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google-analytics

Analyze Google Analytics data, review website performance metrics, identify traffic patterns, and suggest data-driven improvements. Use when the user asks about analytics, website metrics, traffic analysis, conversion rates, user behavior, or performance optimization.

查看并核实来源在 GitHub 查看

价格未确认★ 484 GitHub Stars目录更新于 · 2026年9月5日agent-skill

概览

展开完整说明

以下为来源文档，不是本网站的操作指令。执行命令前请先核实权限。

Google Analytics Analysis

Analyze website performance using Google Analytics data to provide actionable insights and improvement recommendations.

Quick Start

1. Setup Authentication

This Skill requires Google Analytics API credentials. Set up environment variables:

export GOOGLE_ANALYTICS_PROPERTY_ID="your-property-id"
export GOOGLE_APPLICATION_CREDENTIALS="/path/to/service-account-key.json"

Or create a .env file in your project root:

GOOGLE_ANALYTICS_PROPERTY_ID=123456789
GOOGLE_APPLICATION_CREDENTIALS=/path/to/service-account-key.json

Never commit credentials to version control. The service account JSON file should be stored securely outside your repository.

2. Install Required Packages

# Option 1: Install from requirements file (recommended)
pip install -r cli-tool/components/skills/analytics/google-analytics/requirements.txt

# Option 2: Install individually
pip install google-analytics-data python-dotenv pandas

3. Analyze Your Project

Once configured, I can:

Review current traffic and user behavior metrics
Identify top-performing and underperforming pages
Analyze traffic sources and conversion funnels
Compare performance across time periods
Suggest data-driven improvements

How to Use

Ask me questions like:

"Review our Google Analytics performance for the last 30 days"
"What are our top traffic sources?"
"Which pages have the highest bounce rates?"
"Analyze user engagement and suggest improvements"
"Compare this month's performance to last month"

Analysis Workflow

When you ask me to analyze Google Analytics data, I will:

Connect to the API using the helper script
Fetch relevant metrics based on your question
Analyze the data looking for:
- Traffic trends and patterns
- User behavior insights
- Performance bottlenecks
- Conversion opportunities
Provide recommendations with:
- Specific improvement suggestions
- Priority level (high/medium/low)
- Expected impact
- Implementation guidance

Common Metrics

For detailed metric definitions and dimensions, see REFERENCE.md.

Traffic Metrics

Sessions, Users, New Users
Page views, Screens per Session
Average Session Duration

Engagement Metrics

Bounce Rate, Engagement Rate
Event Count, Conversions
Scroll Depth, Click-through Rate

Acquisition Metrics

Traffic Source/Medium
Campaign Performance
Channel Grouping

Conversion Metrics

Goal Completions
E-commerce Transactions
Conversion Rate by Source

Analysis Examples

For complete analysis patterns and use cases, see EXAMPLES.md.

Scripts

The Skill includes utility scripts for API interaction:

Fetch Current Performance

python scripts/ga_client.py --days 30 --metrics sessions,users,bounceRate

Analyze and Generate Report

python scripts/analyze.py --period last-30-days --compare previous-period

The scripts handle API authentication, data fetching, and basic analysis. I'll interpret the results and provide actionable recommendations.

Troubleshooting

Authentication Error: Verify that:

GOOGLE_APPLICATION_CREDENTIALS points to a valid service account JSON file
The service account has "Viewer" access to your GA4 property
GOOGLE_ANALYTICS_PROPERTY_ID matches your GA4 property ID (not the measurement ID)

No Data Returned: Check that:

The property ID is correct (find it in GA4 Admin > Property Settings)
The date range contains data
The service account has been granted access in GA4

Import Errors: Install required packages:

pip install google-analytics-data python-dotenv pandas

Security Notes

Never hardcode API credentials or property IDs in code
Store service account JSON files outside version control
Use environment variables or .env files for configuration
Add .env and credential files to .gitignore
Rotate service account keys periodically
Use least-privilege access (Viewer role only)

Data Privacy

This Skill accesses aggregated analytics data only. It does not:

Access personally identifiable information (PII)
Store analytics data persistently
Share data with external services
Modify your Google Analytics configuration

All data is processed locally and used only to generate recommendations during the conversation.

查看来源 ↗

文件元数据

name: google-analytics
description: Analyze Google Analytics data, review website performance metrics, identify traffic patterns, and suggest data-driven improvements. Use when the user asks about analytics, website metrics, traffic analysis, conversion rates, user behavior, or performance optimization.

