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Walma-Labs

ga4-mcp

by Walma-Labs

list_property_annotations

Fetch GA4 property annotations by property ID to review notes on releases, campaigns, changes, and traffic shifts for specific dates.

Instructions

List a property's annotations: notes left in GA4 on specific dates or periods, typically for releases, campaign launches or changes, and traffic jumps or drops with an external cause.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
property_idYesThe Google Analytics property ID: a number, or 'properties/' followed by a number. Use get_account_summaries to find it.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.5/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. 'List' plus the note-like nature of annotations conveys that this is a non-mutating read, but it says nothing about permissions, rate limits, result volume, or ordering. It adds useful domain context (what annotations contain) without covering the operational traits.

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?

A single sentence that front-loads the verb and resource, then spends the remainder clarifying the domain term 'annotation'. Every clause earns its place and nothing is repeated.

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?

There is no output schema and no annotations, so the description is the only source of behavioral information. It conveys the concept of annotations but not the shape of the response (fields, ordering, pagination), which for a list tool leaves a gap despite the simple one-parameter surface.

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% and the single property_id parameter is thoroughly documented in the schema, including the accepted formats and how to discover it via get_account_summaries. The description adds no parameter detail, so the baseline of 3 applies.

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?

The description gives a specific verb ('List') and a precisely scoped resource ('a property's annotations'), then explains what an annotation is in GA4. No sibling tool touches annotations, so an agent can tell this apart from the report/get siblings without opening a schema.

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?

It explains what annotations are and when they typically exist ('for releases, campaign launches or changes'), but never states when to call this tool, what prerequisite (a valid property_id) is needed, or how it relates to alternatives. That context is about the data, not about tool selection.

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