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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive), but the description adds genuinely new context: it is a curated Subastech knowledge base sourced from BOE, requires no account, is not legal advice, and notably is 'sin modelo de lenguaje' (not an LLM). That last point meaningfully sets expectations about output style.

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 tight sentences, front-loaded with the core action and scope, then the sourcing/constraint caveats. No filler.

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 an output schema present and 100% parameter coverage, the description need not explain return values. It supplies the sourcing, access, and non-advisory context an agent needs. It could be slightly stronger by clarifying scope boundaries versus the sibling analysis/search tools.

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 description coverage is 100% with a single required 'pregunta' parameter already documented with an example. The description's concept list marginally clarifies what kinds of inputs are expected but adds no syntax or constraint detail beyond the schema; baseline 3 is appropriate.

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?

Specific verb+resource: 'Explica un concepto de las subastas judiciales en España', with concrete example domains (depósito, cargas, posesión, cesión de remate, tipos de subasta). It clearly reads as a conceptual/knowledge-base tool, distinguishing it from sibling data tools like buscar_subastas, analisis_subasta, or subasta.

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?

The framing ('Base de conocimiento... textos generales, no asesoramiento') implies when to use it, but no alternative is named and no explicit when/when-not routing is given. Usage is inferable rather than stated.

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