Métricas de ventas

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

Annotations only declare readOnlyHint=true, so the description adds real behavioral value: it discloses that results are compared against the previous period and that cuenta="todas" consolidates all connected stores. Return format/pagination is not addressed, keeping it short of a 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?

Three compact sentences with the returned metrics front-loaded and the usage hint and special parameter value last. No filler, though the quotation-style usage example is slightly informal for a tool definition.

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?

For a read-only, two-optional-parameter tool with no output schema, the description covers what comes back, the comparison baseline, and the multi-store consolidation case. It is adequate; only the absence of sibling differentiation leaves a small gap.

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% (baseline 3), and the description adds meaning beyond the schema by documenting the special value cuenta="todas", which the schema description (a user_id when multiple accounts are connected) does not mention. The dias parameter is left to the schema.

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 specific resources returned (facturación, unidades, ticket promedio) plus the period-over-period comparison, so an agent knows exactly what this produces. It doesn't explicitly contrast with close siblings like ml_panel_ventas or ml_rentabilidad, but the content is far more specific than a name restatement.

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?

"Ideal para ¿cómo vienen las ventas?" gives an implied usage scenario, and the cuenta="todas" note clarifies one consolidation mode. However, with ~29 siblings including ml_panel_ventas and ml_rentabilidad, no alternative is named and no when-not-to-use condition is given.

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