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Analytics

Deploy privacy-first analytics with correct API patterns, rate limits, and GDPR compliance.

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name: Analytics description: Deploy privacy-first analytics with correct API patterns, rate limits, and GDPR compliance.

Critical Implementation Gotchas

Umami API timestamps: Use milliseconds, not seconds. Date.now() in JS, int(time.time() * 1000) in Python.

Plausible API v2: Requires site_id parameter, NOT domain name. Get site_id from dashboard URL first.

PostHog events: Properties must be JSON serializable. Never pass DOM elements or functions.

Rate limits: Umami 600/hour, Plausible 600/hour, PostHog 1000/minute. Implement exponential backoff on 429.

Environment-Specific Setup

Development: ALWAYS use separate project/site for local testing. Production data pollution is irreversible.

Tracking domains: Never hardcode. Use env vars to switch between localhost and production.

Bot filtering: Enable in settings. Privacy tools have weaker bot detection than Google Analytics.

GDPR Compliance Gotchas

EU visitors need explicit consent even for privacy-first tools. Check IP geolocation before tracking.

Data retention: Set automatic deletion - Umami in Settings > Data, Plausible 30 days max, PostHog in project settings.

Cookie-free warning: Umami/Plausible don't use cookies but still need consent for EU visitors if collecting identifiers.

Runtime Safety

Verify script loads before sending events. Check for umami, plausible, or posthog globals first.

Never track PII (email, names, IP) in custom events. Violates privacy principles.

Batch PostHog events via /batch endpoint. Umami/Plausible require individual requests.

Authentication Patterns

Store API keys in environment variables only. Never hardcode.

Umami: Requires website ID + API key combination.

Plausible: Uses Bearer token authentication.

PostHog: Uses project-specific API key.

如何使用「Analytics」?

  1. 打开小龙虾AI(Web 或 iOS App)
  2. 点击上方「立即使用」按钮,或在对话框中输入任务描述
  3. 小龙虾AI 会自动匹配并调用「Analytics」技能完成任务
  4. 结果即时呈现,支持继续对话优化

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