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Google Analytics (unofficial)

List supported marketing reporting sources, metrics, and dimensions

marketing_get_catalog
Read-only

Use this when the user wants to discover the canonical marketing reporting graph, available sources, supported metrics, supported dimensions, or which connectors are live today. Each source also reports a passthrough field describing whether native fields beyond the curated list are accepted (GA4 accepts any native dimension/metric; Search Console accepts any native dimension; Bing is limited to the curated fields). Do not use this for GA4 account discovery or data retrieval.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sourceNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
metricsYes
sourcesYes
versionYes
dimensionsYes

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, and non-destructive behavior. The description adds beneficial context about the `passthrough` field behavior per source and the dynamic nature of live connectors, which goes beyond the annotations. 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?

Three sentences, front-loaded with use cases, then a specific output field callout, then an exclusion. Every sentence contributes meaning without 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?

Output schema exists so return values don't need detailed explanation. The description covers when to use, what it provides, and a key behavioral nuance. However, the undocumented `source` parameter leaves some ambiguity for correct invocation.

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

Parameters1/5

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

Schema coverage is 0% and the description never mentions the optional `source` parameter, its accepted values, or how it affects results. The description fails to compensate for the schema's complete lack of documentation.

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?

The description clearly states the tool lists the marketing reporting catalog (sources, metrics, dimensions, connectors), with a specific verb and resource. It does not explicitly differentiate from the sibling marketing_get_sources, which may also list sources.

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?

It explicitly says when to use ('when the user wants to discover...') and provides a clear negative case ('Do not use for GA4 account discovery or data retrieval'), but does not name alternative sibling tools.

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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TDQS

A4.2/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose: catalog for schema discovery, report for standard reporting, funnel for conversion analysis, sources for account/property discovery, and manage_surface for selector management. There is no overlap or ambiguity between them.

Naming Consistency5/5

All tool names follow a consistent marketing_verb_noun pattern: get_catalog, get_funnel, get_report, get_sources, and manage_surface. The verb and noun structure is uniform and predictable.

Tool Count5/5

Five tools is well-scoped for an analytics server, covering discovery, reporting, funnel analysis, source/account listing, and surface configuration without being bloated or too thin.

Completeness5/5

The tool surface covers the core analytics lifecycle: discover schema (catalog), connect to sources (sources), manage settings (manage_surface), and retrieve data (report and funnel). No obvious gaps exist; even advanced needs like pass-through dimensions are handled within get_report.

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