List known surf spots
list_surf_spotsLists surf spots saved by Global Surfari users (popular and recently added).
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Global Surfari Surf Forecasts
TDQS
A3.8/5.0
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses that it returns a list of spots, popular and recently added, implying a read-only operation. However, with no annotations, it does not clarify whether it requires authentication or has any side effects, though none are expected.
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 a single, efficient sentence that communicates the tool's purpose without any extraneous words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple list tool with no parameters and no output schema, the description provides adequate context: what it lists and a hint about ordering (popular and recently added). Could mention that it returns spot IDs or details, but it's sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters exist, and the schema description coverage is 100%. The description adds no parameter info, but none is needed. Baseline for 0 parameters is 4.
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 clearly states the verb (lists) and the resource (surf spots saved by Global Surfari users), and the qualifier (popular and recently added) distinguishes it from sibling tools like get_surf_forecast, which deal with forecasts.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when or when not to use this tool, nor any mention of alternatives. The sibling tool names imply that list_surf_spots is for obtaining spot IDs before using forecast tools, but this is not explicitly stated.
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
A4.1/5.0
Disambiguation5/5
Each tool has a distinct input method: get_surf_forecast uses latitude/longitude, get_surf_forecast_by_spot uses a named spot, and list_surf_spots returns a list of spots. No overlap in purpose.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern with snake_case: get_surf_forecast, get_surf_forecast_by_spot, list_surf_spots. The naming is uniform and predictable.
Tool Count4/5
With 3 tools, the server is slightly small but still reasonable for its focused domain. Additional tools like a spot detail or search could enhance completeness, but the count is not problematic.
Completeness4/5
The server covers the primary use cases: forecast by coordinates, forecast by named spot, and listing spots. Minor gaps exist (e.g., no spot details, no date range specification), but the core functionality is well-covered.