MYOPL Pickleball

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 agent knows this is a safe read operation. The description adds the constraint that it only returns public data (published OPL ratings) and excludes private fields, which is useful context beyond the annotations. However, the description does not disclose behavior like error handling for non-existent usernames or rate limits. With annotations covering the safety profile, a 3 is fair.

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, tight sentence that front-loads the core purpose ('Look up an exact public username and published OPL ratings') and then lists exclusions. Every word earns its place, with no fluff. This is an excellently concise and well-structured description.

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 with only one parameter, and the annotations provide the safety profile (read-only, idempotent). The description covers the scope and exclusions, and there is no output schema needed to explain return values (the description says it returns OPL ratings). For a lookup tool of this complexity, nothing essential is missing, making it complete.

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. The description specifies that 'username' must be an exact public username, and that it is used to look up published OPL ratings. This adds meaning beyond the schema's pattern (which just says string of letters/numbers/.-_ up to 64 chars). It clarifies the semantics of the parameter, justifying a 4.

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 verb (look up), the resource (public player rating), and the exact scope (exact public username, published OPL ratings). It also explicitly lists what is not included (email, telephone, location, match history, private fields), which distinguishes it from potential sibling tools like search_myopl_help or search_myopl_website. This is a specific and unambiguous definition.

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 when to use this tool: when you need public OPL ratings for an exact username. It does not explicitly name alternative tools or provide when-not-to-use guidance, but given the sibling list (search tools, browse tools), the restriction to 'exact public username' and 'published OPL ratings' gives clear context. A 4 is appropriate because it is clear but lacks explicit 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 indicate read-only, idempotent, non-destructive behavior, and the description adds useful context beyond them: it returns a spoken reply and structured choices, and it does not perform live availability checks or booking. No contradiction with 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?

Two tight sentences front-load the core purpose and then add the output format and boundary. Every clause adds value, with no filler or repetition of schema details.

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 browse-style tool with safety annotations and only one required parameter, the description covers purpose, output nature, and key limitations. It does not explain the exact structured-choice format or language parameter, but nothing critical is missing for an agent to 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 well by mapping 'courts to play at, clubs to join, open play sessions' to the category enum and 'city, state or country' to the location parameter. The language parameter is not described, but its enum values and default make its meaning reasonably inferable.

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?

Description states a specific action ('Offer') and concrete resources ('courts', 'clubs', 'open play sessions') for a location, and it differentiates itself by noting it does not search live availability or join/book. This makes the tool's role clear next to search_myopl_* siblings.

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 clearly frames when to use the tool: to offer courts/clubs/sessions for a named city, state, or country. It also gives explicit exclusions ('does not search live availability or join/book anything'), though it does not name specific sibling alternatives to route to.

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 establish the tool as read-only, idempotent, and non-destructive, so the description only needs to add extra context. It does so by noting that results are published Help Center instructions with source URLs and that account or conversation data is out of scope, going beyond the annotation fields.

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 concise sentences with no filler. The core purpose and scope are front-loaded, and the exclusion of account/conversation access is a useful, non-redundant addition.

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 two-parameter read-only search tool, the description covers the essential points: what is searched, what is returned, and what is excluded. There is no output schema, but the description's mention of source URLs is enough to set expectations. Minor gaps like return ordering or language behavior are not critical here.

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 for both parameters. It implies that 'query' is a search phrase but never explicitly describes how it is matched, and it gives no guidance about the 'language' parameter beyond what the enum already makes obvious. The description does not bridge the schema coverage 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 uses a specific verb ('Find') and a precise resource ('published MYOPL Help Center instructions'), and adds what is returned ('with source URLs'). This clearly distinguishes it from the sibling tools like search_myopl_website, which likely target the main website instead of the Help Center.

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 gives clear context for when this tool is appropriate: searching published Help Center instructions. It also states an exclusion ('No account or conversation access'), which helps an agent avoid using it for private data. It does not explicitly name sibling alternatives, but the scope is clear enough to route correctly.

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 readOnly/openWorld/idempotent/destructive states, so the bar for extra value is lower. The description adds meaningful context beyond annotations: it clarifies the data scope (public published info, no account or conversation access) and indicates the response includes source URLs. No contradiction with 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?

A single, front-loaded sentence with no filler. The core purpose comes first, and the access limitation is added in a short second clause. Every word contributes.

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 only two simple parameters and strong annotations, the description is largely complete: it identifies the search scope, notes source URLs in results, and excludes private data access. It could still mention return shape or pagination, but these are minor omissions given the schema and annotations.

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 needed to compensate by explaining the query and language parameters. It does not mention either parameter, their constraints, or how language affects results. The schema is simple, but the description adds no parameter-specific meaning.

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 ('Find') and resource ('published MYOPL product and website information'), and adds a concrete output detail ('with source URLs'). It also distinguishes itself from sibling tools like search_myopl_help and search_pickleball_rules by focusing on product/website information rather than help content or rules.

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 context through the phrase 'published MYOPL product and website information' and explicitly excludes account or conversation access. However, it does not explicitly state when to prefer this tool over siblings or mention alternatives, leaving some inference to the agent.

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 establish readOnly, openWorld, idempotent, and non-destructive behavior. The description adds useful behavioral context beyond those hints: the tool returns evidence and citations, produces a grounded answer only when the private resolver is enabled, and warns that excerpts alone are not a complete ruling. These are genuine, non-redundant disclosures.

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 compact and front-loaded with the core purpose. Each sentence contributes meaning: purpose, return behavior, caveat, and a clarifying non-feature. The final 'No package download' sentence is slightly tangential but short and relevant to setting expectations. No filler 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 simple search tool with no output schema, the description covers the key operational facts: resource scope, return content, conditional grounded-answer behavior, and an important epistemic caveat. It does not fully compensate for the low schema coverage on parameters, but the schema's named parameters and enum are largely self-explanatory and annotations cover the safety profile. The definition is adequate and near-complete.

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 needed to explain the query and language parameters, but it does not mention either by name or give usage guidance. The word 'Search' loosely implies query is the search text, and the schema's enum/default covers language, but the description itself adds no parameter-level meaning. The language parameter also remains underserved, especially given the mention of 'English evidence.'

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 opens with a specific verb and resource: 'Search the validated USA Pickleball rulebook.' It also states what the tool returns (evidence, citations, grounded answer), which distinguishes it from the sibling MYOPL search tools and player-rating tool. The purpose is immediately clear and not interchangeable with any 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 gives implied context: use it to search the USA Pickleball rulebook. It also offers practical guidance about preserving clarification requests and not treating excerpts as complete rulings. However, it never explicitly contrasts with alternatives like search_myopl_help or search_myopl_website, so an agent must infer the boundary between those tools.

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