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Ai search visibility

ai_search_visibility

Check whether the site's page appears in AI search for each target search, at which position, and which sites appear in its place, with plain recommendations. Uses the saved searches or the ones the page suggests when queries is omitted. Send {} to use the saved searches, or the searches the page title and H1 suggest; send {queries} to choose. One index check plus one search per query, each USD 0.00075 when it returns results. A run with the same searches in the last 24 hours comes back with reused: true and no cost. Without a watch package: one run per week, three searches. With one: twenty runs per UTC day, ten searches. Result titles and snippets are third-party data.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "id": "<id>"
    },
    "name": "ai_search_visibility"
  }
}

Input Schema

NameRequiredDescriptionDefault
idYesSite owned by this account.
langNoLanguage of the recommendations.
queriesNoOptional. One to ten searches, 1 to 128 characters each.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.4/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Discloses a lot that annotations do not: per-query cost (USD 0.00075, only when results return), 24h dedup with reused: true and no cost, weekly vs watch-package run/search quotas per UTC day, and that titles/snippets are third-party data. These are exactly the operational facts an agent needs before calling a paid, quota-limited operation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the purpose, then each following sentence carries a distinct operational fact (query defaults, cost, caching, quotas, third-party data). No filler or repetition of schema fields.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with hidden costs, quotas, caching, and optional-query resolution, the description covers every decision an agent must make before calling it, and there is no output schema requiring separate explanation of return values. Nothing material is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so baseline is 3; the description still adds real semantics by explaining what happens when queries is omitted (saved searches or page title/H1 suggestions) and the 1-10 per-run search cap. It does not explain lang, its default, or that it governs the recommendations' language.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

Specific verb and resource: it checks whether the site's page appears in AI search, at what position, which competitors appear instead, and returns recommendations. That is far more concrete than the title. It does not explicitly name sibling tools (ai_search_history, track_search_queries) to separate itself from them, so it stays short of a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives explicit invocation guidance: send {} to use saved/auto-suggested searches, send {queries} to choose. It also states the plan-based run/search limits so an agent knows what is permitted. It lacks explicit when-not-to-use guidance or routing to ai_search_history vs this tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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