name: cloudplus-google-analytics description: Use when Codex needs to answer Google Analytics / GA4 questions through the CloudPlus project's Google Analytics MCP workflow, including traffic reports, events, conversions, funnels, realtime activity, account/property metadata, custom dimensions or metrics, and Google Ads links. Prefer the remote SSH stdio MCP runner when local Google ADC is unavailable.

Google Analytics

Overview

Use the project Google Analytics MCP workflow for GA4 read-only analysis. The Skill is stored in this repository for partner/project use; the MCP server normally runs on the cloud host through SSH stdio and a temporary Docker runner.

Primary project reference:

• docs/GOOGLE_ANALYTICS_MCP.md

Runtime Model

Preferred first-stage runtime:

local MCP client / local Skill
  -> ssh -T cloud host
  -> docker run --rm -i cloudplus/analytics-mcp
  -> cloud-host ADC credential mount
  -> Google Analytics Admin API / Data API

Do not ask users to configure local Google ADC when the project cloud runner is available.

When To Use

Use this Skill for:

• GA4 traffic, acquisition, engagement, retention, or conversion analysis.
• Event popularity, event parameters, custom dimensions, and custom metrics.
• Funnel or path-style questions that can be answered by GA Data API reports.
• Realtime active user questions.
• Account/property discovery and property configuration questions.
• Google Ads link discovery for GA properties.

Do not use this Skill for:

• Editing GA4 configuration.
• Writing credentials into .env, source files, or chat output.
• Non-GA SEO checks such as Google Search Console unless another project doc/tool covers it.

Workflow

1. Read docs/GOOGLE_ANALYTICS_MCP.md if the runtime, credential, or cloud runner setup is relevant.
2. Confirm the MCP server is available in the MCP client. If unavailable, report that analytics-mcp must be configured through SSH stdio.
3. If the GA4 property is ambiguous, call get_account_summaries first.
4. For property metadata, use get_property_details, list_google_ads_links, or get_custom_dimensions_and_metrics.
5. For historical reports, require or clearly infer:
6. property id
7. date range
8. metrics
9. dimensions
10. filters or comparisons
11. For live activity, use run_realtime_report, not historical report tools.
12. Summarize results with the property, date range, dimensions, metrics, filters, and any assumptions.

Defaults

When the user omits details and the request is low risk:

• Date range: use last 28 days for trend/report questions.
• Realtime: use run_realtime_report.
• Property: discover with get_account_summaries rather than guessing.
• Sorting: sort descending by the primary metric.
• Limit: keep result sets small enough to explain clearly.

State all defaults in the final answer.

Report Guidance

Prefer concise, decision-oriented summaries:

• Start with the main finding.
• Include a compact table when comparing dimensions such as page path, event name, country, channel, or campaign.
• Mention whether metrics are users, sessions, event count, conversions, revenue, or another GA metric.
• Avoid overclaiming causality from descriptive GA reports.
• Call out sparse data, sampling/thresholding, missing property access, or unclear date ranges.

Credential Safety

小蔥技能7w4.net持續更新中。

• Never request or expose credential JSON content.
• Never suggest committing ADC files, service-account keys, or OAuth client JSON files.
• Treat SSH aliases, hostnames, credential paths, and property IDs as deployment-sensitive when the user has not already disclosed them.
• If credential setup is needed, point to docs/GOOGLE_ANALYTICS_MCP.md and keep examples placeholder-based.

Partner Project Notes

This repository keeps the Skill source under skills/cloudplus-google-analytics/ for project maintainers and partners. A local Codex installation may need to copy or symlink this folder into its user-level Skill directory before automatic triggering works.

這是一個專注於 Google Analytics 資料分析的實用 Skill，文件內容詳細，清晰地說明了何時使用、如何使用以及安全注意事項，對新手友好。配置簡潔，上手難度不高。主要不足是缺少實際使用示例，且 agent 配置較為簡單，可能影響某些場景下的觸發準確率。總體質量良好，適合有 GA4 分析需求的使用者使用。