dataforseo-labs-api_skill

This skill helps you run SEO research workflows with DataForSEO Labs to discover competitors, generate keyword ideas, and analyze markets.

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Bundled Files

2 months ago

Catalog Refreshed

4 months ago

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Readme & install

Copy the install command, review bundled files from the catalogue, and read any extended description pulled from the listing source.

Installation

Preview and clipboard use veilstrat where the catalogue uses aiagentskills.

npx veilstrat add skill leonardo-picciani/dataforseo-agent-skills --skill dataforseo-labs-api

  • SKILL.md4.7 KB

Overview

This skill connects to the DataForSEO Labs API to run fast, research-grade SEO workflows for competitive research, keyword discovery, and market analysis. It supports both interactive live queries and task-based batch jobs, returning normalized summaries plus raw payloads for debugging. Use it to identify SERP competitors, surface keyword opportunities, and estimate traffic potential across markets.

How this skill works

The skill calls DataForSEO Labs endpoints (live or task-based) with HTTP Basic auth and project-specified parameters: keywords, domains, locations, languages, device, and date range. For live workflows it issues single POST requests and returns results immediately. For task-based flows it posts tasks, polls task status (or accepts pingbacks), retrieves final results, validates status codes, and normalizes output including any error messages.

When to use it

  • Find competing domains and SERP-level competitors for target queries or topics.
  • Run keyword idea generation and related-keyword discovery across specific markets.
  • Perform keyword gap analysis to see what competitors rank for that you don’t.
  • Estimate traffic potential and prioritize content opportunities by market and device.
  • Automate periodic portfolio analysis or scheduled market snapshots.

Best practices

  • Use official Locations/Languages reference to avoid invalid geo/language inputs.
  • Choose live endpoints for exploratory research and task-based endpoints for high-volume or scheduled jobs.
  • Always validate top-level status_code == 20000 and each tasks[].status; surface status_message on failure.
  • Store tasks[].id and use tasks_ready/task_get for reliable polling; support webhooks/pingbacks if available.
  • Return both a concise normalized summary and the raw JSON response for auditability and debugging.

Example use cases

  • Generate top 20 keyword ideas for "remote onboarding" tailored to US desktop users and estimate monthly traffic.
  • Run a keyword gap report comparing your domain vs three competitors in the UK and export intersecting keywords.
  • Create a competitor landscape with domain intersections and top ranking pages for a product category.
  • Schedule weekly market snapshots to track historical SERP shifts and domain rank changes across regions.
  • Estimate traffic potential for a 30-keyword list and produce a proposed content roadmap prioritized by opportunity.

FAQ

HTTP Basic Auth using your DataForSEO login and password (Authorization: Basic base64(login:password)).

When should I use live vs task-based endpoints?

Use live endpoints for interactive, single-request queries; use task-based endpoints for high-volume, long-running, or scheduled jobs that require polling or webhooks.

How do I know a response succeeded?

Treat any top-level status_code != 20000 as failure and inspect tasks[].status and status_message for per-task errors.

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