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Agent Skill · 研究检索

shadow-ai-monitor(影子 AI 监视器)

shadow-ai-monitor 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

shadow-ai-monitor 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为操作浏览器;许可证为 MIT-0,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 8,873。

总安装 15,420周安装 649GitHub Stars 公开资料未说明下载 5,556核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
1.0.0

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:shadow-ai-monitor(影子 AI 监视器)
来源仓库:https://github.com/techcodecrafter/shadow-ai-monitor
安装命令:
openclaw skills install shadow-ai-monitor
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 shadow-ai-monitor

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

用于跟踪员工 AI 工具使用情况、数据暴露风险和 PIPEDA 合规性的企业级仪表板。适合在企业环境中监控 AI 使用行为并生成专业 HTML 报告。通过 clawhub 安装,需确认权限范围及是否涉及联网或文件操作。建议结合原始 README 核验具体功能与适用场景后再部署。

维护状态和实际效果需人工持续评估,不保证稳定性。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install shadow-ai-monitor;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要操作浏览器,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

shadow-ai-monitor 怎么安装?

在终端执行 openclaw skills install shadow-ai-monitor。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

shadow-ai-monitor 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

shadow-ai-monitor 需要什么权限?

权限级别是操作浏览器。该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

shadow-ai-monitor 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

shadow-ai-monitor 用的人多吗?

公开数据是累计安装 15,420 次,近一周安装 649 次,下载 5,556 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

shadow-ai-monitor 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
shadow-ai-monitor

影子 AI 监视器 · 本页

15,420—操作浏览器MIT-0通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
shadow-ai-monitor
description
Shadow AI Monitor - Enterprise-grade dashboard for tracking employee AI tool usage, data exposure risks, and PIPEDA compliance. Generates professional HTML dashboards with interactive drill-downs, compliance analysis, and PDF export. Perfect for CTOs and security teams monitoring ChatGPT, Claude, Gemini, Copilot, and other AI tools. Includes demo data generator for presentations.

Shadow AI Monitor

A professional web dashboard system for tracking employee AI tool usage, identifying data exposure risks, and measuring PIPEDA compliance.

What This Skill Does

Generates enterprise-grade HTML dashboards showing:

  • 📊 AI Tool Usage Analytics - Track which tools employees use (ChatGPT, Claude, Gemini, Copilot, Midjourney, Grok, Perplexity, Cursor, GitHub Copilot)
  • ⚠️ Risk Analysis - Classify data exposure as Low/Medium/High risk
  • 📋 Compliance Scoring - PIPEDA compliance score (0-100) with detailed requirement breakdown
  • 👥 Employee Insights - Anonymized usage patterns and heatmaps
  • 📈 Trend Tracking - Daily usage trends and event logs
  • 📄 Board-Ready Reports - PDF export with professional styling

Perfect For

  • Security Teams monitoring shadow AI adoption
  • CTOs assessing compliance gaps
  • Legal/Compliance teams tracking data exposure
  • Sales Teams demoing AI governance products
  • Consultants delivering AI risk assessments

Quick Start

Generate a demo dashboard:

node scripts/generate_demo_data.js
node scripts/generate_dashboard.js shadow-ai-data.json

Open shadow-ai-dashboard.html in your browser.

Features

🎯 Interactive Dashboard

Click to Explore:

  • Employee Bars → See top 3 riskiest events, tools used, data categories, dates
  • Compliance Score → View 5 PIPEDA requirements, pass/fail status, specific fixes
  • Export Button → Generate PDF with letterhead styling

Key Metrics:

  • PIPEDA compliance score (color-coded: green ≥85, yellow ≥70, red <70)
  • Risk event breakdown (High/Medium/Low)
  • Top 3 AI tools by usage
  • Top 10 employees (anonymized)

Visualizations:

  • Bar charts: Tool usage, employee activity
  • Doughnut chart: Risk distribution
  • Line chart: Daily trends
  • Heat map: Employee usage intensity
  • Scrollable event log (last 20 events, high-risk highlighted)

📋 Personalized Recommendations

Auto-generated advice based on actual data patterns:

  • References specific employees and percentages
  • Tool-specific recommendations (e.g., "ChatGPT accounts for 48% of usage")
  • Compliance-specific action items
  • Example: "Employee 5 generated 8 high-risk events involving client matters — review recommended"

🔒 PIPEDA Compliance Analysis

Detailed breakdown of 5 core requirements:

  1. Consent for Collection
  2. Limiting Use, Disclosure & Retention
  3. Safeguards
  4. Openness
  5. Individual Access

Each shows:

  • Pass/Fail status
  • Requirement description
  • Specific action items using your actual data

📊 Demo Data Generator

Creates realistic data for a 50-person Canadian organization:

Configurable:

  • Company name (default: Morrison & Associates)
  • Employee count
  • AI tools tracked
  • Data categories (Client Legal, Financial, Health, Personal, etc.)
  • Risk distribution
  • Time period (last 7 days default)

Realistic Patterns:

  • Mix of 9 different AI tools
  • Varied risk levels (~25% high, ~35% medium, ~40% low)
  • Employee anonymization (Employee 1, Employee 2, etc.)
  • Concerning patterns for demo impact

Files

shadow-ai-monitor/
├── SKILL.md                        # This file
├── scripts/
│   ├── generate_demo_data.js      # Demo data generator
│   └── generate_dashboard.js      # HTML dashboard generator

Installation

Via ClawHub:

clawhub install shadow-ai-monitor

Manual:

mkdir -p ~/.openclaw/skills
cd ~/.openclaw/skills
# Download and extract skill files

