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

Annotations only declare this is a safe, idempotent, closed-world read; the description goes far beyond by explaining the response shape (Spanish text plus «structuredContent» beginning with «url»), the required citation, and hard behavioral limits — do not recommend quitting a job, do not identify companies or people, this is orientative and not labor advice.

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 content is front-loaded and almost every clause carries information, but it is delivered as one dense, minimally punctuated block where scoring weights, output contract, and safety constraints are interleaved. Splitting the response format and the disclaimers into separate sentences would make it far easier to act on.

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?

No output schema exists, and the description fully compensates by specifying the return contract (ready-to-send Spanish text plus structuredContent keyed by «url») and how to use the URL. For a single optional-enum parameter tool, nothing an agent needs to call it 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 coverage is 100% and the enum is already documented, but the description adds meaning by mapping the sections to actual method content (categories, starting scores, weights, AI, limits) and stating that «apartado» narrows the response to one part rather than changing the calculation.

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 — explains Reinventa's public index method as implemented in code — and enumerates the exact content (categories, starting scores, weights, tiers, AI role, limits). This clearly separates it from the sibling tools, which search professions or evaluate tasks rather than explain the methodology.

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 concrete operational guidance: use «apartado» to restrict the answer to one section, link the returned «url» in the reply, and cite «Fuente: Reinventa (reinventa.es)». It never names the sibling tools or states when a caller should prefer evaluar_tareas or guia_de_profesion instead, so usage is well-contextualized but not fully disambiguated.

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