padel.how Racket Reviews

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds only the 'published' qualifier and the count constraint, but does not disclose any additional behavioral traits such as error behavior when slugs are invalid or whether all slugs must exist. With annotations present, the description adds minimal context beyond the obvious, so a baseline of 3 is appropriate.

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 description is a single sentence that fully states the purpose and key constraints. No fluff, front-loaded with the verb and resource. It is appropriately concise for the tool's simplicity.

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 has a single parameter, an output schema exists, and annotations cover the safety aspects. The description provides the essential operational details (compare, slug count, distinctness). It lacks explicit linkage to sibling tools for obtaining slugs, but given the low complexity and available structured data, it is reasonably complete. Could improve by mentioning that slugs come from search/get tools, but not strictly necessary.

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 0%, so the description must compensate. It explains that 'slugs' refers to racket slugs, must be distinct, and the count should be 2-4. This adds meaningful semantics beyond the bare array type. However, it does not clarify the format of slugs or how to obtain them, which would be additional but not critical for this simple tool.

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 clearly states the action (compare) and the resource (rackets) via slugs, specifying the count range (2-4) and the distinctness condition. This distinguishes it from siblings like get_racket (single racket) and search_rackets (search rather than comparison).

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 purpose is obvious enough that usage context is clear, but the description does not explicitly mention alternatives or when not to use it. It implies the agent should already have valid slugs (e.g., from search_rackets), but does not explicitly state that or name sibling tools. Lacks explicit guidance but is not misleading.

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 read-only, idempotent, and non-destructive behavior. The description adds 'published' and 'validated' context, but no further side-effect or error details are provided.

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?

One concise, clear sentence with no unnecessary words or repetition.

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 get-by-slug operation, the description fully conveys what is returned (a published racket) and the input requirement, making it complete for its purpose.

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 only parameter 'slug' is described as a validated catalogue slug, providing meaningful context that the schema lacks. This compensates for the absent schema description.

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 clearly states it retrieves a single published racket by its slug, distinguishing it from sibling tools like search, compare, and list.

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?

It implies usage when you have a validated slug and need one racket, but does not explicitly contrast with search or list for broader queries.

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 indicate read-only, idempotent, non-destructive behavior. The description adds the key behavioral detail that results are grouped by case-insensitive normalized spelling, which is not expressed in the annotations and helps the agent understand the output structure.

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 description is a single, concise sentence that front-loads the core purpose and avoids redundant filler. It earns its place by adding the grouping criterion.

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?

Given the tool's simplicity (no parameters, read-only, output schema present), the description is sufficient: it names the resource and the grouping behavior. The output schema covers return structure, so no further explanation is needed.

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 input schema is empty, so there are no parameter semantics to clarify. With zero parameters, the description does not need to elaborate on parameter meaning; baseline score of 4 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?

The description clearly states the action (list), the resource (brand variants), and the specific grouping criterion (case-insensitive normalized spelling). This distinguishes it from sibling tools get_racket, search_rackets, and compare_rackets, which handle different operations.

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 obtaining brand variants but provides no explicit guidance on when to choose this tool over search_rackets or get_racket. No alternatives are mentioned, so the agent must infer the tool's role from its name and description.

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 the tool as read-only and idempotent, covering the safety profile. The description adds that filters are literal and case-insensitive, which is useful behavioral context beyond the schema. However, it does not mention any other behaviors (e.g., pagination, sorting, empty results) that might matter, but given the strong annotations, this is acceptable but not outstanding.

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 description is a single, front-loaded sentence with no redundant wording. It is concise and to the point, earning high marks for efficiency.

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 10 parameters, an output schema, and no parameter descriptions, the description is far from complete. It does not clarify how filters combine, what 'literal' means for range fields, or how sorting and pagination interact. Even though the output schema exists, the description's lack of parameter guidance leaves significant gaps for a tool of this complexity.

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 0%, yet there are 10 parameters. The description provides only a general statement about filters being literal and case-insensitive, which applies to text parameters but does not explain individual parameters like year, score ranges, or audience. It fails to compensate for the lack of schema descriptions, leaving the agent to guess parameter semantics.

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 clearly states the tool's purpose: 'Search published rackets' with a specific qualifier 'using literal, case-insensitive catalogue filters.' It conveys the action (search) and resource (rackets), and the filter semantics distinguish it from sibling tools like get_racket (retrieve single) or list_racket_brands (list brands).

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 that this tool is for searching rackets via filters, but it does not explicitly contrast with sibling tools or provide when-to-use/when-not-to-use guidance. The phrase 'catalogue filters' hints at usage context, but no alternatives are named, so it relies on the reader to infer that it's the search tool among siblings.

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