search_equipmentSearch current golf balls, drivers, putters, rangefinders, and launch monitors. Returns official Stymie detail URLs, images, MSRP, and stated best-for guidance when published.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| query | Yes | Brand and/or model name | |
| category | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds useful behavioral context by specifying return fields (official URLs, images, MSRP, best-for guidance) and noting that best-for guidance is only included 'when published,' indicating conditional availability.
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, focused sentence that front-loads the tool's purpose and return details. Every phrase earns its place without redundant fluff.
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 search tool with three parameters, the description is mostly complete: it covers scope and expected output. It doesn't address edge cases like result limits or empty search behavior, but given the simplicity and annotation coverage, the description suffices.
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 describes only the query parameter (33% coverage). The description compensates somewhat by listing the five equipment categories in natural language, aligning with the category enum. However, the limit parameter's semantics and any search behavior nuances are not explained in the description, leaving some gaps.
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 searches equipment (golf balls, drivers, putters, rangefinders, launch monitors) and returns specific result fields (URLs, images, MSRP, best-for). This distinguishes it from sibling tools like search_courses and search_tee_times.
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 equipment searches but provides no explicit guidance on when to prefer this tool over search_stymie or other sibling search tools. It doesn't mention exclusions or alternative tools, so usage is implied rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
find_nearby_courses and search_courses overlap significantly, both returning courses near a location with mileage, and search_stymie adds another ambiguous entry point. However, each tool has a distinct specialization (exact distance vs. general search, cross-collection discovery).
All tool names follow a consistent verb_noun snake_case pattern (build_, find_, get_, search_), making the API predictable and easy to navigate.
13 tools is a reasonable size for a golf data server covering courses, equipment, architects, trips, and reviews. The slight overlap between search tools could be consolidated, but the count is not excessive.
The domain is well-covered for read-only data (courses, scorecards, reviews, equipment, architects), but tee times are a placeholder and trip building relies on external verification. This leaves notable gaps in functionality that agents must work around.