Periodically analyze open pull requests for CI failures, code review feedback, and quality issues, then fix them in batch. Use this skill when the user asks to check PR status, triage CI failures, fix review comments, analyze open PRs, or run a scheduled PR health check across the repository.
npx skills add https://github.com/TencentCloudBase/CloudBase-AI-Toolkit --skill pr-review-fix
Systematically analyze open pull requests for CI failures, code review feedback, and code quality issues — then fix them efficiently.
Use this skill when you need to:
Do NOT use for:
references/discovery.md for the full discovery procedure. gh pr list --state open --json number,title,headRefName,statusCheckRollup,reviewDecision,mergeable --limit 30
references/triage.md for prioritization rules.references/fix-workflow.md for the fix procedure.a. Stash current work: git stash
b. Check out the PR branch: git checkout -B <branch> github/<branch>
c. Reproduce the issue locally (build, test, or lint)
d. Apply the fix
e. Verify locally: build → test → lint
f. Commit with conventional-changelog format: fix(<scope>): 🔧 <description>
g. Push: git push github <branch>
h. Return to original branch: git checkout <original> && git stash pop
gh pr checks <number>
| Task | Read |
| --- | --- |
| Discover and list open PR status | references/discovery.md |
| Prioritize which PRs to fix first | references/triage.md |
| Execute fixes on PR branches | references/fix-workflow.md |
| Understand project CI pipeline | references/ci-pipeline.md |
| Common fix patterns and recipes | references/fix-recipes.md |
Follow the project's conventional-changelog format:
fix(<scope>): 🔧 <english description>
Where <scope> is the affected module (e.g., cloudrun, security, code-quality, test).
Use when receiving code review feedback, before implementing suggestions, especially if feedback seems unclear or technically questionable - requires technical rigor and verification, not performative agreement or blind implementation
Use when completing tasks, implementing major features, or before merging to verify work meets requirements
Execute git commit with conventional commit message analysis, intelligent staging, and message generation. Use when user asks to commit changes, create a git commit, or mentions "/commit". Supports: (1) Auto-detecting type and scope from changes, (2) Generating conventional commit messages from diff, (3) Interactive commit with optional type/scope/description overrides, (4) Intelligent file staging for logical grouping
Comprehensive GitHub code review with AI-powered swarm coordination
Behavioral guidelines to reduce common LLM coding mistakes. Use when writing, reviewing, or refactoring code to avoid overcomplication, make surgical changes, surface assumptions, and define verifiable success criteria.
Use this skill to review code. It supports both local changes (staged or working tree) and remote Pull Requests (by ID or URL). It focuses on correctness, maintainability, and adherence to project standards.
Refactor bloated AGENTS.md, CLAUDE.md, or similar agent instruction files to follow progressive disclosure principles. Splits monolithic files into organized, linked documentation.
Create high-quality git commits: review/stage intended changes, split into logical commits, and write clear commit messages (including Conventional Commits). Use when the user asks to commit, craft a commit message, stage changes, or split work into multiple commits.
Take tencentcloudbase/pr-review-fix from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.