design-judge-skills: Evidence-driven Agent Skills for design award research, evaluation, award matching, entry writing

by SeanJ1ang · Codex Skill · ★ 1.0k

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

How to install design-judge-skills

npx skills add SeanJ1ang/design-judge-skills --list
npx skills add SeanJ1ang/design-judge-skills --global --agent codex --skill '*' --yes --copy

Taken from the project's README on GitHub. Check the security audit before running it.

Security audit verdict: SAFE · quality 66/100

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.

agent-skillsclaude-codecodexdesign-awardsdesign-evaluationdesign-researchhermes-agentindustrial-designopenclawopencode

Quick Facts

Stars1,022
Forks157
LanguagePython
CategoryCodex Skill
LicenseApache-2.0
Quality Score66/100
Last Updated2026-08-24
Created2026-07-18
Platformsclaude-code, codex, python
Est. Tokens~15k

About design-judge-skills

Design Judge Skills 面向设计奖全流程的证据驱动 Agent Skills:从获奖案例检索、设计评价和奖项匹配,到申报文字准备与提交终检。 快速开始 · 获奖样本体量 · 安装 · 技能索引 · 贡献与开发 · Star 历史 · English 将设计奖申报拆解为边界清晰、可独立触发与验证的技能模块,围绕官方来源、证据定位与透明评分构建可追溯的辅助决策流程,并依据公开标准比较申报路径、解释适配度与确定申报优先级。 目录 项目介绍 工作流 设计原则与边界 快速开始 安装 5.1 npx skills 安装方式 5.2 Claude Code 安装方式 5.3 Codex 安装方式 5.4 其他 Agent 场景 技能索引 贡献与开发 Star 历史 项目介绍 Design Judge Skills 覆盖设计奖申报中的五类核心任务: 检索并核验同类别获奖案例;...

Compatible Skills

These tools work well together with design-judge-skills for enhanced workflows:

  • design-skill-os — semantic(0.46)+complementary+same_lang+similar_pop+shared_platform (66%)
  • veriflow-cc — semantic(0.35)+complementary+same_lang+similar_pop+shared_platform (62%)

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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:

View on GitHub → Browse Codex Skill tools