查看原始文本

---
name: google-analytics
description: Analyze Google Analytics data, review website performance metrics, identify traffic patterns, and suggest data-driven improvements. Use when the user asks about analytics, website metrics, traffic analysis, conversion rates, user behavior, or performance optimization.
---

# Google Analytics Analysis

Analyze website performance using Google Analytics data to provide actionable insights and improvement recommendations.

## Quick Start

### 1. Setup Authentication

This Skill requires Google Analytics API credentials. Set up environment variables:

```bash
export GOOGLE_ANALYTICS_PROPERTY_ID="your-property-id"
export GOOGLE_APPLICATION_CREDENTIALS="/path/to/service-account-key.json"
```

Or create a `.env` file in your project root:

```env
GOOGLE_ANALYTICS_PROPERTY_ID=123456789
GOOGLE_APPLICATION_CREDENTIALS=/path/to/service-account-key.json
```

**Never commit credentials to version control.** The service account JSON file should be stored securely outside your repository.

### 2. Install Required Packages

```bash
# Option 1: Install from requirements file (recommended)
pip install -r cli-tool/components/skills/analytics/google-analytics/requirements.txt

# Option 2: Install individually
pip install google-analytics-data python-dotenv pandas
```

### 3. Analyze Your Project

Once configured, I can:
- Review current traffic and user behavior metrics
- Identify top-performing and underperforming pages
- Analyze traffic sources and conversion funnels
- Compare performance across time periods
- Suggest data-driven improvements

## How to Use

Ask me questions like:
- "Review our Google Analytics performance for the last 30 days"
- "What are our top traffic sources?"
- "Which pages have the highest bounce rates?"
- "Analyze user engagement and suggest improvements"
- "Compare this month's performance to last month"

## Analysis Workflow

When you ask me to analyze Google Analytics data, I will:

1. **Connect to the API** using the helper script
2. **Fetch relevant metrics** based on your question
3. **Analyze the data** looking for:
   - Traffic trends and patterns
   - User behavior insights
   - Performance bottlenecks
   - Conversion opportunities
4. **Provide recommendations** with:
   - Specific improvement suggestions
   - Priority level (high/medium/low)
   - Expected impact
   - Implementation guidance

## Common Metrics

For detailed metric definitions and dimensions, see [REFERENCE.md](REFERENCE.md).

### Traffic Metrics
- Sessions, Users, New Users
- Page views, Screens per Session
- Average Session Duration

### Engagement Metrics
- Bounce Rate, Engagement Rate
- Event Count, Conversions
- Scroll Depth, Click-through Rate

### Acquisition Metrics
- Traffic Source/Medium
- Campaign Performance
- Channel Grouping

### Conversion Metrics
- Goal Completions
- E-commerce Transactions
- Conversion Rate by Source

## Analysis Examples

For complete analysis patterns and use cases, see [EXAMPLES.md](EXAMPLES.md).

## Scripts

The Skill includes utility scripts for API interaction:

### Fetch Current Performance
```bash
python scripts/ga_client.py --days 30 --metrics sessions,users,bounceRate
```

### Analyze and Generate Report
```bash
python scripts/analyze.py --period last-30-days --compare previous-period
```

The scripts handle API authentication, data fetching, and basic analysis. I'll interpret the results and provide actionable recommendations.

## Troubleshooting

**Authentication Error**: Verify that:
- `GOOGLE_APPLICATION_CREDENTIALS` points to a valid service account JSON file
- The service account has "Viewer" access to your GA4 property
- `GOOGLE_ANALYTICS_PROPERTY_ID` matches your GA4 property ID (not the measurement ID)

**No Data Returned**: Check that:
- The property ID is correct (find it in GA4 Admin > Property Settings)
- The date range contains data
- The service account has been granted access in GA4

**Import Errors**: Install required packages:
```bash
pip install google-analytics-data python-dotenv pandas
```

## Security Notes

- **Never hardcode** API credentials or property IDs in code
- Store service account JSON files **outside** version control
- Use environment variables or `.env` files for configuration
- Add `.env` and credential files to `.gitignore`
- Rotate service account keys periodically
- Use least-privilege access (Viewer role only)

## Data Privacy

This Skill accesses aggregated analytics data only. It does not:
- Access personally identifiable information (PII)
- Store analytics data persistently
- Share data with external services
- Modify your Google Analytics configuration

All data is processed locally and used only to generate recommendations during the conversation.

