Agent skill · Data & Analytics

seo-dataforseo

Live SEO data via DataForSEO MCP server. SERP analysis (Google, Bing, Yahoo, YouTube, Google Images), keyword research (volume, difficulty, intent, trends), backlink profiles, on-page analysis (Lighthouse, content parsing), competitor analysis, content analysis, business listings, AI visibility (ChatGPT scraper, LLM mention tracking), and domain analytics. Requires DataForSEO extension installed. Use when user says "dataforseo", "live SERP", "keyword volume", "backlink data", "competitor data", "AI visibility check", "LLM mentions", "image SERP", "google images", "image rankings", or "real sea

Infrasity-Labsgithub.com/Infrasity-LabsGitHub ↗
claude-codeMIT
Install
npx skills add Infrasity-Labs/dev-gtm-claude-skills --skill seo-dataforseo --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 3
SKILL.md size: 17 KB
Bundled scripts: none
Requires: Requires DataForSEO MCP server
Path: .claude/skills/seo-dataforseo/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 97
Language: Python

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# DataForSEO: Live SEO Data (Extension) Live search data via the DataForSEO MCP server. Provides real-time SERP results (organic + images), keyword metrics, backlink profiles, on-page analysis, content analysis, business listings, AI visibility checking, and LLM mention tracking across 10 API modules with 79+ MCP tools. ## Prerequisites This skill requires the DataForSEO extension to be installed: ```bash ./extensions/dataforseo/install.sh ``` **Check availability:** Before using any DataForSEO tool, verify the MCP server is connected by checking if `serp_organic_live_advanced` or any DataForSEO tool is available. If tools are not available, inform the user the extension is not installed and provide install instructions. ## API Credit Awareness DataForSEO charges per API call. Be efficient: - Prefer bulk endpoints over multiple single calls - Use default parameters (US, English) unless user specifies otherwise - Cache results mentally within a session; don't re-fetch the same data - Warn user before running expensive operations (full backlink crawls, large keyword lists) ## Cost Guardrails **Before every DataForSEO MCP call**, run cost estimation: ``` python scripts/dataforseo_cost

What's inside
Steps it walks through
  1. Prerequisites
  2. API Credit Awareness
  3. Cost Guardrails
  4. Quick Reference
  5. SERP Analysis
  6. /seo dataforseo serp <keyword>
  7. /seo dataforseo serp-youtube <keyword>
  8. /seo dataforseo youtube <videoid>
  9. /seo dataforseo serp-images <keyword>
  10. Keyword Research
  11. /seo dataforseo keywords <seed>
  12. /seo dataforseo volume <keywords>
  13. /seo dataforseo difficulty <keywords>
  14. /seo dataforseo intent <keywords>
Ships with 2 files
  • references/cost-tiers.md
  • references/tool-catalog.md
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About this skill
What does the seo-dataforseo skill do?

Live SEO data via DataForSEO MCP server. SERP analysis (Google, Bing, Yahoo, YouTube, Google Images), keyword research (volume, difficulty, intent, trends), backlink profiles, on-page analysis (Lighthouse, content parsing), competitor analysis, content analysis, business listings, AI visibility (ChatGPT scraper, LLM mention tracking), and domain analytics. Requires DataForSEO extension installed. Use when user says "dataforseo", "live SERP", "keyword volume", "backlink data", "competitor data", "AI visibility check", "LLM mentions", "image SERP", "google images", "image rankings", or "real sea

How do I install it?

Run `npx skills add Infrasity-Labs/dev-gtm-claude-skills --skill seo-dataforseo --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From Infrasity-Labs/dev-gtm-claude-skills, a repository with 97 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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