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Live SEO data via DataForSEO MCP server: SERP analysis, keyword research (volume, difficulty, intent, trends), backlink profiles, on-page analysis, competitor and content analysis, business listings, AI visibility (LLM mention tracking), and domain analytics. Requires DataForSEO extension installed.
Passed 14 of 21 test cases with the skill, and 3 of 21 without it.
and 14 more in the full report
11 fixed3 passed either way7 still failing0 broke2 errored
Tokens, turns and time describe resource use, not a dollar price.
One of 11 test cases the skill fixed. Same model, same prompt, with and without the skill.
We want to gather Google Images SERP rankings for 'ergonomic office chairs' to see image position, direct image URLs, and alt text. Many SEO scripts try to call a dedicated google_images_live tool endpoint. How should this request be handled via the active setup?
| Checked | Without skill | With skill |
|---|---|---|
| Refrains from calling a non-existent dedicated Google Images MCP tool. | Missed | Passed |
| Extracts image elements from serp_organic_live_advanced as the fallback data source. | Missed | Passed |
The instructions your model reads when the skill loads.
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 9 API modules with 79+ MCP tools.
This skill requires the DataForSEO extension to be installed:
./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.
DataForSEO charges per API call. Be efficient:
Before every DataForSEO MCP call, run cost estimation:
"${CLAUDE_PLUGIN_ROOT}/scripts/claude-seo" run dataforseo_costs.py check <endpoint> [--count N]
"status": "approved" → proceed with the API call"status": "needs_approval" → show the cost estimate to the user and ask for confirmation before proceeding"status": "blocked" → inform the user that the daily budget limit would be exceeded; do NOT proceedAfter each API call completes, log the cost:
test cases passed, vs 3 / 21 without
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