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

With no annotations, the description carries the full burden and does so well: it discloses the 503 metrics_recalculating condition with retry guidance and that results are never partial sums, the null-vs-invented-0 semantics, and the delivered/sent denominators for rates. It also flags deprecated alias fields and a cross-tool naming mismatch (bounce_hard_rate vs bounce_rate_hard), which is valuable behavioral context beyond any structured field.

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 purpose and core metric list are front-loaded, and nearly every clause earns its place by encoding return-value semantics that no output schema captures. It is nonetheless a single dense run-on paragraph, which costs it a point on structure.

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?

With no annotations and no output schema, the description compensates by documenting the return shape in depth: rate units and decimals, rate bases, hard/soft bounce separation, total_bounces composition, and the recalculation state. An agent has everything needed to call and interpret the tool.

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?

Schema coverage is 100%, so from/to are already documented, and the baseline would be 3. The description adds meaning the schema lacks: both bounds are inclusive ('ambos incluidos') and the range is interpreted in the account's timezone, which materially affects how an agent sets the parameters.

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?

Names the resource (métricas globales de la cuenta) and enumerates the exact metrics returned (enviados, entregados, abrieron, clic, bajas, rebotes, contactos nuevos), which is concrete enough to distinguish it from list_campaigns or get_subscriber. It explicitly contrasts itself with get_campaign_stats at the end, letting an agent separate the two.

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?

Gives solid selection context: it is scoped to account-wide metrics over a day range, the cohort is the send day (same source as /metricas), and get_campaign_stats is named for the per-campaign case. It stops short of a fully explicit when-to-use-this-vs-that rule, but an agent can route correctly.

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