pacificstudio/openase/review-code
Trust tier 2
- community
Source check pending
Checking that the SKILL.md file is still in the repository.
Review behavior, risk, performance, and test coverage before style nits.
Install
npx vskill@latest install pacificstudio/openase/review-codeSKILL.md
Review Code
Overview
Conduct a thorough code review for quality, security, performance, and maintainability. Focus on the real risks first, then provide concrete, severity-rated feedback with file and line references where possible.
When To Use
- Before merging a pull request.
- After implementing a feature or refactor.
- When the user asks for a review of changed files or a branch.
- When the code looks correct at first glance but may still hide regressions or design debt.
Review Workflow
- Identify the review scope.
- Review the current diff, named files, or the whole change set.
- Prefer reviewing the actual changed surface before expanding further.
- Check behavioral correctness first.
- Regressions against existing behavior.
- Missing edge-case handling.
- Broken invariants or data consistency risks.
- Review the main quality categories.
- Security risks.
- Code quality and complexity.
- Performance concerns.
- Error handling and observability.
- Maintainability, coupling, and testability.
- Evaluate the test story.
- Are the important paths covered?
- Are the tests proving behavior rather than implementation trivia?
- Is there an obvious missing regression test for the change?
- Rate findings by severity.
CRITICAL: must fix before merge; security or correctness issue with serious impact.HIGH: should fix before merge; likely bug, major regression risk, or serious design flaw.MEDIUM: worthwhile fix; non-blocking but meaningful quality issue.LOW: suggestion, cleanup, or style improvement.
- Report findings in priority order.
- File and line reference.
- What is wrong.
- Why it matters.
- Concrete fix guidance.
Review Categories
- Security: secrets, unsafe input handling, authz gaps, injection, XSS, CSRF.
- Code quality: complexity, duplication, large functions, fragile branching.
- Performance: avoidable repeated work, inefficient algorithms, N+1 patterns, unnecessary re-renders.
- Maintainability: unclear naming, tight coupling, hidden assumptions, hard-to-test logic.
- Reliability: missing error handling, weak retries, silent failures, incomplete logging.
Operating Rules
- Lead with findings, not praise.
- Prioritize behavior and risk before style nits.
- Prefer evidence and concrete examples over general taste.
- If there are no findings, say so explicitly and still mention residual risks or test gaps.
- Keep recommendations actionable enough that another engineer can implement them directly.
Default Deliverable Shape
Return these sections:
Findings- ordered by severity, each with file and line references.Open Questions / Assumptions- only if they affect confidence.Residual Risks- what was not fully proven by the review.Short Summary- brief overall assessment after the findings.
Security
- Security scanPassed, 100 of 100Pattern checks on the skill's files.
- Model reviewNot runA model review is scheduled for the next rescan.
Quality evaluation
- Task evaluationNot runNo evaluation yet. Run one in Skill Studio.
Source
- SKILL.md in the repositoryCheckinginternal/builtin/skills/review-code/SKILL.md
Popularity
- Repository stars
- 261
- Repository forks
- 25
- 7-day trend score
- 28
Stars and forks are for the whole GitHub repository, not this skill alone. Not refreshed yet.
Works with
Any agent vskill installs to: 56 targets in all. These 39 have a page on this site.
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- AI Agent
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- Amazon Q
- Firebase Genkit
- Sweep
- Devin
- Phind
- Mentat
- Claude Desktop
- Aider
- GPT Pilot
- Plandex
- bolt.new
- v0
- Replit Agent
- Anse
- TypingMind
- BetterChatGPT
- LibreChat
- Warp AI
- Pieces
- Fig AI
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