at diffs.

   Happy to answer questions.

2. 2 points Jan 5, 2026

   Show HN: An AI agent that audits your entire Python codebase

   1 comment d-yoda ludo-tech.org
3. d-yoda Dec 30, 2025 parent

   So what happens when they swap Claude for Llama under the hood?
4. d-yoda Oct 8, 2025 parent

   Thanks! I will fix the issue as soon as I can in the next version.
5. d-yoda Oct 8, 2025 parent

   Yes, that's definitely something I'm looking into. I've received a few comments about AI coding integrations, so it's becoming a high priority.
6. d-yoda Oct 8, 2025 parent

   This is super insightful, thank you for sharing. It's a great list of common LLM-generated anti-patterns.

   I'd love to look into incorporating checks for these into pyscn. This is exactly the kind of stuff I want it to catch.

7. d-yoda Oct 8, 2025 parent

   Wow, was it really in some newsletters? That's awesome to hear, and would definitely explain the recent spike on GitHub!

   Thanks a lot for the bug report and for providing the details. I have a hunch—it's possible that you need to explicitly specify the path depending on your directory structure. For example, if your Python files are under a src directory, could you try running it like [your_tool_name] analyze src/?

   If that still doesn't solve the problem, it would be a huge help if you could open a quick issue on GitHub for this.

   Thanks again for your feedback!

8. d-yoda Oct 6, 2025 parent

   Thanks for trying it out! For the progress bar bug, would you mind opening a GitHub issue with details? That'll help us track it down.

   Great idea using it as grounding for AI-assisted refactoring! Let us know how that workflow goes.

9. d-yoda Oct 6, 2025 parent

   Haha, maybe your code is better than you think! But seriously, we'd love to hear if the thresholds feel too lenient. Feedback welcome!
10. d-yoda Oct 5, 2025 parent

    Thanks for sharing! Good to know about rust-code-analysis. Always helpful to see what other tools are doing in this space.
11. d-yoda Oct 5, 2025 parent

    Fair point! My initial target was engineers using AI, but I'm open to refining the messaging.
12. d-yoda Oct 5, 2025 parent

    MCP integration could be a good option. If there's interest, feel free to raise an issue on GitHub.
13. d-yoda Oct 5, 2025 parent

    Pylint's duplication check is text-based (compares lines), while pyscn uses tree edit distance on ASTs. This means pyscn can catch structural clones even when variable/function names differ.
14. d-yoda Oct 5, 2025 parent

    They complement each other - Ruff for style, pyscn for architecture. pyscn focuses on structural quality - checking if your code follows fundamental design principles like DRY, YAGNI, or other best practices.
15. d-yoda Oct 5, 2025 parent

    Rust is definitely the king of performance! I personally love Go, but Rust's performance is truly impressive.
16. d-yoda Oct 5, 2025 parent

    Glad you like it! Trying to make it as user-friendly as possible.
17. d-yoda Oct 5, 2025 parent

    Yes! tree-sitter supports multiple languages and the core algorithms should transfer easily. I focused on Python first because I saw many people struggling with code quality issues in Python.
18. d-yoda Oct 5, 2025 parent

    Not yet! But the algorithms should transfer well - the core logic supports TypeScript, so it's definitely doable.
19. d-yoda Oct 5, 2025 parent

    Yeah Go is very fast!
20. d-yoda Oct 5, 2025 parent

    I'm actually more optimistic. While Python/JS have huge ecosystems, there are still things only Go/Rust can achieve.
21. d-yoda Oct 5, 2025 parent

    Great point! Golang is indeed one of those languages with strong "vibe coding resistance" - it's personally one of my favorites for that reason. On the flip side, I think there's a future where tools like pyscn work alongside AI to make languages with large communities like Python even more dominant.
22. d-yoda Oct 5, 2025 parent

    Thank you! I'll keep improving it more and more!
23. d-yoda Oct 5, 2025 parent

    "You're absolutely right!" - the messaging could be clearer. I built pyscn because more engineers than expected are using AI assistants these days (to varying degrees), and I wanted to give them a tool to check code quality. But the real value might be for engineers who inherit or maintain AI-generated codebases as you say, rather than those actively vibe coding.
24. d-yoda Oct 5, 2025 parent

    Thank you! 1.For tree edit distance, I referred to "APTED: A Fast Tree Edit Distance Algorithm" (Pawlik & Augsten, 2016), but the algorithm works as O(n²) so I also implemented LSH (classic one) for large codebases.The other analyses also use classical compiler theory and techniques. 2. Should be straightforward! tree-sitter gives us parsers for 40+ languages. CFG construction is just tracking control flow, and the core algorithm stays the same.

    I focused on Python first because vibe coding with Python tends to accumulate more structural issues. But the same techniques should apply to other languages as well.

    Excited about the Qlty integration - that would make pyscn much more accessible and would be amazing!

25. 136 points Oct 5, 2025

    Show HN: Pyscn – Python code quality analyzer for vibe coders

    84 comments d-yoda github.com

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