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RyanCardin15

LocalTides MCP Server

get_high_tide_flooding_daily

Retrieve daily high tide flooding counts for a specific station, filtering by date range, flood threshold, and datum reference. Supports JSON, XML, and CSV output formats.

Instructions

Get high tide flooding daily count data for a station

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
begin_dateNoStart date (YYYYMMDD format)
datumNoDatum reference for DPAPI
end_dateNoEnd date (YYYYMMDD format)
formatNoOutput format (json, xml, csv)
stationYesStation ID
thresholdNoFlood threshold level
yearNoYear for analysis (YYYY format)

Implementation Reference

  • Registers the 'get_high_tide_flooding_daily' tool with the FastMCP server, including name, description, input schema, and handler function that delegates to DpapiService and returns JSON.
    server.addTool({
      name: 'get_high_tide_flooding_daily',
      description: 'Get high tide flooding daily count data for a station',
      parameters: HighTideFloodingDailySchema,
      execute: async (params) => {
        try {
          const result = await dpapiService.getHighTideFloodingDaily(params);
          return JSON.stringify(result);
        } catch (error) {
          if (error instanceof Error) {
            throw new Error(`Failed to get high tide flooding daily data: ${error.message}`);
          }
          throw new Error('Failed to get high tide flooding daily data');
        }
      }
    });
  • Zod schema defining the input parameters for the get_high_tide_flooding_daily tool, including station, format, datum, threshold, and date range options.
    export const HighTideFloodingDailySchema = z.object({
      station: StationSchema,
      format: FormatSchema,
      datum: DpapiDatumSchema,
      threshold: ThresholdSchema,
      begin_date: z.string().optional().describe('Start date (YYYYMMDD format)'),
      end_date: z.string().optional().describe('End date (YYYYMMDD format)'),
      year: YearSchema
    }).describe('Get high tide flooding daily count data');
  • DpapiService method implementing the core logic: extracts parameters and calls fetchDpapi with the '/htf/daily' endpoint to retrieve data from NOAA DPAPI.
    async getHighTideFloodingDaily(params: Record<string, any>): Promise<any> {
      const { station, format = 'json', ...rest } = params;
      
      return this.fetchDpapi('/htf/daily', {
        station,
        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 states the tool retrieves data but doesn't mention any behavioral traits like rate limits, authentication requirements, data freshness, or potential side effects. For a data-fetching tool with no annotations, this leaves significant gaps in understanding how it operates.

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 directly states the tool's purpose without unnecessary words. It's front-loaded with the core action and resource, making it easy to parse quickly, which is ideal for 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 complexity of 7 parameters (with 1 required) and no output schema or annotations, the description is minimally adequate. It identifies the data type but lacks context on usage, behavioral traits, or output format details. For a tool with moderate parameter complexity and no structured support, it should provide more guidance to be fully helpful.

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?

The description adds no parameter semantics beyond what's in the input schema, which has 100% coverage with detailed descriptions for all 7 parameters. Since the schema fully documents parameters like date formats, enums, and required fields, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't need to given the comprehensive schema.

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 resource ('high tide flooding daily count data for a station'), making the purpose understandable. However, it doesn't explicitly differentiate from sibling tools like 'get_high_tide_flooding_annual' or 'get_high_tide_flooding_monthly', which would require mentioning the 'daily' time granularity more prominently.

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 multiple sibling tools for high tide flooding data (e.g., annual, monthly, seasonal, projections), there's no indication of the specific use case for daily counts, such as for detailed short-term analysis or monitoring.

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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