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GSCPAP - Google Search Console, GA4, PageSpeed Insights & live SERPs MCP

GA4 audience breakdown

ga4_user_demographics
Read-only

Audience breakdown over the last N days.

Returns three slices:

  • by_country: top countries by activeUsers

  • by_device: deviceCategory (desktop/mobile/tablet) split

  • by_browser: top browsers

Input Schema

NameRequiredDescriptionDefault
daysNo
limitNo
property_idYes

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3/5.0
Behavior3/5

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

Annotations already cover the safety profile (readOnlyHint=true, destructiveHint=false, openWorldHint=true), so the bar is lower. The description adds genuine behavioral context about aggregation semantics — 'top countries by activeUsers', deviceCategory bucketing, 'top browsers' — which annotations cannot convey. It does not mention cost, quotas, or how ranking/cutoffs work, so this is additive but not rich.

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?

It is short and front-loaded, with the scope in line one and the return slices as a scannable list. The only slight waste is spending description space enumerating return fields when an output schema already exists.

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

Completeness3/5

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

For a three-parameter read-only aggregate with an output schema, the description gives enough to know roughly what comes back, and return values need not be re-explained. However, with 0% schema coverage it should clarify property_id's role and the limit behavior, and it gives no guidance on choosing this tool among many GA4 siblings.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must carry parameter meaning, and it only partially does: 'last N days' clarifies the days parameter's window. The 'limit' parameter (presumably top-N per slice) and the required property_id are never mentioned, leaving two of three parameters unexplained in both schema and description.

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 names a concrete resource (audience breakdown) and enumerates the three output slices (by_country, by_device, by_browser), which makes it distinguishable from sibling GA4 tools like ga4_overview or ga4_traffic_sources. It falls short of a full verb+scope statement because it never says explicitly that this reports GA4 demographic/technology dimensions of active users.

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?

There is no when-to-use guidance at all: nothing says to pick this over ga4_overview, ga4_engagement, or ga4_traffic_sources, nor what question it answers. The reader must infer usage entirely from the returned slices.

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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