analytics_data

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

The readOnlyHint annotation already signals this is a safe read operation, and the description complements it by noting the requirement for a connected data source and specifying per-endpoint date ranges (e.g., last 2 months, last 3 months). There is no contradiction between the annotation and the query language used.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The first sentence is a clear, front-loaded summary. The required-ID lookups are explained in one concise sentence, and the endpoints are presented in a scannable bullet list. Every sentence provides necessary context, with no filler or repetition.

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

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

The description covers prerequisites, ID lookup steps, endpoint choices, and the time ranges for each endpoint, which is strong for selecting the right query. It does not describe the output/return format, and with no output schema that information is absent, but the data types listed in the endpoints give reasonable inference.

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

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

The input schema provides no descriptions (0% coverage), so the description carries the full burden. It clearly explains project_id, account_id, and each endpoint enum value along with what data they return. However, the optional 'config' parameter is not mentioned at all, preventing a perfect score.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb and resource: 'Query your Google Analytics 4 data', and enumerates the metrics it covers (sessions, users, conversions, traffic sources, device breakdown). This clearly distinguishes it from sibling tools like search_console_data and google_ads_data, which target different data sources.

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

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

The description gives explicit prerequisites ('Requires a connected GA4 data source') and a clear step-by-step guide to find the required IDs by calling list_projects() and list_connections(). It does not explicitly mention when not to use this tool or name alternatives, but the GA4 scoping makes the intended context clear.

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