Ensure accessibility in UI components including semantic HTML, ARIA attributes, keyboard navigation, and WCAG 2.2 AA compliance.
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Provides specific version compatibility notes for NativeWind and Tailwind CSS to prevent common installation errors.
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설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
nativewind@2.0.11 and tailwindcss@3.3.2 — higher versions trigger process(css).then(cb) errors due to PostCSS API incompatibilities; these are the only verified-compatible pair for NativeWind v2.nativewind/preset in tailwind.config.js — without the preset, Tailwind compiles classes but NativeWind cannot inject them into React Native's StyleSheet engine.| Anti-Pattern | Why It Fails | Correct Approach |
|---|---|---|
| Using nativewind above 2.0.11 with tailwindcss 3.3.2 | PostCSS API mismatch triggers process(css).then(cb) runtime error; styles fail silently | Pin to nativewind@2.0.11 + tailwindcss@3.3.2; do not upgrade without migration guide |
| Upgrading only one of the two packages | Mismatched peer dependencies cause cryptic PostCSS errors | Remove both and reinstall together: npm remove nativewind tailwindcss && npm install nativewind@2.0.11 tailwindcss@3.3.2 |
Missing nativewind/preset in tailwind.config.js | Tailwind compiles classes but NativeWind cannot inject them into React Native StyleSheet; no styles applied | Add presets: [require('nativewind/preset')] to tailwind.config.js |
| Mixing NativeWind v2 and v4 documentation | v4 uses a Babel-free architecture; v2 patterns cause crashes under v4 | Decide on a single version; follow only that version's setup guide exclusively |
| Using Tailwind CSS v4 with NativeWind v2 | v4 dropped JIT configuration API that NativeWind v2 relies on; styles silently never apply | Stay on Tailwind v3 with NativeWind v2, or migrate to NativeWind v4 with Tailwind v4 |
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.
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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.
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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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