GoCDKeys

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

No annotations exist, so the description carries full burden and does substantial work: it enumerates returned fields (precio_base, tasas, precio_con_tasas, summary), explains the tax semantics ('sin tasas de pago', 0 = no cobra), coupon handling, and that summary embeds price+store as a link. It stops short on error behavior, permissions, or freshness guarantees, but discloses unusually rich return 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?

Purpose is front-loaded, but the body is bloated with prescriptive output-formatting rules (how to quote prices, where to place links, when to say 'sin tasas') that inflate length relative to the core selection signal. Several of these sentences are essentially templates rather than tool definition.

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?

With no output schema, the description usefully describes the return payload (the three price fields, coupon, and summary). Coverage is strong for a read tool, though it omits what happens for unknown/invalid game ids or empty results.

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 100% for both parameters, so the schema already documents 'game' and 'lang'. The description adds no format or syntax detail for either parameter (e.g. what a valid slug looks like), so the baseline of 3 is appropriate.

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+resource clearly: it returns a game's best price along with format (key/cuenta/gift), store, purchase link and timing context. An agent can tell it fetches pricing, but the description never contrasts it with siblings like get_deals or get_price_history, so the boundary is left to inference.

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?

Explicit trigger is given: 'Usalo cuando pregunten donde comprar, cuanto cuesta o si conviene esperar.' That is a clear when-to-use statement. It offers no when-not-use or named alternative, so it stops short of full routing guidance.

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

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

With no annotations, the description carries the full burden. It usefully clarifies fee semantics (precio_base excludes payment fees; all-time low and average are fee-free) and prescribes an output citation format, going beyond the schema. It does not address permissions, rate limits, or pagination, which is a gap for an unannotated read tool.

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 definition is compact and front-loads the resource before the operational detail. The instruction about how to cite two prices is slightly digressive but still earns its place as behavior guidance.

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?

With no output schema, the description compensates by naming the returned fields and their fee semantics, so an agent knows what to expect. A touch more on defaults/limits (e.g., default limit) would make it fully self-sufficient.

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 100%, so the schema already documents lang, type, limit, and platform, making 3 the baseline. The description implicitly echoes the type parameter (all-time low / below usual) but adds no syntax or enum guidance 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 resource (games currently at all-time low or below their usual price) and the exact fields returned (store, precio_base, precio_con_tasas), distinguishing it from siblings like get_price_history and get_best_price. An agent can tell what this returns without opening any schema.

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?

"Usalo cuando pregunten que ofertas hay hoy" gives an explicit trigger condition for the tool. However, it does not name or exclude alternatives (e.g., get_best_price for a single game), so the boundary with siblings is left to inference.

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

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.

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

No annotations exist, so the description carries full behavioral burden. It does disclose the return shape and a required output convention ('cita los dos juntos, «X EUR (Y EUR con tasas)»'), which is genuinely useful. It says nothing about default window/limit behavior, result ordering, or read-only/no-side-effect status, leaving real gaps for a no-annotation tool.

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?

Purpose and return fields are front-loaded, and the second sentence cleanly covers usage. The format instruction is dense but earns its place; overall it is appropriately sized for a definition that must carry annotation-level context itself.

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?

With three optional params, no output schema, and no annotations, the description supplies what an agent most needs: the resource scope, the returned fields, a quoting convention, and a trigger condition. Missing only edge behavior such as default window, result caps, and any permission context.

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% — days, lang, and limit are each documented in the schema with valid ranges and defaults. The description adds no syntax or meaning beyond that, so the baseline of 3 applies.

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 resource ('juegos que aun no han salido') plus exactly what is returned (fecha de lanzamiento, precio_base, precio_con_tasas) and even the output quoting format. The 'not yet released' scope cleanly separates it from siblings like get_deals or get_best_price, which cover available/priced items.

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?

Explicitly says when to use it: 'cuando pregunten cuando sale un juego o que se puede reservar', which maps directly to release-date and preorder questions. It stops short of naming alternatives or when-not-to-use conditions (e.g., vs. get_deals), leaving that routing to inference.

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

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

No annotations are provided, so the description carries the full behavioral burden. It discloses the returned fields and a price-formatting convention, but says nothing about matching behavior (e.g. multiple/fuzzy results), pricing source, or any auth/rate constraints; for a read-style search tool this is acceptable but not rich.

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?

Front-loads what the tool does, then the return shape, then the usage trigger, with no filler sentences. The price-formatting directive is dense and slightly verbose, keeping it from a perfect score.

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?

With no output schema, the description correctly summarizes the return shape (id, platforms, ficha) and even specifies how to render base vs. with-fees prices. Combined with the usage trigger, an agent has everything needed to call and report this tool correctly.

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 q, lang and platform are already documented in the schema. The description adds no additional parameter meaning beyond the schema (the price-format text concerns output, not inputs), which matches the baseline 3 for high-coverage schemas.

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 (Busca) plus resource (un juego por nombre) and defines the return payload (id, plataformas, ficha). Crucially it positions itself relative to siblings as the resolver step performed before asking for prices, so an agent can distinguish it from get_best_price/get_deals without opening any schema.

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?

Explicitly says to use it 'cuando el usuario mencione un juego y necesites resolverlo antes de pedir precios', which gives a clear trigger and an implied ordering relative to get_best_price. It does not name an alternative to avoid, so it stops short of full when/when-not guidance.

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