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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false and openWorldHint=false, so the safety profile is fully covered. The description adds one genuinely useful behavioural fact beyond that: it collects no user data and the user must write to the contact directly, which prevents an agent from attempting a lead-capture flow. It does not explain what happens when the price is not published (empty field? alternative text?), which is the main behavioural unknown here.

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 short sentences, front-loaded with the payload (model, price, contact) and followed by the one constraint that matters (no data collection). No filler, no repetition of the title, and the conditional 'si está publicado' is compactly handled.

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, read-only informational tool with full annotation coverage and no output schema, the description covers what is returned and how the user should proceed. The only gap is that it does not say how to present the result when price is unpublished or contact data is missing, a minor omission for a tool this simple.

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 nothing for the description to disambiguate; the baseline for a parameterless tool is 4 and the description correctly creates no false expectation of input. It even clarifies the interaction model (direct contact, no data collection), which is the only semantic an agent could get wrong.

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 names three concrete things the tool returns: the contracting model, the price (with the caveat 'si está publicado'), and a direct contact for requesting a demo. That is a specific verb-plus-resource purpose an agent can match to a pricing/demo question. It stops short of naming any sibling tool, so differentiation from preguntas_frecuentes or seguridad_y_datos relies on the agent inferring from the topic.

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?

Usage is implied rather than stated: an agent can infer it should call this when a user asks about price, contracting, or booking a demo. There is no explicit when-not guidance and no reference to the sibling tools (funciones, integraciones, preguntas_frecuentes) that also answer informational questions. The note that interested parties contact the sales channel directly does help route the post-call behaviour.

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