offers

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

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so the safety profile is covered. The description adds genuinely useful context that results are brand-specific because the brand's own chart is used, but says nothing about failure behavior for unknown brands/sizes or what the returned value looks like.

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?

A single front-loaded sentence with no filler; every clause (single size, brand-specific, three systems) carries information the agent needs.

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?

The tool is simple and read-only, and the description covers the input semantics adequately. However, with no output schema, the description should indicate what is returned (e.g. a size string in the target system, or an error when the brand has no matching chart) and it does not.

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?

With 50% schema coverage, the two undocumented params (from_system, to_system) are enums whose meaning is made explicit by the description naming the EU, US and UK systems. It also clarifies that only one size value is converted and that brand selects the chart, adding meaning beyond the schema's example values.

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 and resource — converting a single shoe size between EU/US/UK using a brand's own chart. It is unambiguous and clearly distinct from siblings like search_sneakers or get_offers, though it doesn't explicitly name those alternatives.

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 context of use is implied by the verb 'converts' and the size-system scope, so an agent can infer when to reach for it. There is no explicit statement of when not to use it, no prerequisites (e.g. unknown brand handling), and no reference to alternatives.

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?

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so the safety profile is covered. The description adds the meaningful scope constraints of freshness ('today's') and limited source coverage ('shops HYPEIBIZA compares'), but says nothing about order, pagination or how the limit is applied.

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?

A single front-loaded sentence with the behavior first and the optional filters trailing, with no wasted clauses. Slightly more could be said about scope without bloat.

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 simple, annotation-heavy read tool with no output schema, the description covers purpose and filtering adequately. It is still unclear what a 'deal' record contains and whether limit caps total results or results per brand/model, which matters for interpreting the call.

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 67%: brand and model are documented in the schema and limit is self-evident from its default/min/max bounds. The description only reinforces that the filters are optional and mutually combinable; it adds no format or matching semantics beyond what the schema already states.

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 and resource ('Lists today's price drops') plus the data source scope ('shops HYPEIBIZA compares'), which is more than a restatement of the name. It does not, however, distinguish itself from siblings like get_offers or search_sneakers, so an agent must infer the boundary.

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?

'Optionally for one brand or model' implies the filtering use case, and 'today's' implies a recency window. But there is no explicit guidance on when to pick this over get_offers or search_sneakers, nor any exclusions or prerequisites.

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?

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so the safety profile is covered. The description adds value beyond that by disclosing the returned fields per shop and the behavioral effect of the size parameter (adds in/low/out status). It stops short of covering ordering, currency normalization or completeness of the shop list.

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?

A single dense sentence with zero filler, and the core action plus output contents are front-loaded before the optional size qualifier. Slightly over-packed but every clause carries information.

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 enumerating the returned per-shop fields, and it explains the size parameter's effect on the result. For a two-parameter read tool with full annotations, nothing an agent needs to invoke it correctly is missing.

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 both parameters are already documented in structured form, including the slug pattern and its source tools. The description's "optionally for one size" restates the optionality without adding format or semantics beyond the schema's in/low/out explanation.

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?

"Lists the shops that sell one product" gives a specific verb and resource, and the sentence enumerates exactly what each entry contains (price, strike price, stock, link). It does not name or contrast with any sibling, so an agent must infer that this is the product-level detail view versus search_sneakers/get_deals.

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?

Usage is only implied: "optionally for one size" signals when to pass the size parameter, and the slug's origin is documented (though in the schema, not the description). There is no statement of when to call this instead of search_sneakers or get_deals, and no prerequisites or exclusions.

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?

Annotations already declare readOnly, idempotent, and non-destructive behavior, so the description's added value is in the return semantics: a cap of 10 results ranked by lowest shop price. That ranking/limit detail is genuine behavioral context beyond the annotations, though it omits pagination or empty-result 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?

A single front-loaded sentence that packs the resource, match fields, result cap, and pricing rule with no filler. Slightly long but every clause carries information.

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 compensates by stating the return shape (up to 10 products) and ranking criterion (lowest shop price). Only minor gaps remain, such as how few-result or no-result cases behave.

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 67% and the query parameter is already well documented with examples in the schema; the description restates the same matching fields. The size-driven pricing nuance and the limit cap are only partly reflected, so with the schema doing most of the work a baseline 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 (searches) and resource (HYPEIBIZA catalogue for sneakers and streetwear) plus the fields matched (name, model, style code). It is clearly distinct from convert_size and get_deals, though it does not explicitly distinguish itself from the overlapping get_offers sibling.

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 implies usage for product lookup by name/model/style code, but never states when to prefer this over get_offers or get_deals, nor any exclusions or prerequisites. The agent must infer the boundary from the sibling names alone.

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