Quattr

ai_prompt_coverage_gap

Read-only

AI answer-engine (ChatGPT/Perplexity/Gemini/AI Mode) citations — NOT Google's on-SERP AI Overviews (use competitive_overview/competitive_trends ai_overviews for those). Which AI-answer prompts do we under-appear in? Ranks prompts (the prompt = the tracked keyword) by how few of your pages are cited in the AI answer, so you see coverage gaps at prompt grain. Use for "which AI prompts don't cite us", "AI answer coverage gaps", "prompts where we're missing". Per-segment.

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": {
      "segment": "<segment>",
      "date_range": "<date_range>"
    },
    "name": "ai_prompt_coverage_gap"
  }
}

Input Schema

Name	Required	Description
`brand`	No	Branded vs non-branded prompts.
`top_n`	No
`intent`	No	Restrict to one intent (resolve_entity first).
`segment`	Yes	An ANSWER-ENGINE scope: an AI-visibility tracker id (decomposed to its per-engine segments) or one per-engine segment id. A conventional organic/paid search segment holds no AI-answer citation data and is declined — use market_share_breakdown or gsc_breakdown for that grain. resolve_entity first if unsure.
`platform`	No	Answer engine to scope to ("chatgpt"/"gemini"/"aimode"/"perplexity") — picks that engine's market-share segment when `segment` is a tracker. Omit for all engines.
`date_range`	Yes	Explicit date range, e.g. "2026-05-01 to 2026-05-31". Both endpoints are INCLUSIVE — the END day is covered (a 7-day range = 7 days). Quattr weeks run Sunday–Saturday; for "last week" use the most recent complete Sun–Sat span.

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 19, 2026

TDQS

A4.3/5.0

Behavior4/5

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

Annotations already declare readOnly/openWorld=false, so the safety profile is covered. The description adds genuine behavioral context beyond that: it operates at prompt grain, and a conventional organic/paid search segment is 'declined' (an error behavior). It stops short of describing ranking mechanics or output shape, so 4 rather than 5.

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 resource and the critical disambiguation (not Google AI Overviews) first, then use cases. Dense but mostly earning its place; the quoted use-case list is slightly redundant with the lead sentence.

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 6-param, no-output-schema tool with annotations present, the description covers domain, disambiguation, alternatives, and the segment constraint well. Minor gap: no note on result ordering/pagination behavior for top_n, but the core calling decision is complete.

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 83%, so the schema already documents segment, platform, intent, date_range, and brand thoroughly. The description adds only the clarification that 'the prompt = the tracked keyword' and the per-segment grain, not much beyond the schema. Baseline 3 is appropriate.

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 and resource (ranks AI-answer prompts by how few of your pages are cited) and explicitly distinguishes the scope from Google's on-SERP AI Overviews, naming the sibling tools that cover those. An agent can tell exactly what this returns versus ai_prompt_winners or competitive_overview.

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?

Explicit when-to-use ('which AI prompts don't cite us', 'AI answer coverage gaps') plus explicit when-NOT and alternatives: use competitive_overview/competitive_trends ai_overviews for Google AI Overviews, and market_share_breakdown/gsc_breakdown for organic/paid grain. Also directs resolve_entity first. Nothing left 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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