SoleScout

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description usefully discloses the return shape (one winner per size), which matters since there is no output schema, but says nothing about missing sizes, partial data, or how the optional size parameter alters 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?

Two tight sentences with the core behavior front-loaded and the caveat second. No filler, though it could more directly anchor the optional size parameter.

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 per-size-winner statement carries important return-value context, and annotations cover safety. Still missing is how the optional size argument interacts with the 'EACH size' behavior—an agent cannot tell whether it returns all sizes or just the filtered one.

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 both parameters are already documented, and the description adds only the concept that results are per-size. It does not clarify what happens when the optional 'size' filter is supplied versus omitted, which is the one ambiguity the schema cannot resolve.

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 and operation: the cheapest retailer per size for one product. The second sentence sharpens the distinction from a product-level lowest-price query, though no sibling tool (e.g. where_to_buy) is named for contrast.

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 a usage condition by warning that a product-level 'lowest price' is usually wrong for a specific buyer, which implies when to prefer this tool. However, it never names an alternative among the siblings (where_to_buy, search_sneakers) or states explicit exclusions, leaving 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?

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds that results carry product counts, which is useful, but says nothing about pagination, ordering, or size of the 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?

Two terse sentences, with the core purpose front-loaded and the usage hint second. No filler.

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 zero-parameter, read-only listing tool with no output schema, the description covers purpose and the intended workflow. It could add a note on typical result size or that it returns all brands unfiltered, but nothing essential 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?

The tool takes no parameters, so the baseline of 4 applies. There is nothing parameter-related the description could usefully add.

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 first sentence states a concrete verb+resource: it lists brands from the catalogue and includes their product counts. It is distinguishable from search_sneakers and where_to_buy, though it does not explicitly name siblings to differentiate against.

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?

'Ground a brand name before searching' gives clear workflow context, effectively telling the agent to call this prior to a search. It does not state exclusions or name which sibling search it feeds, 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.

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

Annotations already cover the read-only, closed-world safety profile, so the bar is lower. The description adds real behavioral value by stating the response contains a 'live lowest price' and a count of tracked retailers per product, which tells the agent about data freshness and result shape.

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 tight sentences, front-loaded with what is searched and immediately followed by what is returned. Every clause earns its place with no filler.

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 fills the gap by describing the return payload (lowest price, retailer count). Combined with full schema coverage for inputs, the agent has what it needs, though sorting behavior and the brand/limit interaction are left implicit.

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 baseline is 3, but the description goes further by giving concrete query examples ('samba og', 'HQ9438') that illustrate the accepted input formats for the required parameter. The brand and limit parameters get no additional narrative, keeping it from a 5.

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 verb ('Search') and resource ('the catalogue') and enumerates the queryable fields (model name, colorway, style code). It also previews the return payload, which implicitly separates it from siblings like cheapest_for_size and where_to_buy, though it never names an alternative explicitly.

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?

There is no when-to-use or when-not-to-use guidance and no mention of the sibling tools that handle size-specific pricing or retailer lookup. The examples clarify query format but not when this tool is the right choice over its 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 readOnlyHint=true and openWorldHint=false, so safety is covered. The description adds real context beyond that: the returned data shape (price, in-stock sizes, direct links) and the coverage trait ('long-tail coverage a feed-based catalogue does not have'), which signals it may return retailers a feed wouldn't. No pagination or rate-limit detail, but the added behavioral value is genuine.

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 sentences, front-loaded with the substantive content (retailers, price, sizes, link) and no filler. The trailing coverage claim is slightly promotional but still carries differentiating information, so it earns its place.

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 does the job of describing return contents, and it does so adequately. Annotations cover the read-only profile. The only real gap is the absence of any routing guidance versus cheapest_for_size, which affects the completeness of the overall definition.

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% and the schema itself already explains the one parameter ('product slug from search_sneakers'), including the sibling cross-reference. The description adds no syntax, format, or validation detail beyond that. Baseline 3 is appropriate when the schema carries the parameter burden.

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 names a specific resource (tracked retailers carrying a given product) and enumerates what comes back: price, in-stock sizes, and a direct product-page link. That is concrete enough to tell it apart from list_brands and search_sneakers on its face. It stops short of explicitly contrasting with the closest sibling, cheapest_for_size, which also surfaces prices.

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?

There is no statement of when to reach for this tool over its alternatives. Nothing tells the agent to call it after search_sneakers to resolve a slug, nor when cheapest_for_size would be preferable over this broader price listing. Usage is only inferable from the return summary.

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