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

With no annotations, the description carries the full behavioral burden. It discloses the payment cost ($0.12 USDC via x402), which is useful, but it does not clarify whether the tool only transforms the input, returns data, writes files, or has other side effects.

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 description is a single concise, front-loaded sentence with no filler. The payment note is relevant operational context and earns its place, though the brevity comes at the cost of missing usage detail.

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 tool with no output schema, no annotations, and many siblings, the description is minimal. An agent would not know what input format to supply, how the output is returned, or when to prefer this over similar data-handling 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 coverage is 0%, and the only parameter ('input') is described only by its name. The description says 'datos' but does not specify what form the input should take (text, URL, file path, structured object) or how the requested JSON/CSV target is indicated.

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 states a clear verb ('extraer/estructurar') and resource ('datos') with explicit output formats (JSON o CSV). This differentiates it from sibling tools like traduccion, resumen, or clasificar, though it does not name alternatives explicitly.

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?

No guidance is given about when to use this tool versus siblings such as analisis_datos or clasificar. The context of 'extract/structure to JSON/CSV' implies a use case, but no explicit when-to-use, prerequisites, or exclusions are provided.

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