visibility

Your buyer questions

list_buyer_questions

Read-onlyIdempotent

Each buyer question FrontStat asks the AI search engines about your market, with yes or no per engine: does the answer recommend your product. Needs a FrontStat plan (Lite or Pro): send your dashboard token as a Bearer token. Covers the domain on your subscription.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

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

Input Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 1, 2026

TDQS

A3.8/5.0

Behavior4/5

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

Beyond the annotations, the description adds useful behavioral context: it requires a paid plan, needs a Bearer token, and covers the subscribed domain. It also discloses the output shape as per-engine yes/no answers to buyer questions. It does not cover rate limits or pagination, but the important access constraints are surfaced.

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?

Three short sentences with no wasted wording. The purpose is front-loaded, followed by access requirements and scope, making it easy to scan.

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?

With no parameters and no output schema, the description carries the burden of explaining the return value and access conditions. It does both: it says each buyer question includes per-engine yes/no recommendation outcomes and states the required plan and authentication.

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?

The tool takes zero parameters, so there is no parameter semantics for the description to compensate for. Baseline score is appropriate.

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 clearly identifies the returned resource: buyer questions FrontStat asks AI search engines about the market, with per-engine yes/no recommendation results. It is specific enough for an agent to understand the tool's purpose, though it does not explicitly differentiate itself from siblings such as get_visibility or who_wins_instead.

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?

The description states prerequisites (Lite/Pro plan, Bearer token) and scope (domain on the subscription), but does not say when to use this tool versus alternatives. There is no explicit guidance, exclusion, or comparison to sibling tools.

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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