Serie mensual del historico de precios de un juego. Va SIN tasas de pago y sin cupones (tarifa de tienda) y mezcla formatos: dilo al citarla y no la compares con precio_con_tasas. Usalo cuando pregunten si ha estado mas barato o como ha evolucionado el precio.
| Name | Required | Description | Default |
|---|---|---|---|
| game | Yes | id numerico o slug | |
| lang | No | Idioma del usuario para los enlaces: es, en, de, fr, it o pt. Por defecto en | |
| months | No | Meses hacia atras, 1-60 |
Changes observed during successful MCP inspections.
Input schema / properties / langAdded value: +{
+ "description": "Idioma del usuario para los enlaces: es, en, de, fr, it o pt. Por defecto en",
+ "type": "string"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden, and it does disclose meaningful dataset traits: values exclude payment fees and coupons, and the series mixes formats, with an instruction to disclose that when citing. It still omits response shape, currency, and pagination behavior.
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 sentences that front-load what the series is before the caveats. The citation instruction ('dilo al citarla') is slightly meta but still earns its place as a usage constraint.
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 and no annotations, the description covers the important semantic caveats (fee/coupon exclusion, mixed formats, non-comparability) needed to avoid misreporting. It leaves the actual return payload shape unstated, which is the main remaining gap.
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 100%, so game, lang, and months are already fully documented in the schema. The description adds no per-parameter meaning beyond what is structured, which is the baseline 3 case.
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 concrete verb+resource: a monthly series of a game's price history, which an agent can distinguish from list-oriented siblings like get_deals. It does not explicitly differentiate itself from get_best_price, so the agent must infer the split between 'current best price' and 'historical series'.
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?
Gives an explicit trigger ('Usalo cuando pregunten si ha estado mas barato o como ha evolucionado el precio') and a do-not rule (do not compare it with precio_con_tasas). It stops short of naming a sibling alternative for the 'current price' case, but the when-to-use condition is clear.
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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