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quality-audit质量审核

Agent Skill

用于辅助安全审计、权限检查、凭据风险、认证流程和常见漏洞排查。它适合让 Agent 梳理敏感配置、检查依赖风险、分析鉴权逻辑或生成安全复核清单。使用时不能把工具输出直接当最终结论,涉及密钥、令牌、用户数据或生产系统时,应先确认最小权限、脱敏方式和操作边界。

总安装

1,234

周安装

53

GitHub Stars

15

下载量

432
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

3

许可证

MIT

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:quality-audit(质量审核)
来源仓库:https://github.com/nickcrew/claude-ctx-plugin
仓库路径:skills/quality-audit
安装命令:
npx skills add https://github.com/nickcrew/claude-ctx-plugin --skill quality-audit
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/nickcrew/claude-ctx-plugin --skill quality-audit

简介

quality-audit 用于辅助安全审计、权限检查、凭据风险与认证流程分析,帮助 Agent 识别潜在漏洞。

  • 适用于代码安全复核、依赖风险检查或生成安全审计清单的场景。
  • 可调用其审计模块输出检查结果,但不可直接作为最终结论使用。
  • 涉及密钥、令牌或生产系统时,应先确认最小权限并确保数据脱敏处理。
  • 适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

SKILL.md

Quality Audit Skill

Systematic framework for evaluating skill quality across four dimensions: Clarity, Completeness, Accuracy, and Usefulness.

When to Use This Skill

  • Reviewing a new skill before adding to the registry
  • Auditing existing skills for quality improvements
  • Creating quality rubrics for skill validation
  • Standardizing skill quality across the library
  • Preparing skills for production use

Core Principles

The Four Quality Dimensions

DimensionWeightFocus
Clarity25%Structure, readability, progressive disclosure
Completeness25%Coverage, examples, edge cases, anti-patterns
Accuracy30%Correctness, best practices, security
Usefulness20%Real-world applicability, production-readiness

Scoring Scale (1-5)

ScoreLabelMeaning
1UnacceptableFundamentally broken, dangerous, or unusable
2Needs WorkMajor issues requiring significant revision
3AcceptableMeets minimum standards, functional
4GoodHigh quality, minor improvements possible
5ExcellentExemplary, production-ready, best-in-class

Passing Criteria

  • Minimum: 3.0 weighted average (acceptable)
  • Target: 4.0 weighted average (good)
  • Exceptional: 4.5+ weighted average (excellent)
  • Blocking: Accuracy must be ≥3.0 (no dangerous advice)

Audit Workflow

Phase 1: Structure Check

checklist:
  structure:
    - [ ] Has valid YAML frontmatter
    - [ ] Contains required metadata (name, description)
    - [ ] Follows progressive disclosure (Tier 1 → 2 → 3)
    - [ ] Sections are logically ordered
    - [ ] Token estimate is reasonable (<5000 for core)

Phase 2: Content Evaluation

checklist:
  content:
    - [ ] "When to Use" section is clear
    - [ ] Core principles are well-defined
    - [ ] Code examples are complete and runnable
    - [ ] Anti-patterns are documented
    - [ ] Troubleshooting guidance exists

Phase 3: Dimension Scoring

For each dimension, evaluate against specific criteria:

Clarity Criteria:

  • Well-organized sections with logical flow
  • Concise explanations without jargon overload
  • Code examples are readable and well-commented
  • Progressive disclosure from simple to complex

Completeness Criteria:

  • Covers core concepts thoroughly
  • Includes edge cases and error handling
  • Provides both do's and don'ts
  • Has working examples for main use cases

Accuracy Criteria:

  • Code examples compile/run without errors
  • Follows current best practices (not deprecated)
  • Security considerations are correct
  • Performance claims are verifiable

Usefulness Criteria:

  • Examples solve real-world problems
  • Can be applied immediately
  • Scales to production use cases
  • Includes troubleshooting guidance

Phase 4: Report Generation

## Audit Report: {skill_name}

**Date**: {date}
**Auditor**: {auditor}
**Status**: {PASS|FAIL|NEEDS_REVIEW}

### Scores

| Dimension | Score | Weight | Weighted |
|-----------|-------|--------|----------|
| Clarity | {x}/5 | 25% | {x*0.25} |
| Completeness | {x}/5 | 25% | {x*0.25} |
| Accuracy | {x}/5 | 30% | {x*0.30} |
| Usefulness | {x}/5 | 20% | {x*0.20} |
| **Total** | | | **{sum}/5** |

### Issues Found

- [CRITICAL] {issue description}
- [MAJOR] {issue description}
- [MINOR] {issue description}

### Recommendations

1. {actionable recommendation}
2. {actionable recommendation}

Implementation Patterns

Pattern 1: Quick Audit (5-minute review)

Use for rapid assessment of skill quality:

# Run automated structure checks
cortex skills audit <skill-name> --quick

# Output: Pass/Fail with basic metrics

Quick Audit Checks:

  1. YAML frontmatter valid?
  2. Required sections present?
  3. Code blocks have language tags?
  4. No TODO/FIXME markers?
  5. Token count reasonable?

