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RyanCardin15

LocalTides MCP Server

get_high_tide_flooding_likelihoods

Retrieve daily high tide flooding likelihoods for a specific station using station ID, date, and threshold level. Supports output in JSON, XML, or CSV formats for analysis and planning.

Instructions

Get high tide flooding daily likelihoods for a station

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dateNoSpecific date (YYYYMMDD format)
datumNoDatum reference for DPAPI
formatNoOutput format (json, xml, csv)
stationYesStation ID
thresholdNoFlood threshold level

Implementation Reference

  • The core handler function that fetches high tide flooding likelihoods data from the NOAA DPAPI endpoint '/htf/likelihoods' using the service's fetchDpapi method.
    async getHighTideFloodingLikelihoods(params: Record<string, any>): Promise<any> {
      const { station, format = 'json', ...rest } = params;
      
      return this.fetchDpapi('/htf/likelihoods', {
        station,
        format,
        ...rest
      });
    }
  • Zod schema defining the input parameters for the get_high_tide_flooding_likelihoods tool, including station, format, datum, threshold, and optional date.
    export const HighTideFloodingLikelihoodsSchema = z.object({
      station: StationSchema,
      format: FormatSchema,
      datum: DpapiDatumSchema,
      threshold: ThresholdSchema,
      date: z.string().optional().describe('Specific date (YYYYMMDD format)')
    }).describe('Get high tide flooding daily likelihoods');
  • Registration of the MCP tool 'get_high_tide_flooding_likelihoods' using server.addTool, which delegates to the DpapiService handler and uses the corresponding schema.
    server.addTool({
      name: 'get_high_tide_flooding_likelihoods',
      description: 'Get high tide flooding daily likelihoods for a station',
      parameters: HighTideFloodingLikelihoodsSchema,
      execute: async (params) => {
        try {
          const result = await dpapiService.getHighTideFloodingLikelihoods(params);
          return JSON.stringify(result);
        } catch (error) {
          if (error instanceof Error) {
            throw new Error(`Failed to get high tide flooding likelihoods: ${error.message}`);
          }
          throw new Error('Failed to get high tide flooding likelihoods');
        }
      }
    });
Behavior2/5

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

No annotations are provided, so the description carries full burden. It states it 'gets' data (implying read-only), but doesn't disclose behavioral traits like authentication requirements, rate limits, data freshness, or what happens with invalid inputs. For a tool with 5 parameters and no annotations, this leaves significant gaps in understanding how it behaves.

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 with zero waste. It's appropriately sized and front-loaded, making it easy to parse quickly without unnecessary elaboration.

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 5 parameters, no annotations, and no output schema, the description is minimally adequate but incomplete. It specifies the resource but doesn't address behavioral aspects or usage context. For a data retrieval tool with multiple parameters and sibling alternatives, more guidance would be helpful, though the 100% schema coverage partially compensates.

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%, so the schema already documents all 5 parameters thoroughly with descriptions and enums. The description adds no additional meaning beyond what's in the schema (e.g., it doesn't explain relationships between parameters like how 'datum' and 'threshold' interact). Baseline 3 is appropriate when schema does the heavy lifting.

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 verb ('Get') and resource ('high tide flooding daily likelihoods for a station'), making the purpose understandable. It distinguishes from some siblings like 'get_high_tide_flooding_annual' by specifying 'daily' likelihoods, but doesn't explicitly differentiate from 'get_high_tide_flooding_daily' which appears to be a direct sibling with similar scope.

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 is provided on when to use this tool versus alternatives. With multiple flooding-related tools in the sibling list (e.g., get_high_tide_flooding_annual, get_high_tide_flooding_daily, get_high_tide_flooding_monthly), the description offers no indication of which tool to choose for different temporal needs or scenarios.

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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