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

With no annotations, the description carries the full burden and mostly delivers: it discloses cost (free), data provenance (invented, not from Mercado Libre), and the key risk (unusable for decisions). It omits operational details such as whether authentication or rate limits apply, but the main behavioral hazard is flagged unambiguously.

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 short sentences with zero filler; the free/paid distinction is front-loaded as "GRATIS" and the disclaimer about fake data follows immediately. Every sentence adds a distinct fact.

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 zero-parameter preview tool with no output schema, the description covers what matters: the return is a sample report matching `informe_oportunidad`'s format and the data is fabricated. It leaves the concrete report fields to the sibling's definition rather than describing them here.

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 tool takes zero parameters, so there is no parameter meaning to add and the baseline applies. The description correctly implies no input is needed.

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 ("Devuelve un informe de muestra") and explicitly anchors it to the sibling `informe_oportunidad` as the same format with fabricated data. An agent can distinguish the sample report from the real one 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?

Gives explicit usage context ("ver qué vas a recibir antes de pagar") and an explicit when-not ("no sirven para decidir"), which is strong guidance. It stops short of a direct instruction to switch to `informe_oportunidad` for real decisions, relying on the reader to infer it.

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