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konkomaji

Google Marketing MCP

by konkomaji

gsc_compare_periods

Compare a current period against the previous equal-length window to identify biggest gainers and losers by dimension (query, page, country, device).

Instructions

Compare a window against the equal-length window immediately before it, and return the biggest gainers and losers.

This is the tool for "what changed". The API cannot diff periods itself, so this runs both windows and joins them.

Args: dimension: query, page, country, or device. days: length of each window (default 28, so 28 vs the prior 28). limit: how many gainers and how many losers to return.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
daysNo
limitNo
end_dateNo
site_urlNo
dimensionNoquery
start_dateNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.8/5.0
Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It also contributes useful implementation context by revealing 'the API cannot diff periods itself' and that the tool 'runs both windows and joins them'. It does not, however, say whether this is a read-only operation, how change is measured (absolute vs percentage), or how winners/losers are sorted.

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 short and front-loaded: the first sentence states the core operation, and the bullet list adds just enough per-parameter context. There is no fluff, and every sentence contributes to the correctness of the call.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Output schema exists, so return shape does not need to be described. But the tool has 6 parameters and 0% schema description coverage, yet the description does not explain how site_url/start_date/end_date anchor the comparison windows. This is a material gap given that the description is the only source for parameter semantics and behavior.

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 schema has 0% description coverage, so the description should compensate? it adds real values for dimension (allowed values), days (window length), and limit (count of results). But it leaves site_url, start_date, and end_date unexplained, which are crucial for selecting the site and the comparison window, so roughly half the parameters remain underspecified.

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 states a specific operation (compare current equal-length window with preceding equal-length window) and a clear output (biggest gainers and losers). It also describes itself as the tool for "what changed", which differentiates it from sibling tools that return raw analytics or audience lists, even though siblings are not named.

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?

Phrase 'This is the tool for "what changed"' clearly tells when to select this tool, and the note about the API not being able to diff periods explains why the tool exists. However, it does not mention sibling alternatives or explicit when-not-to-use cases, so the agent has to infer exclusion scenarios.

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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