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Find Nearby Courses

find_nearby_courses
Read-onlyIdempotent

Find golf courses within an exact distance of a city, ZIP code, destination, or coordinate. Supports public-access and private filters and returns exact mileage, logo availability, scorecard availability, and maximum slope.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
stateNoOptional 2-letter state code to disambiguate a city
accessNoall
latitudeNo
locationNoCity, 5-digit ZIP code, or golf destination
longitudeNo
distance_milesNo25

TDQS

A4.1/5.0
Behavior4/5

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

The annotations already declare read-only and idempotent behavior, so the bar is lower. The description adds useful behavioral context by listing the specific return fields (exact mileage, logo availability, scorecard availability, maximum slope), which goes beyond the structured metadata. It does not disclose potential edge cases like coordinate pairing requirements, but is not misleading.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two succinct sentences, front-loaded with the core action and scope, and every phrase adds value. No redundancy or filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has 7 parameters, no required fields, and no output schema, so the description carries a significant burden. It covers the primary search concept and output fields, but omits key operational details such as parameter defaults (distance_miles, limit), how coordinates are supplied, and the full set of access filter values. This is adequate but leaves clear gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is only 29%, so the description must compensate. It does clarify that 'location' can be a city, ZIP, destination, or coordinate and mentions access-related filters, but it leaves out the 'limit' parameter and does not explain that 'state' disambiguates cities or that latitude/longitude likely need to be paired. It partially compensates but not fully.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('Find') with a clear resource ('golf courses') and precisely defines the scope ('within an exact distance of a city, ZIP code, destination, or coordinate'). It also mentions filters and return details, which distinguishes it from broader sibling tools like search_courses.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context for when to use this tool: when you need courses near a specified location or coordinate. However, it does not explicitly mention when not to use it or name alternative sibling tools, so it misses the higher bar for explicit exclusions.

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

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TDQS

A3.9/5.0
Disambiguation3/5

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).

Naming Consistency5/5

All tool names follow a consistent verb_noun snake_case pattern (build_, find_, get_, search_), making the API predictable and easy to navigate.

Tool Count4/5

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.

Completeness3/5

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.

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