Pattern 2: Full Audit (15-30 minute review)

Comprehensive evaluation with human review:

# Generate full audit report
cortex skills audit <skill-name> --full

# Interactive mode for scoring
cortex skills audit <skill-name> --interactive

Full Audit Process:

  1. Run automated checks
  2. Read through content manually
  3. Test code examples
  4. Score each dimension
  5. Document issues and recommendations
  6. Generate report

Pattern 3: Comparative Audit

Compare skill against reference implementation:

# Compare against template-skill-enhanced
cortex skills audit <skill-name> --compare template-skill-enhanced

Pattern 4: Batch Audit

Audit multiple skills for registry health:

# Audit all skills in a category
cortex skills audit --category security

# Audit skills below threshold
cortex skills audit --below-score 3.5

CLI Commands

# Basic audit
cortex skills audit <skill-name>

# Options
  --quick           Quick structural check only
  --full            Full audit with all dimensions
  --interactive     Interactive scoring mode
  --output FILE     Write report to file
  --format FORMAT   Output format (markdown|json|yaml)
  --compare SKILL   Compare against reference skill
  --fix             Auto-fix simple issues (formatting)

Creating Custom Rubrics

Skills can define custom rubrics in validation/rubric.yaml:

# validation/rubric.yaml
version: "1.0.0"
skill_name: my-skill

dimensions:
  clarity:
    weight: 25
    criteria:
      - "API examples use realistic data"
      - "Error handling is shown for each operation"
  completeness:
    weight: 25
    criteria:
      - "Covers all HTTP methods"
      - "Includes pagination patterns"
  accuracy:
    weight: 30
    criteria:
      - "Follows REST conventions"
      - "Security headers documented"
  usefulness:
    weight: 20
    criteria:
      - "Examples work with common frameworks"

passing_criteria:
  minimum_score: 3.5  # Higher bar for this skill
  required_dimensions:
    - accuracy
    - completeness

Best Practices

Do

  • Be specific - "Line 45: SQL query vulnerable to injection" not "has security issues"
  • Be actionable - Include how to fix each issue
  • Be fair - Use the same standards consistently
  • Document evidence - Quote specific content for each score
  • Prioritize - Critical issues first, suggestions last

Don't

  • Score based on personal style preferences
  • Mark deprecated patterns without suggesting alternatives
  • Fail skills for missing optional sections
  • Ignore security issues regardless of other scores
  • Rush through audits for complex skills

Anti-Patterns

The Rubber Stamp

Problem: Approving skills without thorough review Why it's bad: Low-quality skills erode trust in the library Fix: Use the full audit checklist, test code examples

The Perfectionist Block

Problem: Failing skills for minor issues Why it's bad: Prevents useful skills from being available Fix: Distinguish between blocking issues and suggestions

Score Inflation

Problem: Giving high scores without justification Why it's bad: Makes scores meaningless Fix: Document specific evidence for each score

Integration with CI/CD

# .github/workflows/skill-quality.yml
name: Skill Quality Gate

on:
  pull_request:
    paths:
      - 'skills/**'

jobs:
  audit:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - name: Install cortex
        run: pip install cortex
      - name: Audit changed skills
        run: |
          for skill in $(git diff --name-only HEAD~1 | grep 'skills/' | cut -d'/' -f2 | uniq); do
            cortex skills audit "$skill" --quick --fail-under 3.0
          done

Troubleshooting

"Audit fails but skill looks fine"

  1. Check YAML frontmatter syntax
  2. Verify all required sections exist
  3. Ensure code blocks have language tags
  4. Check for hidden characters (copy/paste issues)

"Scores seem inconsistent"

  1. Review the scoring guide for each dimension
  2. Calibrate by auditing template-skill-enhanced first
  3. Use --interactive mode for clearer criteria

External Resources

Changelog

1.0.0 (2026-01-05)

  • Initial release
  • Four-dimension scoring framework
  • CLI integration
  • CI/CD workflow example

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

04

需要参考平台分布和安装热度时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Claude Code

29.05%
按下载量换算125

Antigravity

26.46%
按下载量换算114

Gemini CLI

18.22%
按下载量换算79

OpenCode

11.51%
按下载量换算50

windsurf

7.82%
按下载量换算34

Codex

3.7%
按下载量换算16

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。

来源信息

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