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code-review

Performs a quick, lightweight review of a small diff or single file, giving concise feedback on correctness, readability, tests, and obvious risks. Use when the user asks for a fast sanity-check review of a small change. For test-automation suites, architectural refactors, security-sensitive paths, or multi-file reviews, use the code-review-advanced skill instead.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

jaktestowac/awesome-copilot-for-testers스타 118(GitHub 118 + cccskills 0)

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Quick Code Review

This skill applies a consistent, lightweight assessment to a small code change. It focuses on key principles of code quality:

  • Safety (avoid incorrect assumptions; call out uncertain areas)
  • Clarity (structuring comments in positive and actionable form)
  • Coverage (address correctness, tests, security, performance, readability)

When to Use

  1. The user asks for a quick review of a small diff, single file, or snippet.
  2. A change needs a fast sanity check before a fuller review.
  3. You need a compact checklist for a routine, low-risk change.

For large or multi-file pull requests, legacy audits, test-automation suites, or high-risk paths (auth, payments, data flows), use code-review-advanced instead.

Skill Behavior

  • Start with a summary: what is changing, why, and whether the implementation is aligned with goals.
  • Categorize findings:
    • ✅ Strengths / wins
    • ⚠️ Concerns / risks
    • 🛠️ Suggestions / improvements
  • Provide short-term fix guidance plus long-term design thoughts.
  • Flag any missing tests, docs, or standards violations.
  • Respect context: mention the module/file/function names (not generic: "the code").

Quick Review Checklist

  1. Correctness

    • Does the code do what the ticket/PR describes?
    • Are edge cases handled (null, errors, concurrency, format)?
    • Any regression risk from changed behavior?
  2. Maintainability

    • Is the implementation easy to read and reason about?
    • Are abstractions and naming appropriate?
    • Any repeated logic that should be refactored?
  3. Testing

    • Are unit and integration tests present and relevant?
    • Do tests cover both normal and boundary cases?
    • Are tests deterministic and fast?
  4. Security & Privacy

    • Are user inputs validated/escaped and untrusted data treated carefully?
    • Any secrets in code, logs, or config?
    • Does the change introduce new permissions, cross-origin, or auth gaps?
  5. Performance

    • Any obvious O(N^2) loops or hot-path allocations?
    • Are caching and batching used when appropriate?
    • For network I/O, is retry/backoff and timeout handling present?
  6. Style/Convention

    • Follow team linting rules and style guide (naming, indent, line length).
    • Approve clean diff with minimal noise in formatting.
  7. Documentation

    • Public APIs should be documented.
    • Migration notes, config docs, and README changes included if needed.

Output Style

  • Keep each comment concise (1-2 sentences plus the issue).
  • Use bullet points for multiple issues.
  • Use neutral, teammate-first language (Consider, Could, Would instead of You).
  • Include a final recommendation state: approve, request changes, or comment.

Related Skills

  • code-review-advanced - evidence-driven, severity-ranked review for complex, risky, or multi-file changes
  • tech-debt-analysis - when recurring review findings suggest a broader debt assessment

Definition of Done

This skill is complete when:

  • the change is summarized with intent and alignment stated
  • findings are categorized (strengths, concerns, suggestions) with concrete file/function references
  • missing tests or docs are flagged
  • a final recommendation (approve, request changes, or comment) is given

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한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

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한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

jaktestowac/awesome-copilot-for-testers1182026년 8월 27일 업데이트

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한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

jaktestowac/awesome-copilot-for-testers1182026년 8월 27일 업데이트

Measures the risk that code shipped without anyone understanding it: a teach-back attestation on high-risk changes, a risk band from changed-code complexity, diff size and whether a human explanation accompanied it, and optional AI-authorship provenance. Findings stay advisory by design. Use when an AI-assisted codebase grows faster than the team reads it, when reviews are rubber-stamped, when nobody can explain a module that ships weekly, or when leadership asks how much of the code the team can actually maintain.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

jaktestowac/awesome-copilot-for-testers1182026년 8월 27일 업데이트

Produces an evidence-backed go/no-go recommendation: exit criteria status, open-defect risk profile, coverage against risk, environment parity, rollback readiness, and the residual risk stated plainly. Use when preparing a release sign-off, when someone asks whether a build is ready to ship, or when a decision to release is being made on impressions rather than evidence.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

jaktestowac/awesome-copilot-for-testers1182026년 8월 27일 업데이트

Records human verification - code review, exploratory sessions, UAT, accessibility passes, UX and observability reviews - as dated, attributed attestations in a register, so human-centric practices stay in the quality contract without pretending to be automated checks. Use when a strategy requires verification no tool can prove, when sign-off evidence is scattered across chats and tickets, when a gap matrix needs to distinguish "attested" from "passed", or when an audit asks who verified what and when.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

jaktestowac/awesome-copilot-for-testers1182026년 8월 27일 업데이트

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