Quattr

bot_verification

Read-only

Which crawlers claiming to be Googlebot are actually Google? Cross-references the declared bot / user-agent against IP verification to separate verified Googlebot hits from spoofers. Use for "are fake Googlebots hitting us", "verify our crawler traffic".

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": {
      "date_range": "<date_range>"
    },
    "name": "bot_verification"
  }
}

Input Schema

Name	Required	Description	Default
`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

A4.2/5.0

Behavior4/5

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

Annotations already declare the read-only and non-destructive nature. The description adds the method (IP verification cross-reference) and the output distinction (verified vs. spoofers), which is useful behavioral context. It doesn't detail return format or limitations, but with annotations covering safety, this is sufficient.

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 tight sentences plus example queries, front-loaded with the core question and method. Every sentence earns its place without redundancy.

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 one fully-specified parameter, safety annotations, and no output schema, the description is complete enough to call the tool correctly. A minor gap is the absence of any hint about output shape, but that's not required without an output schema.

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?

The single date_range parameter has 100% schema description coverage, including inclusive end date and week definition. The description adds no extra parameter hints, so 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?

It states a specific question and verb: cross-references declared bot/user-agent against IP verification to separate verified Googlebot hits from spoofers. This clearly distinguishes it from generic crawler analysis tools by focusing on Googlebot spoofing.

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?

Two explicit example queries guide the agent ('are fake Googlebots hitting us', 'verify our crawler traffic'). However, no when-not conditions or alternative tool names are given, so it's clear context without exclusions.

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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