SkillAtlasSkill 详情

judge

This is the open-source content repository behind

审核状态:已审核Quality 72Security 90

复制安装命令

用 Codex 或 Claude 安装复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它先审查 Skill 页面再帮你安装。

复制前请先查看来源、License 和安全提示。

项目 README

来源文件:README.md

抓取于 2026年9月3日

Skill Store — Marketplace Repository

This is the open-source content repository behind Skill Store. It stores every approved Agent Skill, the records that go with it, and the automated security audits published with each skill.

This repo is a companion to the Skill Store platform, not the place to submit skills. Skills are added through skillstore.io — its review pipeline writes to this repo automatically. Please do not open a pull request here to add a skill; PRs adding skills will be closed. See Contributing a skill below.

Installing a skill

The recommended way to install any skill is the skillstore CLI — one command works for both Claude Code and Codex:

npx skillstore add author/skill-name

For example:

npx skillstore add aiskillstore/code-review

It downloads the skill and drops it into the right skills/ directory for your tool. Claude Code auto-discovers it; for Codex, restart the session.

Prefer to do it by hand, or installing via Claude Web? See the full Installation Guides for every method (CLI, manual, and ZIP upload) and the scope directories (~/.agents/skills/, .claude/skills/, ~/.claude/skills/, .codex/skills/, …).

Contributing a skill

Submit through the platform — not through a pull request:

  1. Go to skillstore.io/submit.
  2. Enter the GitHub repository URL that contains your SKILL.md.
  3. Your submission runs through automated security analysis.
  4. A maintainer reviews and approves it.
  5. On approval, the skill is published here and appears on skillstore.io.

What makes a valid skill

  • SKILL.md — the skill definition (required, per the Agent Skills spec)
  • Supporting files the skill references (optional)
  • LICENSE (recommended)

Security audit

Every submission is scanned automatically before it can be published. The audit flags things like:

  • Dangerous code patterns (eval, exec, raw system commands)
  • File access outside the project scope
  • Network calls to external hosts
  • Obfuscated or minified code
  • Credential / secret handling

Security analysis is report-only: findings inform maintainers and users, but a risk result does not automatically block an otherwise approved skill from being published. See our Security Trust Center for the methodology, limitations, and risk-level definitions.

Live Security Passport example:

Skillstore security

Repository layout

.
├── skills/        # Approved, published skills (one folder each, with SKILL.md)
├── pending/       # Submissions awaiting review
├── packages/
│   ├── cli/       # The `skillstore` CLI (npx skillstore add …)
│   └── skillstore/
├── schemas/       # JSON schemas for skill records
├── scripts/       # Maintenance & scoring scripts
└── .github/workflows/   # Submission, audit, and sync automation

The contents of this repo are maintained by Skill Store's automated pipeline. Manual changes are limited to maintainers.

Links

License

The marketplace catalog is MIT-licensed. Individual skills carry their own licenses — check each skill's LICENSE file.

测试与质量

低风险

  • 来源需自行核对维护者身份。
  • 未检测到明显脚本安装指令。
  • 可能需要外部 token、网络权限或第三方服务。
  • 未检测到高风险命令。
  • 扫描发现:0 条。

Codex — Git Clone 安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 克隆仓库:git clone https://github.com/aiskillstore/marketplace.git
  3. 将 "skills/2389-research/test-kitchen/judge" 文件夹复制到 Codex 的 skills 目录中。
  4. 重启 Codex 让新的 skill 生效。

Codex — 手动复制安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 从源仓库下载 SKILL.md 及相关文件。
  3. 在 Codex 的 skills 目录中创建新文件夹。
  4. 将所有 skill 文件复制到新文件夹中。
  5. 重启 Codex 让新的 skill 生效。

Claude Code — Git Clone 安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 克隆仓库:git clone https://github.com/aiskillstore/marketplace.git
  3. 将 "skills/2389-research/test-kitchen/judge" 文件夹复制到 Claude Code 的 skills 目录中。
  4. 重启 Claude Code 让新的 skill 生效。

Claude Code — 手动复制安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 从源仓库下载 SKILL.md 及相关文件。
  3. 在 Claude Code 的 skills 目录中创建新文件夹。
  4. 将所有 skill 文件复制到新文件夹中。
  5. 重启 Claude Code 让新的 skill 生效。