Usage

Basic Demo Dashboard

cd ~/.openclaw/workspace  # or your working directory
node ~/.openclaw/skills/shadow-ai-monitor/scripts/generate_demo_data.js
node ~/.openclaw/skills/shadow-ai-monitor/scripts/generate_dashboard.js shadow-ai-data.json
open shadow-ai-dashboard.html  # or double-click in Finder/Explorer

This generates:

  • shadow-ai-data.json - Raw usage data
  • shadow-ai-dashboard.html - Interactive dashboard

Customizing Demo Data

Edit scripts/generate_demo_data.js to customize:

Company Name:

const output = {
  company: 'Your Company Name',
  // ...
};

Employee Count:

const employees = Array.from({ length: 100 }, (_, i) => ({
  id: `Employee ${i + 1}`,
  // ...
}));

AI Tools Tracked:

const AI_TOOLS = [
  'ChatGPT', 'Claude', 'Gemini', 'Your-Custom-Tool'
];

Data Categories:

const DATA_CATEGORIES = [
  { name: 'Your Category', risk: 'High' },
  // ...
];

Automated Weekly Reports

Set up with OpenClaw cron:

{
  "name": "Shadow AI Weekly Report",
  "schedule": {"kind": "cron", "expr": "0 9 * * 1", "tz": "America/Toronto"},
  "payload": {
    "kind": "agentTurn",
    "message": "Generate Shadow AI dashboard: 1) Run demo data generator 2) Generate dashboard 3) Send WhatsApp notification with metrics"
  },
  "sessionTarget": "isolated",
  "delivery": {"mode": "announce", "channel": "whatsapp"}
}

Technical Details

Data Structure

{
  "generated": "2026-02-22T15:00:00Z",
  "company": "Morrison & Associates",
  "employeeCount": 50,
  "period": "Last 7 days",
  "events": [
    {
      "timestamp": "2026-02-22T10:30:00Z",
      "employee": "Employee 1",
      "employeeRole": "Senior Associate",
      "tool": "ChatGPT",
      "dataCategory": "Client Legal Matters",
      "risk": "High"
    }
  ],
  "metrics": {
    "totalEvents": 268,
    "topTools": [["ChatGPT", 89], ["Claude", 56]],
    "riskCounts": {"Low": 95, "Medium": 83, "High": 90},
    "complianceScore": 68,
    "recommendations": ["..."]
  }
}

Risk Scoring

High Risk:

  • Client legal matters
  • Financial records
  • Health information

Medium Risk:

  • Personal information
  • Internal memos
  • Proprietary data

Low Risk:

  • General questions
  • Code templates
  • Public research

Compliance Score Calculation

Base: 100 points
Deduct: -2 points per % of high-risk events
Deduct: -0.5 points per % of medium-risk events
Range: 0-100

Example:

  • 268 total events
  • 90 high-risk (34%) → -68 points
  • 83 medium-risk (31%) → -15.5 points
  • Score: 16/100

Dashboard Technology

  • Pure JavaScript - No npm install required
  • Chart.js via CDN - Loaded from jsDelivr
  • Dark Theme - Professional enterprise styling
  • Responsive Design - Works on desktop and tablet
  • Print-Optimized - Clean PDF export with letterhead

Use Cases

1. CTO Demo

Script:

"This is Morrison & Associates, a 50-person law firm. Over 7 days, we detected 268 AI tool events. Their PIPEDA compliance score is 16/100 because 34% of interactions involved client legal matters and health records shared with unapproved AI tools."

*Click compliance score* → Show specific PIPEDA failures *Click Employee 38* → Show their risky events *Click Export* → Board-ready PDF

2. Security Assessment

Generate dashboard with your organization's data:

  1. Monitor Slack/Teams/Email for AI tool mentions
  2. Log to JSON format matching data structure
  3. Run dashboard generator
  4. Present findings to security team

3. Sales Presentation

Demo realistic data showing:

  • Concerning compliance gaps
  • Specific risk patterns
  • Clear ROI through risk reduction
  • Professional, board-ready output

4. Compliance Audit

Track progress over time:

  • Generate weekly snapshots
  • Compare compliance scores
  • Identify trends (improving/worsening)
  • Document remediation efforts

Security & Privacy

✅ No External API Calls - All processing local ✅ No Data Collection - Demo data never leaves your machine ✅ No Credentials Required - Pure JavaScript execution ✅ Anonymized Data - Employee IDs, no PII in demo ✅ Open Source - Review all code before running

Requirements

  • Node.js (any recent version)
  • Web Browser (Chrome, Firefox, Safari, Edge)
  • No npm packages - Uses only Node.js built-ins

Roadmap

Future enhancements:

  • [ ] Real-time monitoring integration
  • [ ] Multi-company comparison
  • [ ] Historical trend analysis
  • [ ] Custom compliance frameworks (GDPR, HIPAA, SOC 2)
  • [ ] Email delivery of reports
  • [ ] Slack/Teams integration
  • [ ] Live data ingestion from DLP tools

Support & Contribution

  • Issues: Report bugs or request features on ClawHub
  • Questions: OpenClaw Discord community
  • Contributions: Submit improved visualizations, compliance frameworks, or data sources

License

MIT - Free for personal and commercial use

Credits

Built with OpenClaw by the automation engineering community.


Version: 1.0.0 Author: Automation Engineers Category: Security, Compliance, Analytics Tags: AI monitoring, PIPEDA, compliance, security, dashboard

平台分布

OpenClaw

83.8%
按下载量换算4,656

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

未展示

权限和风险

操作浏览器

该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

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。目前只有一个公开来源,建议同时核对源仓库。

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