Automate iterative fixing of code review findings in git feature branches.
npx skills add https://github.com/machow/dev-skills --skill roborev-refine
Please help me install this Agent Skill. Skill: roborev-refine Source: https://github.com/machow/dev-skills/tree/main/roborev-refine Command: npx skills add https://github.com/machow/dev-skills --skill roborev-refine
Automates the process of diagnosing and fixing code review findings by continuously iterating until all reviews pass, enabling hands-off code quality improvement.
Run roborev refine to start the automated review-fix loop on your current feature branch.
High-intent search queries and answers about installing and using this skill.
Automating code review fixes involves running an iterative agent that diagnoses findings, applies fixes, commits them, and waits for re-review until all checks pass. This process targets feature branches and repeats up to 10 iterations by default.
Handling per-commit and branch-level code reviews requires an automated loop that first resolves per-commit findings, then runs a branch-level review to address any remaining branch-wide issues. This ensures comprehensive continuous quality improvement.
Yes, running an automated code review fixer without modifying your working directory is possible because the agent operates in an isolated git worktree. This isolated environment keeps your primary working tree completely clean during the iterative fixing process.
To automate iterative code review fixes you need a clean working tree within a git repository and the roborev tool installed. These prerequisites ensure the automated agent can safely apply commits and manage the feature branch without conflicts.
Automated code review fixing manages resolution limits by running up to 10 iterations by default to resolve per-commit findings before stopping. You can also adjust this limit using options like --max-iterations and --since to control the scope.
An automated code review loop requires a clean working tree to ensure the isolated agent can safely commit fixes to the feature branch without overwriting uncommitted local changes. This prevents data loss during the iterative commit process.
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