When the AI reviewer finds low-risk issues — formatting, naming conventions, simple bugs — it commits the fix automatically. Higher-risk findings still go through human review.
CodeRaven Auto-Fix is an automated code correction feature that detects low-risk issues during AI code review (formatting, naming, simple bugs) and commits fixes directly to the pull request. A configurable risk threshold determines which issues are auto-fixed and which require human review. Every auto-fix is logged in a full audit trail.
Code reviews often surface the same types of low-risk issues repeatedly: inconsistent formatting, wrong naming conventions, missing semicolons, unused imports, or simple null checks. These findings are important for code quality, but they create noise in review threads and waste developer time on mechanical fixes.
CodeRaven Auto-Fix handles these issues automatically. During AI code review, each finding is classified by risk level — low, medium, or high. Issues below your configured risk threshold are fixed by the AI, which commits the correction directly to the pull request branch. Higher-risk findings — logic changes, security concerns, architectural decisions — are always posted as review comments for human judgment.
You have full control over the threshold. Set it conservatively to only auto-fix formatting issues, or open it up to handle simple bug fixes and naming violations. The risk threshold can be configured per repository, so different projects can have different levels of automation. Every auto-fix is logged in a full audit trail showing the original finding, the applied fix, and the risk classification.
Real outcomes that improve how your team builds software.
Auto-fix handles formatting, naming, and import issues so review comments focus on logic, architecture, and design decisions.
PRs with only low-risk issues are cleaned up automatically, reducing the number of review-fix-review cycles.
Set the auto-fix threshold per repository. Only the issues you're comfortable automating get fixed automatically.
Every auto-fix is logged with the original finding, applied fix, and risk classification. Review the complete history at any time.
No complex setup required — connect your tools and start seeing results.
During code review, the AI identifies issues and classifies each finding by risk level — low, medium, or high.
Issues below your configured risk threshold are fixed automatically. The AI commits the fix directly to the PR branch.
Higher-risk findings are posted as review comments for human review. You decide whether to accept, modify, or dismiss each suggestion.
Automatically fix formatting issues, import ordering, and naming convention violations so reviews can focus on logic and architecture.
Catch and fix common mistakes automatically while surfacing educational comments on more complex issues.
Reduce reviewer fatigue on repos with frequent PRs by auto-fixing trivial issues and only flagging meaningful problems.
See it in action — no credit card required.
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