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

Annotations already declare readOnly, idempotent, non-destructive and openWorld. The description adds genuinely useful non-schema behavior: it enumerates what is returned and notes "No descuenta preguntas" (does not consume quota), which the annotations do not cover. Not fully exhaustive, but valuable context beyond structured fields.

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?

Front-loaded with what is returned, followed by input provenance and usage ordering. Three short lines, no filler, everything earns its place.

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 values need not be explained, yet the description still summarizes them, and it documents the one undocumented parameter and the call ordering. Adequate for a simple one-param read tool; only minor edge cases (matching rules, error behavior) are unaddressed.

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 must compensate, and it does: it explains that `tabla` is the name returned by buscar_datasets. It does not specify case sensitivity or exact matching rules, but the origin/format meaning is conveyed.

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 plus concrete outputs (columnas con tipo, cantidad de filas, período cubierto, muestra). It also names which sibling produces its input (buscar_datasets) and which it precedes (obtener_datos), so an agent can place it in the workflow without opening schemas.

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?

"Usalo antes de obtener_datos para saber qué columnas pedir y qué fechas existen" gives explicit ordering and rationale, and it clarifies where `tabla` comes from. It stops short of stating when not to use it or naming a competing alternative, but the sequencing guidance is clear.

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