dataforseo-ai-optimization-api_skill

Overview

This skill measures AI/LLM visibility and extracts AI-related signals using the DataForSEO AI Optimization API. It helps surface LLM mentions, quantify AI visibility, and collect LLM responses for analysis. The output is normalized summaries plus raw payloads for validation and debugging.

How this skill works

The skill calls DataForSEO AI Optimization endpoints (live or task-based) to collect LLM mentions, LLM responses, and AI scraping results. It authenticates with HTTP Basic, posts the JSON payload required by the chosen endpoint, and validates top-level status and each task status before returning results. For task flows it stores task IDs, polls tasks_ready (or uses a webhook), then fetches task_get to retrieve final results.

When to use it

• Monitor brand mentions and share-of-voice across LLM outputs
• Compare how multiple LLMs (ChatGPT, Claude, Gemini) present your product
• Run large-scale prompt QA to surface incorrect or unsafe claims
• Identify top domains and pages cited by LLM answers for a category
• Schedule recurring visibility checks using task-based jobs

Best practices

• Select Live for quick interactive checks and Task-based for scheduled or high-volume jobs
• Always validate status_code == 20000 and inspect tasks[].status and status_message
• Store tasks[].id and use tasks_ready + task_get or postback_url for reliable retrieval
• Include location, language, device, and time window when targeting regional insights
• Return both a normalized summary and the raw API payload for auditability

Example use cases

• Build an AI visibility dashboard showing mentions, top sources, and trendlines for your brand
• Run batch prompt tests to flag incorrect claims about product features across LLMs
• Generate a monthly 'AI share of voice' report comparing brand vs competitors
• Find top domains and pages surfaced by LLMs for 'project management software' search prompts
• Fetch LLM responses for a set of prompts and highlight citations and content gaps