AI chat and feedback - Autter

Autter provides conversational codebase help and actionable feedback inside the review workflow.

Pull request feedback

When Autter finds a problem, the comment should explain:

what behavior is affected
why the behavior is risky or inconsistent
which repository context supports the finding
how the author can fix or investigate it

Placeholder showing an Autter pull request comment with codebase context and a proposed fix — Placeholder: replace with an approved AI feedback screenshot.

Codebase questions

Use AI chat to ask about complex logic, architecture, repository patterns, or a proposed change. Useful questions include:

Where is authorization enforced for this route?
Which services call this module?
What pattern does this repository use for retries?
Why does this pull request change the cache invalidation path?
Which tests cover the failure mode in this finding?

Ask focused questions and name the relevant module or behavior. Specific questions make it easier to verify the answer against code.

Suggested fixes

Autter can propose concrete fixes for review findings. Before applying one:

Confirm it addresses the reported behavior.
Check that it follows repository conventions.
Run the relevant tests and static checks.
Review the final diff for unrelated changes.

A suggested fix is generated code. Treat it as a proposal, not as a verified patch.

Improve the feedback

write narrow, testable review rules
connect relevant issues and documentation
keep pull requests focused
use thumbs feedback where available to help calibrate results
revise rules that repeatedly flag valid code