Review entire codebases and publish confirmed findings as GitHub issues.
npx skills add https://github.com/LaiTszKin/apollo-toolkit --skill review-codebases
Please help me install this Agent Skill. Skill: review-codebases Source: https://github.com/LaiTszKin/apollo-toolkit/tree/main/review-codebases Command: npx skills add https://github.com/LaiTszKin/apollo-toolkit --skill review-codebases
Repository-wide code review workflows that require reading the full codebase before judging, prioritize architecture findings over implementation details, and surface a reproducible set of confirmed findings ready for publication via open-github-issue.
Use the review-codebases skill to perform a full repository audit and publish issues for each confirmed finding.
High-intent search queries and answers about installing and using this skill.
Automate a full repository codebase audit by reading the entire project, prioritizing architecture findings over implementation details, and publishing one GitHub issue per confirmed finding with structured, reproducible fields.
An architecture review for a large codebase should read the entire repository first, prioritize system design findings, then code quality, stopping when a higher tier has confirmed findings to ensure governance-ready evaluation.
Automated maintainability assessment evaluates the entire repository by extracting architecture findings, evaluating code quality, and generating deterministic, reproducible reports suitable for project-level governance.
Yes, you can review large repositories by enforcing a full-repo read before judgment, then using the open-github-issue dependency to publish one structured issue per confirmed architectural or maintainability finding.
Yes, the code review process prioritizes architecture and system design first, then code quality, then edge cases, stopping evaluation when a higher tier yields confirmed findings to focus on structural integrity.
Limitations include stopping the review when a higher tier confirms findings, deferring lower-tier edge cases as follow-ups, and restricting publication solely to the open-github-issue format for confirmed findings.
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