Cursor — Git Clone 安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 克隆仓库:git clone https://github.com/aiskillstore/marketplace.git
  3. 将 "skills/2389-research/test-kitchen/judge" 文件夹复制到 Cursor 的 skills 目录中。
  4. 重启 Cursor 让新的 skill 生效。

Cursor — 手动复制安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 从源仓库下载 SKILL.md 及相关文件。
  3. 在 Cursor 的 skills 目录中创建新文件夹。
  4. 将所有 skill 文件复制到新文件夹中。
  5. 重启 Cursor 让新的 skill 生效。

GitHub Copilot — Git Clone 安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 克隆仓库:git clone https://github.com/aiskillstore/marketplace.git
  3. 将 "skills/2389-research/test-kitchen/judge" 文件夹复制到 GitHub Copilot 的 skills 目录中。
  4. 重启 GitHub Copilot 让新的 skill 生效。

GitHub Copilot — 手动复制安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 从源仓库下载 SKILL.md 及相关文件。
  3. 在 GitHub Copilot 的 skills 目录中创建新文件夹。
  4. 将所有 skill 文件复制到新文件夹中。
  5. 重启 GitHub Copilot 让新的 skill 生效。

Windsurf — Git Clone 安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 克隆仓库:git clone https://github.com/aiskillstore/marketplace.git
  3. 将 "skills/2389-research/test-kitchen/judge" 文件夹复制到 Windsurf 的 skills 目录中。
  4. 重启 Windsurf 让新的 skill 生效。

Windsurf — 手动复制安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 从源仓库下载 SKILL.md 及相关文件。
  3. 在 Windsurf 的 skills 目录中创建新文件夹。
  4. 将所有 skill 文件复制到新文件夹中。
  5. 重启 Windsurf 让新的 skill 生效。
查看 SKILL.md 原文
name: judge
description: Scoring framework for test-kitchen cookoff and omakase-off. Invoked at Phase 4 to evaluate implementations using 5-criteria scoring. Do not invoke directly - called by cookoff/omakase-off.

Test Kitchen Judge

Score implementations using the 5-criteria framework. Fill out ALL sections exactly as shown.

Terminology: This skill uses "impl" but works for both:

  • Cookoff: impl-1, impl-2, impl-3 (same design, different implementations)
  • Omakase: variant-a, variant-b (different approaches/designs)

REQUIRED OUTPUT FORMAT

You MUST produce this exact structure. Do not summarize or abbreviate.

## Gate Check
| Impl | Tests Pass | Design Adherence |
|------|------------|------------------|
| impl-1 | X/X ✓ or ✗ | Yes/No |
| impl-2 | X/X ✓ or ✗ | Yes/No |

## Feasibility Check
| Impl | Status | Notes |
|------|--------|-------|
| impl-1 | ✓ OK / ⚠️ Flag | Details |
| impl-2 | ✓ OK / ⚠️ Flag | Details |

## Scoring Worksheet

### impl-1
**Fitness for Purpose** (Does it solve the actual problem?)

*Functional requirements:*
- [ ] Primary use case works end-to-end?
- [ ] All explicitly stated requirements implemented?
- [ ] Handles realistic scenarios, not just happy path?

*User needs (beyond literal requirements):*
- [ ] Would the user actually use this, or just demo it?
- [ ] Does it solve the real problem, not just the literal request?
- [ ] Does deployment/distribution match stated needs?

*Future considerations (if relevant):*
- [ ] If growth/scaling mentioned, does architecture support it?
- [ ] If team/collaboration mentioned, is it maintainable by others?

