game-ui-design-workflow: 一套面向游戏 UI 设计的 Cursor Agent Skills 工作流，覆盖原型视觉生成、风格切换、页面延展与组件拆解

by guiguiyan930-source · Agent Tool · ★ 191

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

Security audit verdict: SAFE · quality 64/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

ai-workflowcursor-skillsdesign-systemgame-developmentgame-uispec-kitui-design

Quick Facts

Stars191
Forks32
LanguagePython
CategoryAgent Tool
LicenseMIT
Quality Score64/100
Last Updated2026-08-05
Created2026-08-04
Platformspython
Est. Tokens~14k

About game-ui-design-workflow

Game UI Design Workflow 一个面向 Cursor Agent 的游戏 UI 设计技能仓库。它用 Spec-Kit 风格的项目文档串联能力： 策划与需求（生成第一步）：游戏策划方案（GDD）、PRD、UI 交互逻辑 → UI 规范：建立视觉语言、设计令牌、布局和交互规则。 UI 延展：从玩法与玩家旅程扩展完整屏幕地图。 页面生成：逐页生成方案、提示词与视觉稿。 组件拆解：把已批准页面拆成可复用、可交付的独立素材。 雪碧图拆分：去掉元素文字，将组件合图切成单元素透明 PNG，并打包 ZIP。 资产交付：语义命名、9-slice、Atlas 与 Godot / Unity / Cocos JSON。 是总控技能；阶段技能也可独立调用。项目事实保存在 ，避免只依赖对话上下文。 使用场景 只有游戏概念，需要先写策划方案、PRD 和 UI 交互逻辑再生图。...

Compatible Skills

These tools work well together with game-ui-design-workflow for enhanced workflows:

  • spec-kit-zh — semantic(0.32)+complementary+rare_topics+same_lang+similar_pop+shared_platform (66%)
  • Aegis — semantic(0.22)+complementary+rare_topics+same_lang+similar_pop+shared_platform (62%)
  • game-design-skills-bundle — semantic(0.30)+complementary+same_lang+similar_pop+shared_platform (60%)
  • AI-Agents-public — semantic(0.16)+complementary+rare_topics+same_lang+similar_pop+shared_platform (60%)
  • Styler — semantic(0.28)+complementary+same_lang+similar_pop+shared_platform (60%)

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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