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

With no annotations, the description carries the full burden. It usefully discloses the paid model ('x402: 0.02 USDC on Base, pay-per-use'), which is real behavioral context an agent needs before invoking. However, it omits failure behavior, size/type constraints on the CSV, and what happens for columns without numeric data.

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 tight components: purpose, input grammar, and pricing. Zero filler, and the primary purpose is front-loaded before the format 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 one-parameter tool the coverage is close to adequate, but with no output schema the description should say what is returned (outlier values, indices, a flag, or a modified CSV). The payment note is present but return shape is left entirely unspecified.

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 nominally 100% but the schema description is only 'service input', adding no meaning. The description compensates by defining the actual payload grammar: '<url_o_csv>||<columna>', including the pipe delimiter and the order of URL then column name. This is genuine value beyond the schema.

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 algorithm ('Detecta outliers (IQR)') applied to a precise resource ('una columna de un CSV'). The IQR qualifier distinguishes it from generic stats tools like estadisticas-descriptivas or limpiar-csv, though no sibling is named to make the routing explicit.

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 when-to-use, when-not-to-use, or alternative routing is given. The only guidance is the input string format, which is a parameter concern rather than usage guidance. An agent gets no signal about prerequisites (valid CSV, column existence) or alternatives.

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