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

Beyond the annotations (readOnly/idempotent/destructive=false/openWorld), the description discloses a rich set of behavioral traits: no 500-row ceiling, token efficiency, error behavior for `columna` + "conteo", ambiguity handling for numeric text formats, and 'no descuenta preguntas'. It also describes response semantics (filas_usadas, truncation when groups exceed `limite`, behavior when no rows match). No contradiction with annotations.

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 core guidance is front-loaded in the first two sentences and the rest is a tight per-parameter bullet list, so every line earns its place. It is longer than average, but the structure keeps it scannable rather than padded.

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?

Despite 12 parameters and 0% schema coverage, the description covers the aggregate operation, grouping, ordering, weighting, filtering, and limit semantics, plus error and truncation behavior. An output schema exists, yet the description still explains key response fields, so nothing an agent needs to call this correctly is missing.

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 description coverage is 0%, so the description must carry the full load, and it does: it defines `operacion` values, the `columna`/`conteo` incompatibility, `agrupar_por` (up to 3, with example), `limite` (1–200, narrower than the schema's default), `ordenar_por`/`orden` values and defaults, `ponderar_por` semantics, and ties `filtros`/`desde`/`hasta`/`columna_fecha` to the sibling's conventions. Only `tabla` is left implicit, which is self-evident.

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 verb and resource ('Calcula en la base una suma, promedio, conteo, mínimo o máximo, opcionalmente agrupado') and the title frames it as totals/rankings over an OpenArg table. It explicitly distinguishes itself from the sibling `obtener_datos`, so an agent can tell them apart without opening either 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?

It gives explicit when-to-use guidance ('Usala SIEMPRE que necesites un total... o un ranking') and names the alternative it replaces ('en vez de traer filas con `obtener_datos`'). The trade-offs (exact, no 500-row cap, fewer tokens) make the routing decision unambiguous.

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