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get_launch

Un lanzamiento con sus etapas y las MÉTRICAS REALES de cada una (enviados, entregados, abrieron, clics únicos, bajas, ingresos USD atribuidos por clic o apertura, sin las ventas solo «influidas») más el total; cada campaña se suma una sola vez. stages_sent de stages_total = etapas ya enviadas. metrics null en una etapa = todavía no tiene correo (no es 0). Es la forma de saber cómo va un lanzamiento. Definiciones: enviados = correos con sent_at; entregados = enviados − rebotados; abrieron = correos con apertura (píxel, webhook o clic); clics únicos = correos con clic en un enlace de contenido (baja, preferencias y pie aparte en clicked_system). Tasas en % con 2 decimales: entrega y rebote sobre ENVIADOS; apertura, clic, bajas y quejas sobre ENTREGADOS (rate_base "delivered"); ctor = clics únicos / abrieron. null = sin denominador, nunca 0 inventado. *_fraction son alias heredados en fracción 0-1 (deprecados).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
launch_idYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

B3.4/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does substantial work: it defines the dedup rule ('cada campaña se suma una sola vez'), explains stages_sent vs stages_total, clarifies that metrics null means no email yet rather than 0, and specifies the denominators for each rate. It stops short of stating auth or rate-limit behavior, hence not a 5.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The purpose is front-loaded and the metric definitions are genuinely needed given the absence of an output schema. However the content is delivered as a single dense run-on paragraph mixing purpose, formula definitions, null semantics, and deprecation notes, which hurts scannability.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema and no annotations, the description does the heavy lifting by documenting return semantics, rate bases, and null handling thoroughly. The remaining gap is the input parameter, which is left entirely unspecified.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% and the single parameter launch_id has no description. The tool text is entirely about output metrics and never clarifies what launch_id is, its source, or its format. It fails to compensate for the coverage gap, though the parameter name is largely self-evident.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb+resource: retrieves a launch with its stages and 'MÉTRICAS REALES'. The line 'Es la forma de saber cómo va un lanzamiento' makes the intent unambiguous. It does not, however, differentiate itself explicitly from siblings like list_launches or get_campaign_stats.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

'Es la forma de saber cómo va un lanzamiento' implies the use case (assessing launch health), which gives implied usage. But there is no explicit when-to-use/when-not guidance and no reference to alternatives such as get_campaign_stats or list_launches, so an agent must infer routing.

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

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