bundle-optimizer
Analyze and reduce bundle size, implement code splitting, optimize dependencies, and improve build performance. Use when bundle is too large, load times are slow, or implementing progressive loading.
浏览 joshtol 维护的已发布 AI 技能,比较用途与说明,并通过来源仓库了解安装方式。
已收录技能
8收录技能的仓库 Stars 合计
80仓库 Forks
8平均每个技能的仓库 Stars
10同一仓库中的多个技能可能共享 Stars,合计包含重复仓库数据。
Analyze and reduce bundle size, implement code splitting, optimize dependencies, and improve build performance. Use when bundle is too large, load times are slow, or implementing progressive loading.
Integrate LLM providers (Claude, GPT, etc.) with emotive-mascot for sentiment-driven emotional responses. Use when connecting to AI services, implementing chat interfaces, or creating emotion-aware conversation...
Integrate the emotive-mascot into new use cases, applications, and frameworks. Use when adding mascot to a new page, creating custom interactions, or setting up framework-specific implementations (React, Vue, v...
Generate complete use case implementations for specific industries and scenarios. Use when creating new demo pages, implementing industry-specific mascot integrations, or exploring new application areas.
Build choreographed multi-step emotion sequences (semantic performances) for complex interactions. Use when designing welcome sequences, error recovery flows, or celebration animations.
Implement and test custom color schemes, themes, and visual variants for the emotive-mascot website and demos. Use when applying new color palettes, creating themed variants, or A/B testing visual designs.
Audit, optimize, and maintain 60fps performance for emotive-mascot animations. Use when diagnosing performance issues, optimizing particle systems, reducing bundle size, or ensuring smooth animations across dev...
Design and implement new emotion behaviors, gestures, and semantic performances for the emotive-mascot engine. Use when creating new emotions, choreographing particle movements, or designing multi-step performa...
默认按已收录数据中的 GitHub 仓库 Stars 排序。Stars 属于来源仓库,同一仓库的多个技能可能共享相同数值;它反映仓库关注度,不代表单个技能的安装量或质量评分。