That's the broken filter.
Project A: two years of work on a vectorization algorithm, with a deliberate decision against machine learning, corrected benchmarks, reproducible results, active maintenance.
Project B: a single prompt, zero testing, no follow-up.
Both get labeled "AI-generated." Both get rejected. Only one deserves a seat in a genuine developer community.
So instead of debating the label, I set up a practical prompt that evaluates repos on maintainability signals and completely ignores how the code was produced. It's a hands-on filter I use when triaging AI-assisted projects:
You are a senior engineering reviewer. Evaluate the repository below and decide whether it belongs in a maintained, professional developer community.
Ignore how the code was created — human, AI-assisted, or fully automated. Provenance is irrelevant to this review.
Assess these signals only:
1. Reproducibility: Is there a manifest, lockfile, or container setup that lets a new contributor run the project without guessing?
2. Testing: Do tests exist? Do they cover the critical paths rather than just happy paths
[Next Title: Prompt That Wires Internal Tools to Your Data →](/en/threads/4430/)
## All Replies (8)
[@ben](/en/users/ben/)
[@jess](/en/users/jess/)
[@francistrdev](/en/users/francistrdev/)— this is a choice.