ai-visibility-mcp

Suggest customer questions

suggest_questions

Read-only

Generate realistic customer questions for a business type and city to test how AI assistants recommend local businesses.

Instructions

Generate 8 to 12 realistic questions a customer might ask an AI assistant when looking for this kind of business in this city. Uses the first configured engine to write them, or a built-in template set if none is set up.

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": {
      "businessType": "<businessType>",
      "city": "<city>"
    },
    "name": "suggest_questions"
  }
}

Input Schema

Name	Required	Description
`city`	Yes	For example "Bel Air, MD"
`count`	No
`service`	No	A service to emphasize, for example "AC repair"
`businessType`	Yes	For example "HVAC company" or "med spa"

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Nov 3, 2026

TDQS

A3.6/5.0

Behavior4/5

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

Annotations only declare readOnlyHint=true, yet the description adds real behavioral detail: the engine selection policy ("uses the first configured engine") and a graceful fallback ("a built-in template set if none is set up"). That tells an agent the call will not fail for lack of configuration and that output may vary in style depending on setup. It stops short of describing the exact return shape, but that is a minor omission.

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?

Two sentences, zero filler, with the purpose and quantity front-loaded and the execution/fallback behavior second. Every clause earns its place.

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

Completeness4/5

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

For a read-only generation tool with no output schema, the description conveys the quantity, the input scoping, and the engine/fallback behavior, which is enough to call it correctly. It leaves the exact return format (list of strings? objects with metadata?) unstated, which slightly lowers confidence for an agent that needs to consume the result.

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

Parameters3/5

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

Schema coverage is 75%, so the structured fields already carry most of the meaning. The description reinforces the count range ("8 to 12") and the business/city framing, but never mentions the optional "service" parameter, which is the one field it could have illuminated (e.g., how emphasizing a service changes the generated questions).

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?

The description gives a specific verb and artifact ("Generate 8 to 12 realistic questions a customer might ask an AI assistant") plus the two scoping dimensions (business kind and city), so the output is unmistakable. It never names the siblings ask_engines, check_visibility, or compare_competitors, so the agent must infer on its own that this prepares question seeds rather than executing queries.

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

Usage Guidelines2/5

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

There is no explicit statement of when to call this versus ask_engines or check_visibility, and no prerequisites or exclusions. The usage is only obliquely implied by the phrase "when looking for this kind of business in this city."

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

Deploy Server