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RyanCardin15

noaa-tidesandcurrents-mcp

get_extreme_water_levels

Retrieve extreme water levels and exceedance probabilities for a specific station using station ID, with output in JSON, XML, or CSV formats. Supports English or metric units.

Instructions

Get extreme water levels and exceedance probabilities for a station

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
formatNoOutput format (json, xml, csv)
stationYesStation ID
unitsNoUnits to use ("english" or "metric")

Implementation Reference

  • The MCP tool handler (execute function) that calls the DpapiService method and returns the JSON-stringified result, with error handling.
    execute: async (params) => {
      try {
        const result = await dpapiService.getExtremeWaterLevels(params);
        return JSON.stringify(result);
      } catch (error) {
        if (error instanceof Error) {
          throw new Error(`Failed to get extreme water levels: ${error.message}`);
        }
        throw new Error('Failed to get extreme water levels');
      }
    }
  • Zod schema defining the input parameters for the get_extreme_water_levels tool (station, units, format).
    export const ExtremeWaterLevelsSchema = z.object({
      station: StationSchema,
      units: UnitsSchema,
      format: FormatSchema
    }).describe('Get extreme water levels for a station');
  • Registration of the get_extreme_water_levels tool on the FastMCP server, including name, description, input schema, and handler.
    server.addTool({
      name: 'get_extreme_water_levels',
      description: 'Get extreme water levels and exceedance probabilities for a station',
      parameters: ExtremeWaterLevelsSchema,
      execute: async (params) => {
        try {
          const result = await dpapiService.getExtremeWaterLevels(params);
          return JSON.stringify(result);
        } catch (error) {
          if (error instanceof Error) {
            throw new Error(`Failed to get extreme water levels: ${error.message}`);
          }
          throw new Error('Failed to get extreme water levels');
        }
      }
    });
  • Supporting service method in DpapiService that constructs and fetches from the NOAA DPAPI '/ewl' endpoint for extreme water levels data.
    async getExtremeWaterLevels(params: Record<string, any>): Promise<any> {
      const { station, units = 'english', format = 'json', ...rest } = params;
      
      return this.fetchDpapi('/ewl', {
        station,
        units,
        format,
        ...rest
      });
    }
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'Get extreme water levels and exceedance probabilities,' which implies a read-only operation, but does not cover aspects like rate limits, authentication needs, data freshness, or error handling. This leaves significant gaps in understanding the tool's behavior.

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

Conciseness4/5

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

The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It is front-loaded with the core action, but could be slightly improved by adding brief context to enhance clarity without sacrificing conciseness.

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?

Given the tool's moderate complexity (3 parameters, no output schema, no annotations), the description is minimally adequate. It covers the basic purpose but lacks details on behavioral traits, usage context, and output expectations. With no output schema, it should ideally hint at return values, but it does not, leaving some gaps in completeness.

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 100%, with clear descriptions for all parameters (station, format, units) including enums. The description does not add any meaning beyond what the schema provides, such as explaining what 'extreme water levels' entail or how 'exceedance probabilities' are calculated. Given the high schema coverage, a baseline score of 3 is appropriate.

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

Purpose4/5

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

The description clearly states the action ('Get') and the resource ('extreme water levels and exceedance probabilities for a station'), making the purpose understandable. However, it does not explicitly differentiate this tool from sibling tools like 'get_top_ten_water_levels' or 'get_water_levels', which might also involve water level data, so it lacks sibling distinction.

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?

The description provides no guidance on when to use this tool versus alternatives. With many sibling tools related to water levels, tides, and flooding, there is no indication of specific contexts, prerequisites, or exclusions for selecting this tool over others, leaving usage unclear.

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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