Description
Is your feature request related to a problem?
Currently, Evergreen does an excellent job of managing stale PRs and automating repository hygiene through configurable policies. However, it lacks context about why a PR might be inactive, often due to a lack of review or unclear change quality. This leads to situations where pull requests are closed without any code-level feedback, which could have otherwise helped the contributor improve or re-engage.
Describe the solution you'd like
I'd love to see Evergreen support an optional AI-powered code review hook. Before acting on a PR (e.g. labeling it stale or auto-closing), Evergreen could:
- Trigger an external service (like ReviewBot AI) to - provide quick, inline GPT-based suggestions or summaries of changes.
- Post those suggestions as comments or attach them as part of Evergreen's messaging.
- Optionally add a label such as ai-feedback: needs improvement or ai-feedback: ready to merge.
This would enrich Evergreen's automation with helpful, contextual insights, keeping it lightweight but smarter.
Describe alternatives you've considered
- Manually combining Evergreen with a separate GitHub Action that runs ReviewBot AI on a PR schedule.
- Building a custom bot that mimics Evergreen’s stale policy but with AI logic added, but this loses the value of Evergreen’s well-maintained framework and policies.
- Using only Evergreen and relying on human reviewers, but that reintroduces the bottleneck Evergreen was designed to avoid.
Additional context
My project ReviewBot AI is a GitHub Action that fetches pull request diffs, runs them through OpenAI (GPT-4o), and posts automated code suggestions as comments.
By enabling an optional hook, Evergreen could trigger tools like this — or any AI analysis platform — without having to deeply integrate AI models directly into the core.
This keeps Evergreen flexible while extending its capabilities into semantic understanding of PR content.
Thanks for your consideration!
– Anish Paleja