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scalably-io

Google Analytics 4 MCP

by scalably-io

ga4_check_compatibility

Read-only

Check whether selected dimensions and metrics can be queried together before running a report, preventing costly errors.

Instructions

Validate whether a dim/metric combo can be queried together. Cheap pre-flight.

compatibility_filter: 'COMPATIBLE' (default, returns only fields that work with the provided selection) or 'INCOMPATIBLE' (returns only fields that would conflict).

Use before run_report when composing exploratory queries, cheaper than catching a GoogleAdsException after a big failed report.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
metricsNo
dimensionsNo
property_idYes
metric_filterNo
dimension_filterNo
compatibility_filterNoCOMPATIBLE

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv1.0.0

TDQS

A4.4/5.0
Behavior4/5

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

readOnlyHint already covers safety; the description adds behavioral value by saying it is a cheap pre-flight, by documenting that compatibility_filter returns only working or conflicting fields, and by framing it as a guard against expensive failures. No contradiction.

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?

Every sentence earns its place: purpose first, then the one non-obvious parameter, then usage context. The formatting is scannable and free of filler.

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?

With readOnlyHint, openWorldHint, and an output schema, the description covers the main invocation context and the compatibility_filter semantics. It is only slightly incomplete on the exact interpretation of the filter/parameter fields for an agent unfamiliar with GA4.

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 0%, so the description must compensate. It fully explains compatibility_filter and references metrics/dimensions, but metric_filter, dimension_filter, and property_id are left to be inferred from names and schema, which is only partial compensation.

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?

Opening states a specific verb-resource pair: 'Validate whether a dim/metric combo can be queried together.' The phrase 'Cheap pre-flight' and comparison to run_report make its purpose distinct from the reporting siblings.

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?

Explicitly instructs when to use it: 'Use before run_report when composing exploratory queries.' It also gives the alternative (run_report) and the cost-based rationale, so an agent can decide without guessing.

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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