get_surf_forecast_by_spot7 day surf forecast for a named surf spot. Tries saved Global Surfari locations first, then geocodes the name. Example: "Bondi Beach", "Mavericks", "Bells Beach".
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | Surf spot or beach name |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses the behavior of trying saved locations first, then geocoding, and states the forecast duration (7 days). This is sufficient for a read-only forecast tool, though it could mention whether the tool might return partial data or fail gracefully.
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 sentences with no wasted words. The first sentence states what it does, the second explains how it works and gives examples. Information is front-loaded and easy to parse.
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 one required parameter, no output schema, and low complexity, the description is largely complete. It explains the tool's purpose, input resolution, and duration. A minor gap is the absence of any information about the output format, which might be assumed from a shared forecast schema, but it's not provided.
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 coverage is 100% (one parameter with description). The description adds value beyond the schema by explaining the resolution logic and giving examples. This helps the agent understand what constitutes a valid 'name' input.
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 provides a '7 day surf forecast for a named surf spot'. It distinguishes from siblings by specifying the input is a spot name and that it tries saved locations then geocodes. Examples like 'Bondi Beach' make the purpose concrete.
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 implicit guidance by stating the resolution strategy (saved locations then geocoding), which helps the agent understand how to use the tool. However, it does not explicitly contrast with siblings like 'get_surf_forecast' or 'list_surf_spots', nor provide when-not-to-use advice.
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.
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.
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.
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.
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.