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

Annotations already declare readOnly/idempotent/non-destructive/openWorld, so safety is covered; the description still adds non-obvious behavior: freshness is the source read date, not the data date, and a table is not 'current' merely because it was read today. It also implies it does not consume the question quota ('No descuenta preguntas'), though that phrase is left unexplained. Some of this restates output-schema fields, which caps it below 5.

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 output contents are front-loaded in the first sentence, followed by parameter sourcing, usage routing and freshness caveats. It is efficient overall, but the date-semantics passage is somewhat meandering and the trailing 'No descuenta preguntas' is cryptic without explanation.

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, so return fields need not be re-explained, yet the description still clarifies the non-obvious freshness semantics and where to source the parameter. With annotations and output schema already present, the only real gap is the unexplained quota statement, leaving the definition effectively complete for correct invocation.

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 0% for the single parameter, so the description carries the burden, and it does: `tabla` is defined as the identifier returned by buscar_datasets. That is the crucial semantic an agent needs and it is not in the schema. It does not give format or naming examples, so it is not fully exhaustive.

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?

States a specific verb and resource (muestra ... una tabla) and enumerates exactly what it returns: columns with types, row count, covered period, freshness and a sample. It also distinguishes itself from siblings by positioning itself upstream of obtener_datos/agregar_datos and downstream of buscar_datasets, so an agent can place it without opening any schema.

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?

Explicitly instructs the agent to use it before obtener_datos or agregar_datos in order to learn which columns to request and which dates exist, naming both alternatives and the condition that selects this tool. No when-not rule is given, but the routing condition is unambiguous.

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