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

Annotations already cover read-only, idempotent, open-world, and non-destructive behavior. The description adds that the output is clean, consistent JSON and discloses a per-call cost via x402, which is useful operational context beyond the structured annotations.

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, well-structured sentence that front-loads the action, explains the purpose, and adds the pricing detail without fluff. Every part earns its place.

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 conversion tool with full schema coverage and strong safety annotations, the description provides sufficient context: input type, output format, use case, and cost. No output schema exists, but the promised JSON output is enough for correct invocation.

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 single `csv` parameter is fully described in the schema ('CSV con cabecera (máx. 1 MB)'). The description adds that the CSV should come from CI jobs and that the result will be JSON, enriching the parameter's meaning without redundancy.

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 specific verb and resource: it converts CI job CSV exports into normalized JSON for detecting slow builds, cache failures, and repeated steps. This clearly differentiates it from siblings like normalizar-requisitos-csv, which target a different CSV domain.

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 description gives a clear use context: use it when you have CI job CSV exports and want consistent JSON for build-performance analysis. It does not explicitly name alternatives or exclusions, but the intended scenario is obvious enough.

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