Checklist: _/8 YES → **Score: _/5** (7-8=5, 5-6=4, 4=3, 2-3=2, 0-1=1)
*Note: Not all items apply to every project. Score based on relevant items.*

**Justified Complexity** (Every line earning its keep?)
- Unnecessary abstractions: ___
- Dead code: ___
- Bloat estimate: ___%

*Line count comparison (if multiple impls):*
- This impl: ___ lines
- Smallest impl: ___ lines
- Extra lines justified by: ___

→ **Score: _/5** (5=minimal, 4=slight bloat <10%, 3=10-25% bloat, 2=25-50%, 1=>50%)

**Readability** (Understand core flow in 5 min?)
Violations:
- [ ] Single-letter vars (not loop index): +1 each = __
- [ ] Functions >50 lines: +1 each = __
- [ ] Nesting >3 levels: +1 each = __
- [ ] Magic numbers: +1 each = __
- [ ] Bad function names: +1 each = __
Total violations: __ → **Score: _/5** (0=5, 1-2=4, 3-4=3, 5-7=2, 8+=1)

**Robustness & Scale** (Handles unexpected + growth?)
- [ ] Input validation?
- [ ] External call error handling?
- [ ] Useful error messages?
- [ ] Null/empty handling?
- [ ] Async timeouts?
- [ ] No unbounded loops?
- [ ] O(n log n) or better?
- [ ] Bounded memory?
- [ ] Queries paginated?
- [ ] No blocking I/O in hot path?
- [ ] Backoff/retry logic?
- [ ] Handles 10x load?
Checklist: _/12 YES + feasibility flags → **Score: _/5**
(11-12 + no flags=5, 9-10 or minor flag=4, 7-8=3, 5-6 or major flag=2, <5 or critical flag=1)

**Maintainability** (Pain of next change?)
- [ ] Single responsibility per function?
- [ ] Explicit dependencies (no globals)?
- [ ] Business logic separated from infra?
- [ ] New feature = ≤3 files changed?
- [ ] Config externalized?
- [ ] Tests catch regressions?
Checklist: _/6 YES → **Score: _/5** (6=5, 5=4, 4=3, 2-3=2, 0-1=1)

### impl-2
[REPEAT SAME FORMAT]

### impl-3 (if applicable)
[REPEAT SAME FORMAT]

## Judge Scorecard
| Criterion | impl-1 | impl-2 | impl-3 | Best |
|-----------|--------|--------|--------|------|
| Fitness for Purpose | | | | |
| Justified Complexity | | | | |
| Readability | | | | |
| Robustness & Scale | | | | |
| Maintainability | | | | |
| **TOTAL** | /25 | /25 | /25 | |

## Hard Gates
| Gate | Result |
|------|--------|
| Fitness Gate (Δ ≥ 2) | Triggered/Not triggered |
| Critical Flaw (any = 1) | Triggered/Not triggered |

## Winner Selection
**Winner: impl-X** (Score: __/25)

**Selection rationale:**
[2-3 sentences explaining WHY this implementation won]

**Trade-offs acknowledged:**
[What the other implementations did better]

Scoring Reference

Scores Meaning

ScoreMeaning
5Excellent - exceeds expectations
4Good - fully meets requirements
3Adequate - core works, some gaps
2Poor - significant issues
1Critical flaw - disqualifying

Hard Gates (Automatic)

  1. Fitness Gate: If Fitness Δ ≥ 2 between impls → Higher fitness WINS immediately
  2. Critical Flaw: If ANY criterion = 1 → That impl is ELIMINATED

Fitness Gate Interpretation

The Fitness Gate triggers the same way in both contexts, but means different things:

ContextWhat Fitness Δ ≥ 2 Means
CookoffOne implementation deviated from or misunderstood the design. All impls should have similar Fitness since they're implementing the same spec. A large gap is a red flag.
OmakaseOne approach genuinely solves the problem better. Different approaches can legitimately have different Fitness. A large gap means one approach is clearly superior.

In both cases, higher Fitness wins. The interpretation just explains why the gap exists.

Feasibility Red Flags

Check before scoring:

  • O(n²) or worse on unbounded data
  • Unbounded memory growth
  • Self-DDoS patterns (polling, no backoff)
  • Missing pagination
  • Blocking I/O in hot path
  • No error recovery

Process

  1. Read all implementation code (should already be in context)
  2. Fill out the worksheet for EACH implementation - do not skip sections
  3. Check hard gates
  4. Announce winner with rationale

CRITICAL: Use integer scores only (1-5). Do not use half points like 4.5.

CRITICAL: Fill out every checkbox. Do not summarize or abbreviate the worksheet.

发现问题?提交给管理员复核

评分:

评论 (0)

暂无评论,成为第一个评论者吧!