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by ai.howseen
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Run a visibility scan

run_scan

Scan the brand's prompts on the AI engines now, with the same limit as the dashboard Run now button (a fresh scan at most once per brand per plan cadence: every 72h, every 24h on Business; prompts added since the last scan can be scanned alone; an unfinished scan can be continued). Preview first; confirm: true runs about 45 seconds per call.

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": "run_scan"
  }
}

Input Schema

NameRequiredDescriptionDefault
brandNoBrand id, name or domain (from list_brands). Optional when the account has a single brand.
confirmNoLeave out (or false) to get a preview: nothing changes. Set true ONLY after the user approved that exact preview.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.7/5.0
Behavior5/5

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

Annotations cover the safety profile (readOnlyHint=false, destructiveHint=false, openWorldHint=true), and the description adds real behavior beyond them: preview changes nothing, confirm=true actually runs, and each call takes about 45 seconds. It also discloses the rate-limit/cadence constraint, which is exactly the kind of context annotations don't carry.

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-loads the action, then packs constraints into a parenthetical and closes with the preview/confirm rule and timing. Dense but every clause earns its place; the nested parenthetical makes it slightly harder to parse than ideal.

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 2-parameter action tool with no output schema, the description covers action, constraints, timing, and the required confirmation flow. The one gap is that it doesn't say what the preview returns, though the absence of an output schema makes that a minor omission.

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 both parameters are already documented (baseline 3). The description still reinforces the semantics of 'confirm' by tying it to the preview step ('Preview first; confirm: true runs') and adds the cadence meaning of 'brand' scoping, giving modest value beyond the schema.

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 (scan) and resource (the brand's prompts on the AI engines now), and the scope is unambiguous. No sibling tool performs scanning, so an agent can identify this as the action-triggering tool without opening the schema.

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 explicit when/when-not conditions: the once-per-cadence limit (72h, or 24h on Business), that prompts added since the last scan can be scanned alone, and that unfinished scans can be continued. The preview-then-confirm workflow is spelled out as the required procedure.

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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