Search Scope AI Visibility Auditor

Generate GEO query universe

generate_geo_query_universe

Read-onlyIdempotent

Generate a commercially useful set of AI-search prompts to monitor for a website, grouped by intent: informational, problem-aware, commercial, recommendation, comparison, alternatives, brand, category, local and trust/validation. Each prompt includes intent, buyer stage, the ideal page type to answer it and a commercial priority (high / medium / low). The brand, services and location are detected from a small crawl of the site; pass service and/or location to override or narrow them (for example one service line, or a city the site does not mention yet). Use it when a user wants a monitoring list for ChatGPT, Claude, Perplexity, Gemini or Google AI Mode, a GEO keyword universe, or prompt ideas per funnel stage. It does NOT return search volumes, does not check which prompts the brand currently appears for, and avoids meaningless long-tail permutations in favour of prompts a real buyer would ask an assistant. Parameters: url (required), service (optional override), location (optional override), count (optional, default 40, max 100).

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": {
      "url": "<url>"
    },
    "name": "generate_geo_query_universe"
  }
}

Input Schema

Name	Required	Description
`url`	Yes	Public website URL to audit, e.g. https://example.com.au. Bare domains are accepted (https is assumed). Private, loopback, internal and IP-literal hosts are rejected.
`count`	No	Number of prompts to return. Default 40, max 100.
`service`	No	Optional service or category override, e.g. 'emergency plumbing' or 'family law'. Replaces the services detected from the site.
`location`	No	Optional location override, e.g. 'Perth' or 'Gold Coast'. Replaces the location detected from the site; pass 'none' to force non-local prompts.

Output Schema

Name	Required	Description	Default
`brand`	Yes
`count`	Yes
`groups`	Yes
`target`	Yes
`queries`	Yes
`category`	Yes
`location`	No
`servicesUsed`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 14, 2026

TDQS

A4.6/5.0

Behavior4/5

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

Annotations already establish readOnly, idempotent, non-destructive and open-world, so the safety profile is covered; the description adds real behavior by disclosing that brand, services and location are auto-detected from a small crawl of the site and can be overridden. It also discloses the quality constraint that permutations are filtered out in favor of plausible buyer questions. It stops short of stating latency or whether the crawl costs anything, which keeps it off a 5.

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

Conciseness4/5

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

Front-loaded with the core act and output shape, then usage triggers, then exclusions — a sensible order for an agent scanning for relevance. The trailing sentence re-listing the four parameters with their required/optional status and defaults duplicates the schema verbatim at 100% coverage and earns little.

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?

Covers the full burden for a generative tool: what it produces, how site context is derived, how overrides interact with detection, and what it deliberately does not do. An output schema exists so return values need no further explanation, and the description still summarizes the per-prompt fields usefully.

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 the baseline is 3, but the description adds semantics the schema does not: service and location act as overrides over crawled detection, and a location may be "a city the site does not mention yet." The count default and max are merely repeated from the schema, which caps this below 5.

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

Purpose5/5

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

States a specific verb and resource ("Generate a commercially useful set of AI-search prompts") and spells out the output shape: intent grouping across ten named buckets, plus intent, buyer stage, ideal page type and commercial priority per prompt. An agent can tell this apart from audit_ai_visibility and extract_site_entities because the description explicitly disclaims search volumes and current-visibility checks.

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

Usage Guidelines5/5

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

Gives concrete when-to-use triggers (a monitoring list for ChatGPT, Claude, Perplexity, Gemini or Google AI Mode; a GEO keyword universe; prompt ideas per funnel stage) and explicit exclusions (no search volumes, no appearance checking, no long-tail permutations). Note the exclusions are framed as non-capabilities rather than routing to a named sibling, but the guidance is unambiguous.

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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