Pickleball3 Paddle Catalog

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

Annotations already declare readOnly, idempotent, and non-destructive behavior. The description adds valuable context by stating it does not invent missing measurements and only works with 'exact public paddles', disclosing data fidelity expectations beyond the structured annotations.

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 two concise sentences that front-load the core action ('Compare...') and then state limitations. No redundant words or filler; every phrase 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?

For a simple read-only comparison tool with one parameter and no output schema, the description covers scope, limitations, and behavioral guarantees. It could optionally mention what fields are compared, but the current level is sufficient for an agent to select and invoke it 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?

With 0% schema description coverage, the description compensates by explaining 'slugs' as 'two to four exact public paddles', clarifying both the count constraint and the meaning of the parameter values. This adds significant semantic meaning beyond the raw 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?

The description uses the specific verb 'Compare' with a clear resource ('two to four exact public paddles') and explicitly states what it does NOT do (no personalized recommendation, no invented measurements). This distinguishes it from siblings like search_paddles and get_paddle.

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 phrase 'without generating a personalized recommendation' provides clear context for when not to use this tool, implying it is for direct comparisons rather than recommendations. However, it does not explicitly name alternative tools or provide exclusion criteria beyond the recommendation limitation.

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, idempotentHint=true, and destructiveHint=false, so the description does not need to restate safety. It adds value by specifying the record contents and the conditional nature of the sponsored link ('when available'). It does not mention 404 or error behavior, but for a read-only get tool this is a minor gap.

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, dense sentence that front-loads the core action and then lists specifics. Every phrase earns its place, including the caveat 'when available.' There is no fluff 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 tool with one parameter and no output schema, the description explains what will be returned (scores, metrics, citations, link) and includes the conditional link. It would be more complete with a mention of not-found behavior, but overall it covers the essential context well.

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 has a single 'slug' parameter with zero description coverage, and the description does not explicitly explain how to use 'slug'. Saying 'one exact public paddle record' lightly implies slug identifies the record, but the description does not clarify slug format, requiredness, or how it maps to the record. With 0% schema coverage, the description should compensate more than it does.

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 uses a specific verb ('Get') and resource ('one exact public paddle record'), clearly distinguishing it from siblings like search_paddles and compare_paddles. It also enumerates what is returned (scores, metrics, citations, sponsored link), making the tool's purpose unmistakable.

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 phrase 'one exact public paddle record' implies this tool is for exact slug-based lookups, but it does not explicitly state when to use it versus search_paddles or compare_paddles. There is no direct alternative guidance or exclusionary language, so the usage context is only implied.

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 annotations already declaring readOnlyHint=true, idempotentHint=true, and destructiveHint=false, the description adds useful context by specifying 'normalized brand names' and 'current snapshot', which suggests a point-in-time view. However, it doesn't elaborate on response format, pagination, or ordering, so it doesn't go far beyond the annotations.

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, efficient sentence that front-loads the verb 'List' and clearly states the resource. Every word earns its place, with no fluff or redundancy.

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, simple listing tool, the description is nearly complete. It mentions the core output (brand names and review counts) and the context (current snapshot). However, with no output schema, it could briefly note whether the list is sorted or paginated, which is a minor 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?

The input schema has zero parameters, so the description cannot add parameter-level detail. Per the rubric, with 0 parameters the baseline is 4. The description appropriately focuses on output rather than input.

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 uses a specific verb ('List') and clearly identifies the resource ('normalized brand names and public review counts') in the current snapshot. This distinguishes it from sibling tools like get_paddle or search_paddles, which focus on single paddles or searching.

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 provides no explicit guidance on when to use this tool versus the sibling tools (compare_paddles, get_paddle, search_paddles). While the purpose implies it's for getting an overview of brands, it doesn't state exclusions or alternative scenarios, leaving the agent to infer usage.

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, idempotentHint=true, and destructiveHint=false, so the safety profile is known. The description adds valuable behavioral context: 'deterministic bounded filters' and the fact that purchase links appear only for verified sponsored URLs. This goes beyond the annotations.

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 one-sentence description is concise and front-loaded, immediately stating the tool's core function and then adding two pieces of useful behavioral detail. No wasted words.

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 nine optional parameters and no output schema, the description is unduly brief. It doesn't describe return value structure, pagination behavior beyond 'bounded', or any parameter specifics. The annotations cover safety but not functional completeness. It's minimally adequate but leaves important gaps.

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 carries the burden of explaining parameters. It only refers to 'filters' generically, without detailing meanings for sort, year, brand, limit, query, offset, min_score, max_score, or has_purchase_link. The enum for sort is also undocumented. This is a significant gap.

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 a specific verb ('Search') and resource ('current public Pickleball3 paddle catalog'), and mentions 'deterministic bounded filters' which distinguishes it from sibling tools like get_paddle and compare_paddles.

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 establishes clear context for when to use this tool—when searching or filtering the paddle catalog. However, it does not explicitly state when not to use it or mention alternatives, so it falls short of the highest 'explicit when/when-not/alternatives' standard.

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