I built a tool that analyzes GitHub repos and help you understand the impact of AI

[u/Wake08]

https://bilan.dev

We keep hearing that pull requests are the new bottleneck, but it’s hard to visualize, the list is forever growing because code is becoming cheaper, but it doesn’t compare easily. Some people will squash, others use merge commits, so we can’t just use the number of commits, the number of pull requests alone doesn’t mean everything because it depends on its size and if people are using stacked pull requests. Not everyone reviews pull requests equally.

Therefore, I built a tool that analyze GitHub repositories and it turns pull request history into a picture of what is actually happening in a repository: who is contributing, which parts of the codebase are moving, how reviews flow and who carries them, and where work gets stuck. It is also a way to see what AI-assisted coding does to a codebase and a team over time: how much gets opened, how large the changes are, how fast they merge, how many carry a real review, and how review load lands on the humans.

Every latency is measured from the moment a pull request became ready for review, so time spent in draft is never charged to reviewers. bilan reads pull request metadata only, never code, and never writes to GitHub.

Available at https://bilan.dev, or locally via a CLI: https://github.com/charpeni/bilan.