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storelift-mcp

storelift-mcp

by vom-core
OverviewSchemaSourceRelated ServersDiscussions(1)Admin
JavaScript
Remote

run_ai_visibility_check

Start an AI visibility sample for one app in a country to measure its presence across AI engines. Uses a plan or purchased run; result via get_ai_visibility.

Instructions

Start an AI visibility sample for one app in one country, with the engines available for the run. Requires Studio or Enterprise and the ai:read scope; Pro's panel allowance does not grant access to this MCP tool. Uses one plan or purchased AI visibility run; get_ai_visibility returns the result. One measurement per app runs at a time.

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": {
      "appId": "<appId>"
    },
    "name": "run_ai_visibility_check"
  }
}

Input Schema

NameRequiredDescriptionDefault
appIdYesapp id from list_apps
countryNocountry code, e.g. tr, us (empty = the app's first three countries)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.5.0

TDQS

A4.6/5.0
Behavior5/5

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

Annotations mark this as a non-read-only, non-idempotent action, and the description adds what they cannot: it consumes one plan or purchased AI visibility run (cost), requires specific entitlement and scope (auth), and is concurrency-limited to one measurement per app. This is rich behavioral context beyond the structured flags.

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?

Four sentences, all informative and front-loaded with the core action. Slightly dense with semicolon-joined clauses, but nothing is wasted and each sentence delivers distinct value.

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 2-parameter action tool with no output schema, the description covers cost, entitlement, scope, concurrency, and where to retrieve results. An agent has everything needed to decide whether and how to invoke it.

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 description coverage is 100%, so both appId and country are already documented, including the empty-country fallback to the app's first three countries. The description only echoes the single-app/single-country framing, adding no syntax or format detail beyond the schema, so baseline 3 applies.

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 (Start) and resource (AI visibility sample) with precise scope: one app in one country, using the available engines. It distinguishes itself from the sibling get_ai_visibility, which it explicitly frames as the tool that returns the result.

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?

Explicitly names the plan tiers that can use it (Studio or Enterprise, not Pro's panel allowance), the required ai:read scope, and points to get_ai_visibility as the retrieval alternative. It also states the concurrency constraint (one measurement per app at a time), leaving little to inference.

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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