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Repositório GitHub

claude-tools

claude-tools contém 3 skills coletadas de JNLei, com cobertura ocupacional por repositório e páginas de detalhe dentro do site.

skills coletadas
3
Stars
20
atualizado
2025-11-20
Forks
5
Cobertura ocupacional
2 categorias ocupacionais · 100% classificado
explorador de repositórios

Skills neste repositório

frontend-design
Designers gráficos

Create distinctive, production-grade frontend interfaces with exceptional design quality. Two modes - (1) New projects - bold aesthetic design philosophy including typography, color theory, spatial composition, motion design, visual details, avoiding generic AI aesthetics, creating unforgettable interfaces. (2) Existing codebases - mandatory design language analysis enforcing consistency by scanning layout patterns, typography hierarchy, component structure, spacing, theme systems before implementation. Use when building components, pages, applications, design systems, UI modifications. Covers React, Vue, Next.js, HTML/CSS, Tailwind. Keywords - create component, build page, design interface, add UI, aesthetic design, visual design, typography, animations, spatial layout, design system, consistency, pattern analysis, existing codebase.

2025-11-20
skill-developer
Desenvolvedores de software

Create and manage Claude Code skills following Anthropic best practices. Use when creating new skills, modifying skill-rules.json, understanding trigger patterns, working with hooks, debugging skill activation, or implementing progressive disclosure. Covers skill structure, YAML frontmatter, trigger types (keywords, intent patterns, file paths, content patterns), enforcement levels (block, suggest, warn), hook mechanisms (UserPromptSubmit, PreToolUse), session tracking, and the 500-line rule.

2025-11-20
skill-optimizer
Desenvolvedores de software

Optimize Claude Code skills for token efficiency using progressive disclosure and content loading order. Use when optimizing skills, reducing token usage, restructuring skill content, improving skill performance, analyzing skill size, applying 500-line rule, implementing progressive disclosure, organizing reference files, optimizing YAML frontmatter, reducing context consumption, improving skill architecture, analyzing token costs, splitting large skills, or working with skill content loading. Covers Level 1 (metadata), Level 2 (instructions), Level 3 (resources) loading optimization.

2025-11-20