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Getting started

  • Welcome
  • Quickstart
  • Core concepts

Guides

  • Creators & Accounts
  • Creators
  • Instagram tracking
  • YouTube tracking
  • Videos
  • Campaigns
  • Creator Goals
  • Tracking Inbox
  • Content calendar
  • How scraping works
  • Analytics & metrics
  • Similar creator pools
  • Over-posting & suppression
  • Program Health
  • Sentiment Radar
  • API keys
  • Limits & plan tiers
  • Notifications
  • Payouts
  • Shareable creator pages
  • Conversions

API reference

  • Overview
  • Authentication
  • Errors
  • Projects
  • Creators
  • Accounts
  • Share Links
  • Videos
  • Content Groups
  • Campaigns
  • Analytics
  • Aggregate Analytics
  • Goal Compliance
  • Payouts
  • Conversions
  • Schema

For agents

  • Agent guide
  • Data model
  • MCP & tooling

Platform

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DocsFor agents

Agent guide

How AI agents should use the trackagoat API to analyze TikTok creator program data.

PreviousSchemaNextData model

On this page

  • Getting started
  • The accounts model
  • Reading context (readme) fields
  • Storing analysis back
  • Recommended workflows
  • Analyze campaign performance
  • Find underperforming creators
  • Content analysis across a campaign
  • Trend analysis over time
  • Pagination
  • Writing data with the API
  • Add a creator to a project
  • Trigger a fresh data pull
  • Write analysis notes back to the creator
  • Full workflow: add → scrape → analyze → write back
  • Idempotency in agentic loops
  • Important caveats