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frontend-expert-review
by mmrakt
⭐ 0🍴 0📅 Jan 21, 2026
SKILL.md
name: frontend-expert-review description: Expert-level frontend code review workflow focusing on maintainability, security, performance, and accessibility. Use when reviewing frontend diffs, PRs, components, SPAs, UI logic, or framework-specific code (React/Next.js, Vue, Svelte, Angular, etc.) and when producing structured findings with severity, file/line references, and actionable recommendations.
Frontend Expert Review
Overview
Provide an expert-grade frontend review with findings prioritized by maintainability, then security, then performance and accessibility (equal weight). Keep feedback precise, actionable, and grounded in file/line evidence.
Workflow
1) Confirm scope and context
- Identify the target files, user flows, and environments (SSR/CSR, mobile/desktop, browser support, i18n, theming).
- Note constraints and missing context; ask focused questions when assumptions would materially affect the review.
2) Load the correct references
- Always read
references/general.mdfor cross-cutting checks. - For framework-specific guidance, read the matching file:
- React:
references/react.md - Next.js:
references/next.md - Vue:
references/vue.md - Svelte:
references/svelte.md - Angular:
references/angular.md
- React:
- If Next.js is involved, also read
references/react.md(Next.js reviews are React reviews too). - If React/Next.js is involved, also read
.codex/skills/vercel-react-best-practices/SKILL.mdand apply its guidance. Treat it as a performance-oriented sub-skill and merge the outputs into one coherent review (do not duplicate findings).
3) Review in priority order
- Maintainability: architecture, boundaries, state/data flow clarity, naming, consistency, typing, error handling, testability.
- Security: XSS/injection risk, unsafe DOM APIs, auth/session handling in client code, secrets exposure, dependency risk.
- Performance & Accessibility (equal): bundle impact, rendering costs, hydration, caching, interaction latency; semantics, keyboard, focus management, ARIA, contrast.
4) Record each finding with evidence
For every issue, include:
- Severity (Critical/High/Medium/Low)
- Category (Maintainability/Security/Performance/Accessibility)
- Location (file path + line)
- Rationale and risk
- Specific fix or alternative approach
5) Close the loop
- Recommend tests or checks that would prevent regressions (unit/e2e/a11y/perf). If no tests are appropriate, say so explicitly.
- If uncertainty remains, list questions and assumptions separately.
Output format
Use this format unless the user requests otherwise:
Findings
- [Severity][Category]
path:line— issue summary. Evidence/risk. Recommendation.
Questions / Assumptions
- ...
Suggested tests or checks
- ...
References
references/general.md(always)- Framework-specific references in
references/
Score
Total Score
50/100
Based on repository quality metrics
✓SKILL.md
SKILL.mdファイルが含まれている
+20
○LICENSE
ライセンスが設定されている
0/10
○説明文
100文字以上の説明がある
0/10
○人気
GitHub Stars 100以上
0/15
○最近の活動
3ヶ月以内に更新がある
0/10
○フォーク
10回以上フォークされている
0/5
✓Issue管理
オープンIssueが50未満
+5
✓言語
プログラミング言語が設定されている
+5
○タグ
1つ以上のタグが設定されている
0/5
Reviews
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Reviews coming soon