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google-data-mcp

google-data-mcp

by seliem-attia

GA4: Create custom metric

ga4_create_custom_metric

Creates a custom event-scoped metric for a GA4 property to track numeric event parameter values.

Instructions

Creates a custom metric (event scope) for a numeric event parameter.

Input Schema

NameRequiredDescriptionDefault
propertyYesGA4 property ID, e.g. '123456789' or 'properties/123456789'
descriptionNo
displayNameYes
parameterNameYes
measurementUnitNoDefault STANDARD

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.6.1

TDQS

B3.1/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=false, destructiveHint=false and openWorldHint=true, so the mutation and external-visibility profile is covered. The description adds that scope is fixed to 'event', narrowing behavior beyond the schema, but says nothing about whether the metric becomes active immediately, whether it can be removed afterwards, or which permissions the caller needs.

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?

One front-loaded sentence with zero filler; the constraint on the parameter type appears before any secondary detail. It is efficient but perhaps too terse for a mutation tool with five parameters.

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?

For a five-parameter write operation with no output schema and only 40% parameter coverage, the description omits return shape, preconditions, and post-creation state. The annotation set covers safety hints, but the agent still lacks enough to invoke this confidently or to recover from failure.

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 40%, below the compensated threshold, so the description must carry more weight. It does add the key constraint that parameterName must refer to a numeric event parameter and that scope is not configurable, but it says nothing about description, displayName, or the measurementUnit enum that the schema documents only as 'Default STANDARD'.

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?

States a specific verb and resource ('Creates a custom metric') plus a scope constraint ('event scope') and a precondition ('for a numeric event parameter'). This implicitly separates it from ga4_create_custom_dimension, though the sibling is never named.

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

Usage Guidelines2/5

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

No when-to-use or when-not-to-use guidance, no mention of alternatives such as creating a dimension or a key event, and no prerequisite steps (parameter must already be collected, property ID format). The only inference available is that the target parameter must be numeric.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.