AdLoop

List Analytics custom definitions

list_ga4_custom_definitions

Read-only

List a GA4 property's custom dimensions and custom metrics, with how many slots are left.

Returns each custom dimension's resource name, parameter name, display name, scope (EVENT, USER or ITEM) and description, and each custom metric's resource name, parameter name, display name, measurement unit and description, plus usage per kind against the property's limit (standard: 50 event, 25 user, 10 item dimensions, 50 metrics; 360: 125, 100, 25, 125). Use it before draft_ga4_custom_dimension or draft_ga4_custom_metric. For the field names to use in reports, see list_ga4_dimensions_and_metrics. Reads the GA4 Admin API (customDimensions.list, customMetrics.list).

Google Analytics Data API: https://developers.google.com/analytics/devguides/reporting/data/v1 and Admin API: https://developers.google.com/analytics/devguides/config/admin/v1

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "list_ga4_custom_definitions"
  }
}

Input Schema

Name	Required	Description	Default
`property_id`	No	GA4 property as "properties/123456789" or the bare numeric ID. If empty, uses the default from config.

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

AddedNov 8, 2026

TDQS

A4.4/5.0

Behavior4/5

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

Annotations already declare readOnlyHint, destructiveHint false and openWorldHint, so the safety profile is covered. The description adds genuinely new context beyond that: the underlying Admin API calls (customDimensions.list, customMetrics.list) and the per-kind slot limits for standard (50/25/10/50) versus 360 (125/100/25/125) properties, which tells the agent what the usage figures mean.

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 purpose and organized logically: what it lists, what each record contains, limits, then related tools. The field-by-field enumeration is somewhat redundant given an output schema exists, but it remains dense and readable with no filler sentences.

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

Completeness5/5

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

Given a read-only list tool with one fully documented optional parameter, an output schema, and full annotations, the description covers everything an agent needs: scope, returned fields, quota semantics, and sibling routing. Nothing material for correct invocation is missing.

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 100% for the single property_id parameter, and the schema already documents both the 'properties/123456789' and bare numeric forms plus the config-default fallback. The description adds nothing about the parameter, so this sits at the baseline for a fully documented schema.

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 ('List a GA4 property's custom dimensions and custom metrics') and immediately scopes it further with 'how many slots are left'. It enumerates the exact fields returned per dimension and per metric, so an agent knows precisely what this produces 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 Guidelines5/5

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

Gives explicit sequencing guidance ('Use it before draft_ga4_custom_dimension or draft_ga4_custom_metric') and names the sibling for a different need ('For the field names to use in reports, see list_ga4_dimensions_and_metrics'). Both the when-to-use and the alternative routing are stated outright.

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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