Visitas y conversión por publicación

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds the 30-day time window and diagnostic intent, but gives no further behavioral detail such as how results are aggregated or returned.

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 focused sentences with no filler. The first defines the computation, the second states actionable value, making it easy to scan.

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 does not describe the return shape or how 'limite' affects results. It is adequate for a simple read-only analytics tool, but leaves invocation details partly to inference.

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 only 50%; 'cuenta' is documented, but 'limite' has no schema description and the tool description does not explain it. The description's 'últimos 30 días' refers to the analysis window, not the 'limite' parameter, so it adds no parameter-level meaning.

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 analytic action: crossing visits against sales for the last 30 days and calculating conversion rate per publication. This clearly distinguishes it from sibling tools like ml_visitas or ml_metricas by including sales and conversion, not just traffic.

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 use case is implied by 'Detecta las que reciben tráfico pero no venden' — an agent can infer when to use it. However, no explicit when-to-use/when-not-to-use guidance or named alternatives is provided.

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