GolfData

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

With no annotations, the description carries the burden of behavioral disclosure. It explains what the response contains, the provenance attributes on enriched fields, and the meaning of enrichment_status values, which is substantial context beyond the raw schema.

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?

Three focused sentences convey the core behavior, provenance model, and enrichment-status semantics without wasted words. The most important message, what the tool returns, is front-loaded.

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 single-parameter retrieval tool with no output schema, the description covers the key behavioral details: return scope, provenance fields, and status interpretation. Minor gaps like missing-product behavior are not critical given the low 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?

The schema already fully describes product_id as a canonical product UUID from search_products, and the description adds no parameter-specific detail. With 100% schema description coverage, the baseline of 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?

The description states a clear verb and resource: retrieving one product plus its enrichment provenance rows. It implies differentiation from siblings like search_products by emphasizing a single product and provenance detail, though it does not explicitly name 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 description gives valuable guidance about checking enrichment_status before trusting specs, which informs how to interpret results. However, it does not explicitly state when to choose this tool versus siblings like get_current_prices or get_verified_offers.

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 no annotations, the description carries the full burden. It discloses that the search matches free text against product names, and lists categories, but it doesn't detail behavior like case sensitivity for categories, whether the search is fuzzy or exact, or the return format. The basic behavior is clear, but richer details are missing.

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 concise, with the core purpose front-loaded. The category list is a necessary addition for this domain-specific tool. Every sentence serves a purpose: the first defines the tool's function, the second gives usage guidance, and the third lists valid values. No waste.

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 role as a search entry point with an output schema absentjon, the description doesn't explain the return format or selection logic, which could be important. However, the purpose and basic parameters are covered, and the sibling tools suggest how results are used. It's adequate but not thorough.

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 all parameters are documented in the schema. The description adds the list of categories, which is also in the schema, and the 'free text matched against the product name' with the 'call this first' context. This adds minimal value beyond the schema, so 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?

The description clearly states the tool's purpose: to search the golf equipment catalog by brand, category, or free text, and to resolve product IDs for other tools. This is specific about the resource (golf equipment catalog) and the action (search), and it distinguishes itself from siblings like get_product by its search role.

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?

Explicitly instructs to call this tool first to resolve product_id for other tools, providing clear when-to-use guidance. It doesn't explicitly mention when not to use it or alternatives, but the context of 'first step' implies it's the entry point, and sibling tools are for specific follow-ups, which is clear enough.

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