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Lightweight analytics integration

Skill meyverick/agy-skills/skills/lightweight-analytics-integration

A collection of elite, modular, and validated AI agent skills and system rules for Google Antigravity.

Install
npx -y skills add meyverick/agy-skills --skill lightweight-analytics-integration

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Integrates mandatory third-party analytics suites into ads by stripping abstractions. Use when raw, minified core JS layers are required to bypass payload limits.

SKILL.md

2.4 KB, 494 tokens by cl100k_base, as published. Nobody here has run it

Lightweight Analytics Integration

This skill dictates the process of stripping massive analytics SDKs down to their absolute core REST/HTTP layers. It allows the integration of complex tracking systems into hyper-constrained environments (like Playable Ads) without blowing up the payload size.

When to Use

  • Use when a client mandates a specific analytics provider (e.g., Mixpanel, Amplitude) but the official SDK exceeds 100KB.
  • Use when tracking custom funnels directly via REST endpoints.
  • NOT for standard web/mobile apps with no payload limits.

Core Process

Phase 1: SDK Deconstruction

  • Do not use npm install <analytics-sdk>.
  • Read the provider's REST API documentation directly.

Phase 2: The Custom HTTP Wrapper

  • Write a 50-line custom wrapper utilizing the native fetch API.
  • Construct the JSON payload exactly as the REST API expects it.
  • E.g., fetch('https://api.amplitude.com/2/httpapi', { method: 'POST', body: JSON.stringify(payload) });

Phase 3: Session & ID Management

  • Official SDKs handle UUID generation and session tracking automatically. You must implement this manually.
  • Generate a lightweight UUIDv4 or use crypto.randomUUID().
  • Store the session ID in local variables for the duration of the ad lifecycle.

Common Rationalizations

RationalizationReality
"I'll just import the core module of the SDK, it should be small."Even core modules often bundle polyfills, heavy JSON parsers, and retry queues. A custom fetch wrapper is the only way to guarantee a < 5KB footprint.
"I don't need a session ID for these events."Analytics dashboards cannot stitch together user journeys without a consistent Session ID or User ID sent with every custom HTTP request.

Red Flags

  • package.json containing heavyweight analytics dependencies for a playable ad.
  • Fetch wrappers failing to send a consistent session_id across multiple events.

Verification

Before finalizing the lightweight analytics integration:

  • The integration bypasses the official NPM SDK in favor of a raw fetch or Image pixel.
  • A custom Session ID is generated and attached to all events.
  • The total byte footprint of the analytics script is under 5KB.

Gives 0 of the 12 instructions most analytics metrics skills give in 494 tokens

Counted across 368 of the 369 authors here whose files we hold, read 2026-08-06

  • read product marketing context before asking questionsin 18 of 368, across 12 files
  • use lowercase with underscores for event namesin 16 of 368, across 6 files
  • track events for decisions not vanity metricsin 15 of 368, across 5 files
  • use object-action format for event namesin 15 of 368, across 8 files
  • produce a tracking plan documentin 14 of 368, across 4 files
  • Call RUBE_SEARCH_TOOLS first to get current schemasin 13 of 368, across 2 files
  • establish consistent event naming conventions before implementingin 10 of 368, across 4 files
  • Verify dimension and metric compatibility before reportingin 9 of 368, across 2 files
  • Encrypt data at rest and in transitin 9 of 368, across 3 files
  • use snake_case for event namesin 9 of 368, across 5 files
  • monitor technical health during the testin 9 of 368, across 5 files
  • use consistent property namesin 8 of 368, across 4 files

Said here and by no other author read

  • read provider rest api documentation
  • write a custom fetch api wrapper
  • construct expected json payload exactly
  • generate session id manually
  • attach consistent session id to events
  • bypass official npm sdk

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.

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