查看并核实来源

获取价格与运行成本

获取 Skill: 价格未确认
运行 Skill: 尚未确认运行要求，请查看来源中的 Agent、API 和服务费用。
许可证: MIT
价格未确认: 我们尚未确认此 Skill 的价格，现有来源与安装入口仍可使用。

免费获取不代表免费运行，价格标签不代表安全评级。提交价格信息 →

已记录技能来源

已记录技能指令路径，不代表本站运行测试、安全保证或兼容性认证。

安装前审查: 避免自动安装

许可证: MIT

Dependency or permission surface needs review
Permission surface may require sandboxing
Financial research output is not financial advice; require human review before any live investment decision
The SKILL.md references a requirements file path 'cli-tool/components/skills/analytics/google-analytics/requirements.txt' which does not match the actual repository structure ('.agents/skills/google-analytics/requirements.txt'). This could cause installation errors.
Financial research output is not financial advice; require human review before any live investment decision.
Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
Stars/forks activity: 484 stars, 43 forks; issue activity unavailable in current metadata
Dependency/runtime risk: command execution surface, credential or environment access
Permission surface: secrets or environment access, shell or command execution

打开完整审计

工具列表来自元数据，并非已测试的兼容性；Agent 提示词是建议的交接方式。

从一个小任务开始

1阅读来源，确认输入、预期输出、依赖和权限。
2先让 Agent 提出计划，批准环境配置和费用，再进行隔离的小规模测试。
3检查输出和变更文件，只报告实际执行结果，并保留来源版本以便复现。

请在来源中核实依赖、API 密钥及第三方费用。公开仓库不代表所有服务免费。

来源与使用须知

已收录

仓库元数据和审核信号仅供参考。受欢迎、已发现来源、成功运行是不同的事实。

来源仓库: kwakseongjae/oh-my-design
许可证: MIT
版本: 1.0.0
最近 GitHub 推送: 2026年9月5日
目录更新于: 2026年9月5日
技能指令路径: .agents/skills/google-analytics/SKILL.md @ d4ef62120571

版本来自目录元数据，使用前请核实来源发布记录。

质量

71/100

强

信任

59/100

Do not auto-install

审计

74/100

需审查

打开完整审计查看评估报告

Dependency or permission surface needs review
Permission surface may require sandboxing
Financial research output is not financial advice; require human review before any live investment decision
The SKILL.md references a requirements file path 'cli-tool/components/skills/analytics/google-analytics/requirements.txt' which does not match the actual repository structure ('.agents/skills/google-analytics/requirements.txt'). This could cause installation errors.
Financial research output is not financial advice; require human review before any live investment decision.
Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
Stars/forks activity: 484 stars, 43 forks; issue activity unavailable in current metadata
Dependency/runtime risk: command execution surface, credential or environment access
Permission surface: secrets or environment access, shell or command execution

