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Ga4 Report

ga4_report

Run a Google Analytics 4 report (Data API runReport) on a property from ga4_properties. Metrics and dimensions use GA4 API names, e.g. metrics sessions, totalUsers, conversions, purchaseRevenue, ecommercePurchases; dimensions date, sessionDefaultChannelGroup, sessionSourceMedium, landingPagePlusQueryString, itemName, deviceCategory, country. Dates: YYYY-MM-DD, today, yesterday or NdaysAgo. Returns rows plus totals.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoRows to return, 1–1000; default 100.
filterNoKeep only rows whose dimension matches.
accountNoGoogle account e-mail to read as, when you have several; an agent reads as the account connected to it.
metricsYesGA4 metric API names, e.g. ["sessions", "purchaseRevenue"].
end_dateNoYYYY-MM-DD, today, yesterday or NdaysAgo; default yesterday.
order_byNoA metric or dimension to sort by, descending; prefix + for ascending.
propertyYesGA4 property id, e.g. 312345678 (from ga4_properties).
dimensionsNoGA4 dimension API names, e.g. ["date", "sessionDefaultChannelGroup"].
start_dateNoYYYY-MM-DD, today, yesterday or NdaysAgo; default 28daysAgo.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior3/5

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

With no annotations, the description carries the full burden; it does disclose that the tool wraps runReport, returns 'rows plus totals', and notes the account-reading behavior via the account param. It does not state read-only safety, quota/rate limits, or error behavior for a tool with 9 params and no annotation coverage, so meaningful gaps remain.

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-loaded with the core action and tightly packed; the metric/dimension/date lists are long but each item reduces ambiguity for an agent that must supply API names. Little waste, though the enumerated examples could be trimmed.

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 9-param tool with a nested filter object, no annotations and no output schema, the description covers purpose, inputs conventions, and return content ('rows plus totals'). Comments on the nested filter semantics and ordering behavior are left entirely to the schema, but nothing critical is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so baseline is 3, but the description adds genuine value by enumerating non-obvious GA4 API names (sessions, purchaseRevenue, sessionDefaultChannelGroup, landingPagePlusQueryString) and date literal formats beyond the two examples the schema shows.

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 ('Run a Google Analytics 4 report (Data API runReport) on a property from ga4_properties'), which is distinguishable from the sibling ga4_properties that only lists properties. An agent can tell what it produces (analytics rows) without opening the schema.

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?

Implicitly routes the agent to ga4_properties for the property id and gives concrete metric/dimension naming conventions, which is real usage context. It stops short of explicit when-not or alternative selection guidance because no direct reporting sibling exists.

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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