AEO Copilot MCP Server

get_index_whitespace

Identify prompts and topics in an index where no brand is consistently cited, revealing whitespace gaps to establish authority and improve visibility.

Instructions

Find whitespace opportunities in an index: prompts and topics where no entity is consistently cited (threshold: fewer than 1 consistent entity across at least 50% of runs). These are gaps where a brand could establish authority.

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": {
      "indexId": "<indexId>"
    },
    "name": "get_index_whitespace"
  }
}

Input Schema

Name	Required	Description	Default
`indexId`	Yes	The index UUID from list_indexes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.2.0Aug 30, 2026

TDQS

A4/5.0

Behavior3/5

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

With no annotations, the description carries the burden of behavioral disclosure. It explains the selection threshold and the kind of data examined (prompts and topics), which is useful. However, it does not disclose output format, whether any aggregation or ordering is applied, or that this is purely a read operation beyond what the 'get_' prefix implies.

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?

The description is two sentences with no filler. The first sentence front-loads the purpose and the operational threshold; the second adds practical value by framing the result as an authority-building opportunity. 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?

Given the tool's low complexity (one required parameter) and clear description of the selection criteria and output concept ('prompts and topics'), an agent has enough to invoke it correctly. It lacks explicit return-structure or pagination details, but the expected result type is reasonably inferable.

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%, and the only parameter is indexId, already documented as 'The index UUID from list_indexes'. The description's phrase 'in an index' softly reinforces that the parameter identifies the index, but it adds no new semantic detail beyond what the schema already provides.

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?

The description uses a specific verb-resource pairing ('Find whitespace opportunities in an index') and precisely defines the concept: prompts and topics where no entity is consistently cited, with a concrete threshold. This clearly differentiates the tool from siblings like get_insights or get_index_results by naming the distinctive output type and selection criteria.

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

Usage Guidelines4/5

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

The description provides clear context for when to use the tool: when identifying index-level gaps where a brand could establish authority. It does not explicitly name alternatives or exclusions, but the use case is stated directly rather than left only to inference, so it earns a 4 rather than a 3.

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