Panel de ventas

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

The readOnlyHint annotation already establishes the operation is a safe read; beyond that the description discloses the aggregation scopes it reports (today vs. month, per-shipping-method split, per-province concentration), which is real behavioral context an agent can use. It stops short of stating auth requirements, account-switching behavior, or whether results are cached/real-time.

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?

Two sentences, front-loaded with the substance of the dashboard before the use-case framing, and no filler. Slightly dense but every clause carries distinct content.

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 output schema and only a readOnlyHint, the description carries the burden of describing return content and it does so thoroughly (billing, top products, shipping breakdown, geography). What is missing is differentiation from sibling analytics tools and any note on the optional account-selection flow.

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?

The single optional 'cuenta' parameter is fully documented in the schema (100% coverage), including a pointer to ml_cuentas for discovering user_ids. The description adds no further meaning to that parameter, so the schema does all the work and the baseline of 3 applies.

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 enumerates the concrete contents of the dashboard (facturación de HOY y del MES, productos más vendidos, reparto por método de envío, concentración por provincia), so an agent knows exactly what this tool surfaces. It is specific about the resource but never contrasts itself with likely-overlapping siblings such as ml_metricas or ml_rentabilidad, so sibling differentiation is left to inference.

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 clear usage context with the quoted prompts '¿cómo venimos hoy?' and 'el panel del mes', which tells the agent when this tool is appropriate. However, it offers no exclusions and does not point to alternatives (e.g. ml_metricas) for more granular or time-series analysis.

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