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get_data_coverage

Read-onlyIdempotent

Retrieve data coverage metrics for supported venue APIs. Returns earliest and latest timestamps, total records, symbol count, resolution, lag, and completeness per data type and venue scope.

Instructions

Get data coverage across supported venue APIs. Returns earliest/latest timestamps, total records, symbol count, resolution, lag, and completeness per data type per venue scope.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYesResult data object

Implementation Reference

  • src/index.ts:1938-1948 (registration)
    Registration of the 'get_data_coverage' tool using the registerTool helper. The handler calls api().dataQuality.coverage() and returns the result via formatResponse.
    // 30. Coverage Overview
    registerTool(
      "get_data_coverage",
      "Get data coverage across supported venue APIs. Returns earliest/latest timestamps, total records, symbol count, resolution, lag, and completeness per data type per venue scope.",
      {},
      ObjectOutputSchema,
      async () => {
        const data = await api().dataQuality.coverage();
        return formatResponse(data);
      }
    );
  • The actual handler function for get_data_coverage: an async arrow function that calls api().dataQuality.coverage() and passes the result to formatResponse.
    async () => {
      const data = await api().dataQuality.coverage();
      return formatResponse(data);
    }
  • Input schema (empty object {}) and output schema (ObjectOutputSchema) for the get_data_coverage tool. The tool takes no parameters and returns a 'data' object.
    registerTool(
      "get_data_coverage",
      "Get data coverage across supported venue APIs. Returns earliest/latest timestamps, total records, symbol count, resolution, lag, and completeness per data type per venue scope.",
      {},
      ObjectOutputSchema,
  • The registerTool helper function used to register get_data_coverage. It wraps the handler with API key guard and error handling, then calls server.registerTool.
    function registerTool(
      name: string,
      description: string,
      inputSchema: ZodRawShape,
      outputSchema: ZodRawShape,
      handler: (params: any) => Promise<McpContent>
    ): void {
      server.registerTool(
        name,
        {
          description,
          inputSchema,
          outputSchema,
          annotations: TOOL_ANNOTATIONS,
        },
        async (params: any) => {
          if (!client) {
            return {
              content: [{ type: "text" as const, text: MISSING_KEY_MESSAGE }],
              isError: true,
            };
          }
          try {
            return await handler(params);
          } catch (err) {
            const error = err instanceof OxArchiveError ? err : new OxArchiveError(String(err), 500);
            return formatError(error);
          }
        }
      );
    }
Behavior4/5

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

Annotations already indicate read-only, non-destructive, idempotent behavior. The description adds value by detailing the exact data returned (earliest/latest timestamps, total records, symbol count, resolution, lag, completeness) and the scoping (per data type per venue). No contradictions with annotations.

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, well-structured sentence that front-loads the main purpose ('Get data coverage across supported venue APIs') and immediately lists the return fields. Every word contributes meaning; no filler.

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?

Given no parameters and an existing output schema, the description covers the main return fields and scoping. However, it might benefit from mentioning if there are any limitations (e.g., date range constraints) or whether the data is real-time or cached. Still, it is fairly complete for a parameterless tool.

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?

The input schema has zero parameters, so schema coverage is trivial (100%). Description does not need to explain parameter semantics. Baseline for 0 params is 4, and the description appropriately omits parameter info.

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 'Get' and the resource 'data coverage', and lists specific returned fields (timestamps, records, symbol count, etc.). It distinguishes from siblings like get_symbol_coverage and get_exchange_coverage by focusing on aggregate coverage per data type per venue.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description does not explicitly state when to use this tool versus alternatives like get_symbol_coverage or get_data_quality_status. It implies usage for overall data coverage but lacks guidance on exclusions or when-not 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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