AI Code Reviewer Tool Built With Attempt Limits to Prevent Infinite Review Loops

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A developer has built a local AI-powered code review tool called frontier-simplify that addresses a common failure mode where automated reviewers loop endlessly without reaching a conclusion. The tool retains findings across multiple review rounds so each subsequent pass can check whether specific issues were actually fixed, rather than re-examining the entire pull request from scratch. It caps automated review at three attempts, after which it hands off a structured summary — including original findings and repair evidence — to a human reviewer without taking any action like merging or posting comments. The attempt limit is a practical safety backstop, not a quality guarantee, and the tool is designed as an optional local maintainer utility rather than a hosted service or merge gate. The developer acknowledges an unresolved challenge: if an AI model both defines the review scope and judges its own findings against it, it may rationalize expanding the task beyond what the limit is meant to prevent.

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