Automate code review to identify correctness issues and regression risks.
npx skills add https://github.com/LinoWhy/.dotfiles --skill code-review-linowhy
Please help me install this Agent Skill. Skill: code-review Source: https://github.com/LinoWhy/.dotfiles/tree/main/agents/.agents/local-skills/code-review Command: npx skills add https://github.com/LinoWhy/.dotfiles --skill code-review-linowhy
Automates strict code reviews to identify correctness issues, potential regressions, and gaps in validation in commits, patches, or PRs.
Describe the patch or commit details and request a strict, prioritized code-review assessment.
High-intent search queries and answers about installing and using this skill.
You can automate code review by describing the commit or pull request details to receive a strict assessment that detects logic errors, edge-case failures, and missing validations, generating prioritized findings with actionable remediation guidance.
Regression risk prioritization evaluates proposed code changes to rank potential regressions by impact and likelihood, helping reviewers focus immediately on the most critical correctness issues and remediation steps.
Yes, you can review patches and commits across different repositories by providing the described changes, which the code review process evaluates for correctness issues and regression risks regardless of the specific repository context.
The best way to check for missing validations is to request a strict code review assessment of the described change, which automatically identifies gaps in validation and provides actionable remediation guidance to close them.
Yes, the code review provides actionable remediation guidance by suggesting concrete fixes and verification steps to close validation gaps and resolve identified correctness issues and regression risks.
You need to provide described changes when a direct pull request is unavailable, allowing the code review to still analyze the patch details for correctness issues, regression risks, and missing validations with prioritized findings.
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