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dataforseo-app-data-api

📁 leonardo-picciani/dataforseo-agent-skills 📅 2 days ago
1
总安装量
1
周安装量
#50093
全站排名
安装命令
npx skills add https://github.com/leonardo-picciani/dataforseo-agent-skills --skill dataforseo-app-data-api

Agent 安装分布

mcpjam 1
claude-code 1
replit 1
zencoder 1
crush 1

Skill 文档

DataForSEO App Data 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

  • “ASO rankings”, “app keyword research”, “app search results”
  • “fetch app reviews”, “review monitoring”, “rating trends”
  • “get app metadata”, “track app updates”, “competitor app analysis”
  • “Google Play”, “Apple App Store”, “app listings search”

Integration Contract (Language-Agnostic)

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

Task vs Live

  • Many App Data endpoints are task-based: task_post -> poll tasks_ready -> fetch via task_get.
  • App listings search is available as Live for some sources.

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)

Google (Google Play):

Apple (App Store):

Business & Product Use Cases

  • ASO tooling: track rankings for app keywords and competitors.
  • Product feedback loops: summarize reviews into themes for PMs.
  • Competitive tracking: monitor competitor listing changes and review shifts.
  • Market research: discover apps by category/geo and map positioning.
  • Reputation monitoring: alerts for rating drops or negative review spikes.
  • Growth experiments: correlate listing copy changes with review sentiment.

Examples (User Prompts)

  • “If you don’t have the skill installed, install dataforseo-app-data-api and then continue.”
  • “Install the App Data skill and track ASO rankings for these keywords in the US and Brazil.”
  • “Fetch new app reviews daily and summarize top themes for product improvement.”
  • “Compare our app listing vs competitors and suggest metadata improvements.”
  • “Monitor competitor app updates and report meaningful changes to descriptions/ratings.”
  • “Build an ASO dashboard: keyword visibility, reviews, and rating trends.”
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