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

Annotations already declare read-only, non-destructive, closed-world behavior, so the description does not need to repeat safety. It adds valuable behavioral nuance by specifying that "usuarios" is the sum of daily users, not unique users for the period—a subtle but important detail for correct interpretation. It does not cover data freshness or timezone handling, but that is a minor gap given the annotations and output schema.

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 description is two sentences and front-loads the metric list before the usage phrases. The first sentence is dense but every clause names a distinct metric or clarifies aggregation, so little is wasted. The synthetic demo marker is non-functional noise, but the rest is efficiently structured.

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?

An output schema exists, annotations cover safety and openness, and the single parameter is fully documented in the schema. The description supplies the metric list, the colloquial query mapping, and the daily-user aggregation caveat, which is everything an agent needs to select and invoke this tool correctly.

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?

There is one parameter (date_range) with 100% schema description coverage, including examples and a default. The description does not add any further meaning or formatting guidance for date_range, so the schema carries the parameter semantics alone, matching the baseline 3.

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 states a specific resource (Google Analytics 4 traffic) and lists the exact metrics returned (sessions, daily user sum, new users, page views, bounce rate, session duration, conversions). It is clear what the tool does, but it does not explicitly name or distinguish itself from sibling summary tools like get_search_console_summary or list_analytics_pages.

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?

It gives clear usage context by mapping common user phrasings ("visitas", "tráfico del sitio", "cuántas personas entraron", "page views") to this tool. However, it does not state when not to use it or name alternative tools for adjacent queries.

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