Ensure accessibility in UI components including semantic HTML, ARIA attributes, keyboard navigation, and WCAG 2.2 AA compliance.
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Code quality expert including clean code, style guides, and refactoring
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查看安装方法安装前可以查看交给 AI 代理的指令内容。
When reviewing or writing code, apply these guidelines:
When reviewing or writing code, apply these guidelines:
When reviewing or writing code, apply the principles above consistently. Focus on:
This expert skill consolidates 1 individual skills:
| Anti-Pattern | Why It Fails | Correct Approach |
|---|---|---|
| Magic numbers in logic | if (status === 200) is opaque; value could change | Extract to const HTTP_OK = 200 with clear name |
| Comments explaining "what" not "why" | Code changes make comments stale and misleading | Write self-documenting code; comment only design rationale |
| God functions (>50 lines, multiple concerns) | Hard to test, debug, and modify independently | Extract single-purpose functions with clear names |
| Premature optimization | Adds complexity before proving a bottleneck exists | Profile first; only optimize measured hot paths |
| Duplicated code blocks | Bug fixes must be applied in N places | Extract to reusable function; DRY principle |
Before starting:
cat .claude/context/memory/learnings.md
After completing: Record any new patterns or exceptions discovered.
ASSUME INTERRUPTION: Your context may reset. If it's not in memory, it didn't happen.
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Ensure accessibility in UI components including semantic HTML, ARIA attributes, keyboard navigation, and WCAG 2.2 AA compliance.
中文简介正在准备中。当前显示原文说明。
Use when you want to improve response quality through meta-cognitive reasoning. Applies 15+ reasoning methods to reconsider and refine initial outputs.
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N-round opposing-stance debates for trade-off analysis. Assigns pro/con roles to agents, runs structured debate rounds with quality scoring, and produces a moderator synthesis with confidence-rated recommendation. Generalizable to architecture, technology, security, and design decisions.
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Force adversarial code review stance that eliminates confirmation bias — reviewer must find issues or re-analyze
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Creates specialized AI agents on-demand when no existing agent matches a request. Use when the Router cannot find a suitable agent for a task. Enables self-evolution by generating persistent agents.
中文简介正在准备中。当前显示原文说明。
LLM-as-judge evaluation framework with 5-dimension rubric (accuracy, groundedness, coherence, completeness, helpfulness) for scoring AI-generated content quality with weighted composite scores and evidence citations
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