gh review loop — Streamline AI reviewer feedback…

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About this project

gh-review-loop enhances the efficiency of AI reviewers by addressing their feedback directly in the terminal. It identifies all bugs pointed out across multiple comments, executes your tests before pushing, and limits iterations to prevent spamming. This tool works seamlessly with Claude Code and Codex, ensuring a smooth development experience.

gh-review-loop is a powerful tool that enhances the efficiency of code review processes by automatically addressing AI reviewer feedback on pull requests (PRs) directly from the terminal. It seeks not only the flagged issues but also identifies related concerns overlooked by the reviewer, ensuring comprehensive code integrity.

Key Features:

Comprehensive Fixes: Rather than just addressing the issues pointed out by your AI reviewer, gh-review-loop finds and rectifies all related bugs in the code, making solutions more complete.
Testing Automation: The tool automatically runs tests on the pull request before any changes are committed, preventing faulty code from being merged.
Controlled Iteration: With a hard cap of three review cycles, it ensures that the process remains manageable and avoids redundancy.
Integration with Claude Code and Codex: This skill seamlessly integrates with existing AI reviewer tools, providing enhanced functionality without requiring additional accounts or infrastructure.

How It Works:

Read Review Threads: Fetches the real-time state of review threads from GitHub and identifies actionable items.
Siblings Sweep: Clusters findings by code patterns and conducts a sweep for similar instances that may not have been flagged, ensuring no issue goes unnoticed.
Verification Gate: Automatically verifies code using predefined tests and linters before proceeding to commit and request re-review. If any checks fail, the process halts, allowing developers to address issues immediately.
Streamlined Commands: Minimal interaction is required, with just a simple command to initiate the review loop. Developers can focus on coding rather than managing review processes.

Example Usage:

Run the AI reviewer loop with the command:

Run the AI reviewer loop

With this command, the agent will process the review, apply fixes, and ensure the code is ready for further review or merging.

Conclusion:

gh-review-loop optimizes the code review workflow by automating fixes based on AI reviewer feedback while ensuring thoroughness and reliability in the commit process. It provides a structured and refined approach to managing pull requests, making it an indispensable tool for developers who leverage AI assistance in their coding practices.