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skill-quality-auditor-new技能质量审核员新

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

2,938

周安装

120

GitHub Stars

公开资料未说明

下载量

950
OpenClaw

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

2

许可证

MIT-0

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:skill-quality-auditor-new(技能质量审核员新)
来源仓库:https://github.com/aidenchangzy/skill-quality-auditor-new
安装命令:
openclaw skills install skill-quality-auditor-new
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。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install skill-quality-auditor-new

简介

审核 Codex 技能的结构合规性和整体可维护性。

  • 适合在技能开发后期进行质量检查和优化建议。
  • 通过 clawhub 安装,可评估触发质量、脚本重用等维度。
  • 建议结合人工复核,避免仅依赖工具输出做决策。
  • 涉及敏感信息时应先脱敏处理。skill-quality-auditor-new 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

name
skill-quality-auditor
description
Audit another Codex skill for structural compliance, trigger quality, instruction clarity, reuse of scripts or references, and overall maintainability. Use when Codex is given a skill folder and needs to judge whether the skill is qualified, explain why it passes or fails, and summarize strengths, weaknesses, blockers, and improvement ideas across multiple dimensions.

Skill Quality Auditor

Overview

Evaluate a target skill with a consistent rubric and return a clear pass/fail-style verdict plus a multi-dimensional review. Prefer the bundled script for the first pass, then turn the raw findings into a concise human-readable assessment.

Workflow

  1. Identify the target skill folder.
  2. Run scripts/evaluate_skill.py <path-to-skill>.
  3. Read the report and group findings into:

- final verdict - strengths - weaknesses - critical blockers - recommended fixes

  1. If the script reports missing context or borderline results, inspect the target skill's SKILL.md and any referenced resources before writing the final judgment.
  2. Keep the final answer decisive: say whether the skill is currently qualified, conditionally qualified, or not qualified.

Rubric

Score the skill across these dimensions:

  • structure: required files, frontmatter validity, naming, obvious TODO placeholders
  • triggering: whether description clearly explains what the skill does and when to use it
  • workflow: whether the body gives actionable steps instead of vague guidance
  • progressive_disclosure: whether detailed material is kept in scripts or references instead of bloating SKILL.md
  • resources: whether scripts, references, and assets are included only when useful and are mentioned in the body
  • examples_and_outputs: whether the skill helps the agent understand expected usage or output shape
  • maintainability: clarity, concision, stale metadata checks, and overall ease of iteration

Use references/rubric.md when you need the detailed scoring logic and interpretation rules.

Verdict Rules

Use these labels:

  • Qualified: no critical blockers and score is strong enough for immediate use
  • Borderline: usable but needs material fixes soon
  • Not Qualified: missing required structure or too weak to trust in repeated use

Treat these as critical blockers:

  • missing SKILL.md
  • invalid or missing YAML frontmatter
  • missing name or description
  • unresolved template placeholders such as TODO
  • description too weak to trigger reliably
  • instructions too incomplete to execute the core task safely

Output Shape

Prefer this response shape:

Verdict

State Qualified, Borderline, or Not Qualified in the first sentence and explain the main reason.

Score Summary

Include the total score and 3-5 highest-signal dimension notes.

What Works Well

List concrete strengths tied to files or sections.

What Needs Work

List concrete weaknesses tied to files or sections.

Next Fixes

List the smallest set of changes most likely to move the skill to Qualified.

Script

Run:

python3 scripts/evaluate_skill.py /absolute/path/to/skill

Optional JSON mode:

python3 scripts/evaluate_skill.py /absolute/path/to/skill --json

The script is dependency-free and performs a deterministic first-pass audit. It is intentionally conservative: if a skill barely explains its trigger conditions or still contains template leftovers, the script should flag it instead of assuming good intent.

Review Rules

  • Prefer evidence over taste.
  • Praise strengths explicitly; do not only list problems.
  • Distinguish hard failures from improvement opportunities.
  • If the target skill intentionally omits scripts, references, or agents metadata, do not penalize that by itself.
  • Penalize unused or stale directories when they add confusion.
  • When inferring quality from wording, cite the exact section or file that led to the conclusion.

Trigger Examples

  • "Check whether this skill is规范合格."
  • "Review this skill and tell me if it passes."
  • "Audit this skill folder and summarize the good and bad."
  • "Evaluate this skill against best practices and give me a verdict."

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

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

OpenClaw

71.76%
按下载量换算682

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

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。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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