Quattr

seo_keyword_gap_analysis

Read-only

Where are competitors beating us on keywords? Per-keyword rank comparison against tracked competitors in a segment: losing / winning / not-ranked buckets with gap sizes.

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": "seo_keyword_gap_analysis"
  }
}

Input Schema

Name	Required	Description
`medium`	No	competitor source medium, e.g. "google/organic" (default) or "google/cpc"
`segment`	Yes	Tracked segment ID (market_share_overview lists them if unknown)
`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

A3.8/5.0

Behavior4/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=false, so safety is covered. The description adds genuine behavioral value by disclosing that results are bucketed into losing/winning/not-ranked with gap sizes, telling the agent what kind of comparison output to expect.

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?

Two sentences, zero waste, and the guiding question is front-loaded ahead of the concrete output detail. 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?

For a read-only, closed-world tool with full schema coverage and no output schema, the description conveys purpose and the shape of the result (bucketed gap comparison). It is nearly complete; only explicit differentiation from sibling competitive tools is missing.

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 all three parameters (medium, segment, date_range) are already documented in the schema, including defaults and inclusive-end semantics. The description only loosely gestures at 'segment' and 'tracked competitors' and adds nothing new for medium or date_range, so the baseline of 3 applies.

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 states a specific resource (per-keyword rank comparison against tracked competitors) and scope (a segment), with concrete output framing (losing/winning/not-ranked buckets). It is clear on what it does, but it does not distinguish itself from close siblings like competitive_keyword_ranking or competitive_overview, leaving the agent to infer the difference.

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

Usage Guidelines3/5

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

The opening question 'Where are competitors beating us on keywords?' implies the scenario in which the tool is useful, giving implied usage context. However, there is no explicit when-to-use/when-not guidance and no named alternative among the many competitive_* siblings, so routing decisions remain inferential.

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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