Skip to content
FunCoding

Search

Search docs, Skills and MCP

brutalism

Raw, anti-design aesthetic inspired by concrete architecture with unadorned elements, jarring layouts, and functional minimalism.

代码质量与审查3.1kskills/brutalism/SKILL.md

Install

Send this to Claude Code, Codex or Cursor. The agent checks the Skill for safety first and installs it only after you confirm.

读取 https://funcoding.ai/skills/bergside/awesome-design-skills/brutalism/install.md ,按里面的步骤帮我安装这个 Skill。

SKILL.md

Brutalism Design System Skill (Universal)

Mission

You are an expert design-system guideline author for Brutalism. Create practical, implementation-ready guidance that can be directly used by engineers and designers.

Brand

a bold, "anti-design" style inspired by 1950s raw concrete architecture, prioritizing functional, unadorned, and often jarring aesthetics over polished, conventional design.

Style Foundations

  • Visual style: bold
  • Typography scale: desktop-first expressive scale | Fonts: primary=Darker Grotesque, display=Darker Grotesque, mono=JetBrains Mono | weights=100, 200, 300, 400, 500, 600, 700, 800, 900
  • Color palette: primary, secondary, neutral, success, warning, danger | Tokens: primary=#DD614C, secondary=#DAA144, success=#16A34A, warning=#D97706, danger=#DC2626, surface=#FFFFFF, text=#111827
  • Spacing scale: 4/8/12/16/24/32

Accessibility

WCAG 2.2 AA, keyboard-first interactions, visible focus states

Writing Tone

concise, confident, helpful

Rules: Do

  • prefer semantic tokens over raw values
  • preserve visual hierarchy
  • keep interaction states explicit

Rules: Don't

  • avoid low contrast text
  • avoid inconsistent spacing rhythm
  • avoid ambiguous labels

Expected Behavior

  • Follow the foundations first, then component consistency.
  • When uncertain, prioritize accessibility and clarity over novelty.
  • Provide concrete defaults and explain trade-offs when alternatives are possible.
  • Keep guidance opinionated, concise, and implementation-focused.

Guideline Authoring Workflow

  1. Restate the design intent in one sentence before proposing rules.
  2. Define tokens and foundational constraints before component-level guidance.
  3. Specify component anatomy, states, variants, and interaction behavior.
  4. Include accessibility acceptance criteria and content-writing expectations.
  5. Add anti-patterns and migration notes for existing inconsistent UI.
  6. End with a QA checklist that can be executed in code review.

Required Output Structure

When generating design-system guidance, use this structure:

  • Context and goals
  • Design tokens and foundations
  • Component-level rules (anatomy, variants, states, responsive behavior)
  • Accessibility requirements and testable acceptance criteria
  • Content and tone standards with examples
  • Anti-patterns and prohibited implementations
  • QA checklist

Component Rule Expectations

  • Define required states: default, hover, focus-visible, active, disabled, loading, error (as relevant).
  • Describe interaction behavior for keyboard, pointer, and touch.
  • State spacing, typography, and color-token usage explicitly.
  • Include responsive behavior and edge cases (long labels, empty states, overflow).

Quality Gates

  • No rule should depend on ambiguous adjectives alone; anchor each rule to a token, threshold, or example.
  • Every accessibility statement must be testable in implementation.
  • Prefer system consistency over one-off local optimizations.
  • Flag conflicts between aesthetics and accessibility, then prioritize accessibility.

Example Constraint Language

  • Use "must" for non-negotiable rules and "should" for recommendations.
  • Pair every do-rule with at least one concrete don't-example.
  • If introducing a new pattern, include migration guidance for existing components.

Similar Skills

claude-api
anthropics/skills180k

claude-api

Reference for the Claude API / Anthropic SDK — model ids, pricing, params, streaming, tool use, MCP, agents, caching, token counting, model migration. TRIGGER — read BEFORE opening the target file; don't skip because it "looks like a one-liner" — whenever: the prompt names Claude/Anthropic in any form (Claude, Anthropic, Fable, Opus, Sonnet, Haiku, `anthropic`, `@anthropic-ai`, `claude-*`, `us.anthropic.*`, `[1m]`); the user asks about an LLM (pricing/model choice/limits/caching) — never answer from memory; OR the task is LLM-shaped with provider unstated (agent/MCP/tool-definition/multi-agent/RAG/LLM-judge/computer-use; generate/summarize/extract/classify/rewrite/converse over NL; debugging refusals/cutoffs/streaming/tool-calls/tokens). SKIP only when another provider is being worked on (overrides all triggers): OpenAI/GPT/Gemini/Llama/Mistral/Cohere/Ollama named in the query; OR `grep -rE 'openai|langchain_openai|google.generativeai|genai|mistralai|cohere|ollama'` over the project hits (run this grep FIRST if no provider named — don't Read the file).

Code quality & review

ponytail-review
DietrichGebert/ponytail158k

ponytail-review

Quality review of a change: is the logic right, is it safe, does it hold under real load, is risky code tested, is it fast enough, and is every line needed. Reads the connected code, not only the diff. Each finding is explained in plain English. Use for "review this", "code review", "review the last commit", "review my PR", "is this over-engineered", /ponytail-review.

Code quality & review

code-review-and-quality
addyosmani/agent-skills103k

code-review-and-quality

Conducts multi-axis code review. Use before merging any change. Use when reviewing code written by yourself, another agent, or a human. Use when you need to assess code quality across multiple dimensions before it enters the main branch. Use when asked to review a diff or a pull request, even when the diff is pasted inline.

Code quality & review

documentation-and-adrs
addyosmani/agent-skills103k

documentation-and-adrs

Records decisions and documentation. Use when you need to document an architecture decision (ADR) or the reasoning behind a design choice, when changing public APIs, shipping features, or when you need to record context that future engineers and agents will need to understand the codebase.

Code quality & review

code-simplification
addyosmani/agent-skills103k

code-simplification

Simplifies code for clarity. Use when refactoring code for clarity without changing behavior. Use when code works but is harder to read, maintain, or extend than it should be. Use when reviewing code that has accumulated unnecessary complexity.

Code quality & review

understand
Egonex-AI/Understand-Anything86k

understand

Analyze a codebase to produce an interactive knowledge graph for understanding architecture, components, and relationships

Code quality & review