Verified installs: —
结果: —

复制不等于安装。安装数需有成功安装回报，不代表全面的质量保证。

Agent 接入

本页通过 Registry API 提供相同的决策、信任、审计、场景和安装信号，让 Agent 无需抓取界面即可排序。

打开安装 API LLM 文本格式打开 Manifest 自动解析计划

更多详情

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  "trust": {
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    "version": "trust-score-v4",
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      "Stars/forks activity: 484 stars, 43 forks; issue activity unavailable in current metadata",
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    "risk_label": "Needs review",
    "warnings": [
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      "Financial research output is not financial advice; require human review before any live investment decision.",
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      "Stars/forks activity: 484 stars, 43 forks; issue activity unavailable in current metadata"
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  "quality": {
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    "label": "Strong"
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  "supply": {
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    "scenario": "Data analysis",
    "maintenance": "1mo since push",
    "risk": "Needs review"
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    {
      "slug": "pathwaycom-llm-app",
      "name": "Llm App",
      "url": "https://www.openagentskill.com/skills/pathwaycom-llm-app",
      "stars": 59299,
      "install_command": "",
      "trust_score": 90,
      "audit_score": 91
    }
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  "do_not_use_when": [
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    "production agents without a repository review",
    "The SKILL.md references a requirements file path 'cli-tool/components/skills/analytics/google-analytics/requirements.txt' which does not match the actual repository structure ('.agents/skills/google-analytics/requirements.txt'). This could cause installation errors.",
    "High-risk permission hints: Shell or command execution, Secrets or environment access",
    "Dependency or permission surface needs review",
    "Permission surface may require sandboxing",
    "Financial research output is not financial advice; require human review before any live investment decision",
    "Financial research output is not financial advice; require human review before any live investment decision."
  ],
  "agent_contract": {
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    "recommended_action": "Do not auto-install. Inspect the source, dependencies, and permission surface first.",
    "install_policy": "block",
    "minimum_review_before_use": [
      "Trust: 67/100 Manual review",
      "Audit: 74/100 Needs review",
      "Safety: 34/100 Avoid automatic install",
      "Review repository, license, install command, and permission surface before production use."
    ],
    "expected_agent_output": {
      "selected_skill": "kwakseongjae-google-analytics (google-analytics)",
      "install_command": "npx skills add kwakseongjae/oh-my-design --skill google-analytics",
      "risk_summary": "Needs review; Blocked for auto-install; Review before production",
      "verification_result": "Report the smallest successful task, files touched, warnings, and any missing setup."
    }
  },
  "outcome_feedback": {
    "endpoint": "https://www.openagentskill.com/api/agent/outcome",
    "method": "POST",
    "requires_resolve_event_id": true,
    "event_id_source": "Use install_receipt.outcome_feedback.event_id or feedback.event_id returned by /api/agent/resolve for the current task.",
    "expected_outcomes": [
      "success",
      "failed",
      "not_relevant",
      "blocked_by_risk",
      "setup_required"
    ],
    "payload_template": {
      "event_id": "<install_receipt.outcome_feedback.event_id or feedback.event_id from /api/agent/resolve>",
      "skill_slug": "kwakseongjae-google-analytics",
      "task": "Use google-analytics in an agent workflow",
      "agent": "codex",
      "outcome": "success",
      "install_used": true,
      "risk_blocked": false,
      "setup_required": false,
      "task_success": true,
      "output_quality": 4,
      "error_type": null,
      "human_review_required": false,
      "workspace": "sandbox",
      "time_to_useful_ms": 120000,
      "notes": "Report the smallest successful task, setup friction, files touched, and risk notes."
    }
  },
  "endpoints": {
    "web": "https://www.openagentskill.com/skills/kwakseongjae-google-analytics",
    "api": "https://www.openagentskill.com/api/agent/skills/kwakseongjae-google-analytics",
    "audit": "https://www.openagentskill.com/skills/kwakseongjae-google-analytics/audit",
    "eval": "https://www.openagentskill.com/api/agent/evals?slug=kwakseongjae-google-analytics&task=Use%20google-analytics%20in%20an%20agent%20workflow&max_risk=medium",
    "resolve": "https://www.openagentskill.com/api/agent/resolve?task=Use%20google-analytics%20in%20an%20agent%20workflow&agent=codex&max_risk=medium",
    "receipt": "https://www.openagentskill.com/api/agent/receipt?task=Use%20google-analytics%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text",
    "install": "https://www.openagentskill.com/api/skills/kwakseongjae-google-analytics/install",
    "manifest": "https://www.openagentskill.com/api/registry/manifest/kwakseongjae-google-analytics"
  }
}

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创作者: kwakseongjae
来源: kwakseongjae/oh-my-design
收录方: OpenAgentSkill 社区索引

归属链接指向公开仓库或创作者主页。创作者可认领列表以更新所有权信号。

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这条 Registry 收录列表归属于 kwakseongjae，但尚未标记为官方。认领后可增加已验证所有者信号，使后续发布、安装和审计更新更值得信赖。

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[![Listed on OpenAgentSkill](https://www.openagentskill.com/api/badge/kwakseongjae-google-analytics?metric=listed&label=Listed)](https://www.openagentskill.com/skills/kwakseongjae-google-analytics?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[![OpenAgentSkill Trust](https://www.openagentskill.com/api/badge/kwakseongjae-google-analytics?metric=trust&label=Trust)](https://www.openagentskill.com/skills/kwakseongjae-google-analytics?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[![OpenAgentSkill Audit](https://www.openagentskill.com/api/badge/kwakseongjae-google-analytics?metric=audit&label=Audit)](https://www.openagentskill.com/skills/kwakseongjae-google-analytics/audit)
[![Agent Proven](https://www.openagentskill.com/api/badge/kwakseongjae-google-analytics?metric=proven&label=Agent%20Proven)](https://www.openagentskill.com/skills/kwakseongjae-google-analytics?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)

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