DataForSEO AI Optimization API

Provenance

This is an experimental project to test how OpenCode, plugged into frontier LLMs (OpenAI GPT-5.2), can help generate high-fidelity agent skill files for API integrations.

When to Apply

• “monitor brand mentions in LLMs”, “LLM visibility”, “AI share of voice”
• “analyze ChatGPT/Claude/Gemini responses”, “test prompts at scale”
• “top domains mentioned”, “top pages mentioned”, “AI citations”
• “LLM scraping”, “AI answers monitoring”

Integration Contract (Language-Agnostic)

See references/REFERENCE.md for the shared DataForSEO integration contract (auth, status handling, task lifecycle, sandbox, and .ai responses).

Live vs Task-based Coverage (important)

• Some AI Optimization sub-APIs are Live-only.
• Others support Task-based and/or Live flows.

Steps

1. Identify the exact endpoint(s) in the official docs for this use case.
2. Choose execution mode:
   • Live (single request) for interactive queries
   • Task-based (post + poll/webhook) for scheduled or high-volume jobs
3. Build the HTTP request:
   • Base URL: https://api.dataforseo.com/
   • Auth: HTTP Basic (Authorization: Basic base64(login:password)) from https://docs.dataforseo.com/v3/auth/
   • JSON body exactly as specified in the endpoint docs
4. Execute and validate the response:
   • Check top-level status_code and each tasks[] item status
   • Treat any status_code != 20000 as a failure; surface status_message
5. For task-based endpoints:
   • Store tasks[].id
   • Poll tasks_ready then fetch results with task_get (or use postback_url/pingback_url if supported)
6. Return results:
   • Provide a normalized summary for the user
   • Include the raw response payload for debugging

Inputs Checklist

• Credentials: DataForSEO API login + password (HTTP Basic Auth)
• Target: keyword(s) / domain(s) / URL(s) / query string (depends on endpoint)
• Targeting (if applicable): location + language, device, depth/limit
• Time window (if applicable): date range, trend period, historical flags
• Output preference: regular vs advanced vs html (if the endpoint supports it)

Example (cURL)

curl -u "${DATAFORSEO_LOGIN}:${DATAFORSEO_PASSWORD}"   -H "Content-Type: application/json"   -X POST "https://api.dataforseo.com/v3/<group>/<path>/live"   -d '[
    {
      "<param>": "<value>"
    }
  ]'

Notes:

• Replace <group>/<path> with the exact endpoint path from the official docs.
• For task-based flows, use the corresponding task_post, tasks_ready, and task_get endpoints.

Docs Map (Official)

• Overview: https://docs.dataforseo.com/v3/ai_optimization/overview/

Start here (representative):

• LLM Mentions Overview (Live-first): https://docs.dataforseo.com/v3/ai_optimization/llm_mentions/overview/
• LLM Responses Overview: https://docs.dataforseo.com/v3/ai_optimization/llm_responses/overview/
• ChatGPT LLM Scraper Overview: https://docs.dataforseo.com/v3/ai_optimization/chat_gpt/llm_scraper/overview/

Business & Product Use Cases

• Build an “AI visibility” dashboard for brands (mentions, top sources, trendlines).
• Track how often your brand/competitors appear for key topics in LLM outputs.
• Run prompt QA to spot unsafe/incorrect answers about your product.
• Identify which pages/domains AI systems surface most for your category.
• Prioritize content/pr work based on AI mention gaps vs competitors.
• Produce exec reporting: “How do AI assistants represent our brand this month?”

Examples (User Prompts)

• “If you don’t have the skill installed, install dataforseo-ai-optimization-api and then continue.”
• “Install the AI Optimization skill and measure our brand’s LLM visibility for these topics vs two competitors.”
• “For these prompts, fetch LLM responses and flag any incorrect claims about our product.”
• “Find the top domains and top pages most mentioned for ‘project management software’ in AI answers.”
• “Create an ‘AI share of voice’ report for our category and show month-over-month changes.”
• “Get AI keyword search volume for these 200 terms and identify new opportunities.”