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by MissionSquad

fundamentalData_earningsCalendar

Fetch upcoming earnings calendar data for stocks to track corporate financial announcements. Specify symbols and time horizons for earnings reports.

Instructions

Fetches upcoming earnings calendar (CSV endpoint).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
symbolNoFetch earnings calendar for a specific symbol.
horizonNoTime horizon for upcoming earnings.3month

Implementation Reference

  • Generic handler function that implements the core logic for executing the tool: resolves API key, manages AVantage client instance via resourceManager, calls the specific AVantage library method (av.fundamentalData.earningsCalendar(params) for this tool), handles errors, and returns JSON stringified data.
    async function executeAvantageTool<TArgs, TResult>(
      toolName: string,
      args: TArgs,
      context: Context<Record<string, unknown> | undefined>, // Use the imported Context type directly
      avantageMethod: (
        av: AVantage,
        args: TArgs
      ) => Promise<{ error?: boolean; reason?: string; data?: TResult }>
    ): Promise<string> {
      logger.info(`Executing '${toolName}' tool for request ID: ${context}`);
      logger.debug(`Args for ${toolName}: ${JSON.stringify(args)}`);
    
      // --- Authentication & Resource Management ---
      // Access extraArgs safely - it might be null or undefined
      const extraArgsApiKey = context.extraArgs?.apiKey as string | undefined;
      const apiKey = extraArgsApiKey || config.apiKey;
    
      if (!apiKey) {
        logger.error(`'${toolName}' failed: Alpha Vantage API key missing.`);
        throw new UserError(apiKeyErrorMessage);
      }
      logger.debug(
        `Using AV API key (source: ${extraArgsApiKey ? "extraArgs" : "environment"}) for ${toolName}`
      );
    
      try {
        // Get or create AVantage instance managed by ResourceManager
        const av = await resourceManager.getResource<AVantage>(
          apiKey, // Cache key is the resolved API key
          "avantage_client", // Type identifier for logging
          async (key) => {
            // Factory Function
            logger.info(
              `Creating new AVantage instance for key ending ...${key.slice(-4)}`
            );
            // AVantage library reads AV_PREMIUM from process.env internally
            return new AVantage(key);
          },
          async (avInstance) => {
            // Cleanup Function (no-op needed for AVantage)
            logger.debug(`Destroying AVantage instance (no-op)`);
          }
        );
    
        // --- Library Call ---
        const result = await avantageMethod(av, args);
    
        // --- Response Handling ---
        if (result.error) {
          logger.warn(
            `'${toolName}' failed. Reason from avantage: ${result.reason}`
          );
          throw new UserError(result.reason || `Tool '${toolName}' failed.`);
        }
    
        if (result.data === undefined || result.data === null) {
          logger.warn(`'${toolName}' completed successfully but returned no data.`);
          return "null"; // Return string "null" for empty data
        }
    
        logger.info(`'${toolName}' completed successfully.`);
        // Stringify the data part of the response
        return JSON.stringify(result.data);
      } catch (error: any) {
        logger.error(
          `Error during execution of '${toolName}': ${error.message}`,
          error
        );
        // If it's already a UserError, rethrow it
        if (error instanceof UserError) {
          throw error;
        }
        // Otherwise, wrap it in a UserError
        throw new UserError(
          `An unexpected error occurred while executing tool '${toolName}': ${error.message}`
        );
      }
    }
  • Zod schema defining the input parameters for the fundamentalData_earningsCalendar tool.
    export const FundamentalDataEarningsCalendarParamsSchema = z.object({
      symbol: z.string().optional().describe('Fetch earnings calendar for a specific symbol.'),
      horizon: z.enum(['3month', '6month', '12month']).default('3month').optional().describe('Time horizon for upcoming earnings.'),
    }).describe('Parameters for fetching earnings calendar (CSV endpoint).')
  • src/index.ts:919-933 (registration)
    Registers the MCP tool 'fundamentalData_earningsCalendar' with the FastMCP server, linking name, description, input schema, and handler execution.
    server.addTool({
      name: "fundamentalData_earningsCalendar",
      description: "Fetches upcoming earnings calendar (CSV endpoint).",
      parameters: schemas.FundamentalDataEarningsCalendarParamsSchema,
      execute: (
        args,
        context // Let type be inferred
      ) =>
        executeAvantageTool(
          "fundamentalData_earningsCalendar",
          args,
          context,
          (av, params) => av.fundamentalData.earningsCalendar(params)
        ),
    });
  • Uses resourceManager to get or create the AVantage API client instance, cached by API key, which is central to all tool executions including this one.
    // Get or create AVantage instance managed by ResourceManager
    const av = await resourceManager.getResource<AVantage>(
      apiKey, // Cache key is the resolved API key
      "avantage_client", // Type identifier for logging
      async (key) => {
        // Factory Function
        logger.info(
          `Creating new AVantage instance for key ending ...${key.slice(-4)}`
        );
        // AVantage library reads AV_PREMIUM from process.env internally
        return new AVantage(key);
      },
      async (avInstance) => {
        // Cleanup Function (no-op needed for AVantage)
        logger.debug(`Destroying AVantage instance (no-op)`);
      }
    );
Behavior2/5

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

With no annotations provided, the description carries full burden but offers minimal behavioral insight. It mentions 'CSV endpoint' which hints at the response format, but doesn't disclose whether this is a read-only operation, potential rate limits, authentication requirements, data freshness, or what happens when no data is found. For a data-fetching tool with zero annotation coverage, this is insufficient.

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 with zero wasted words. It's front-loaded with the core purpose and includes the useful 'CSV endpoint' detail. Every element earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a data retrieval tool with no annotations and no output schema, the description is incomplete. It doesn't explain what the CSV response contains, how results are structured, whether pagination exists, or what happens with invalid inputs. The 'CSV endpoint' hint is helpful but insufficient for an agent to properly interpret results.

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 fully documents both parameters (symbol and horizon with enum values). The description adds no parameter-specific information beyond what's in the schema - it doesn't explain the relationship between parameters, provide examples, or clarify edge cases. Baseline 3 is appropriate when schema does all the work.

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 ('Fetches') and resource ('upcoming earnings calendar') with the additional detail of 'CSV endpoint' indicating the format. It distinguishes from siblings like fundamentalData_earnings (which likely provides historical earnings data) by specifying 'upcoming' and 'calendar', but doesn't explicitly contrast with fundamentalData_ipoCalendar which is another calendar-type tool.

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. It doesn't mention when to choose this over fundamentalData_earnings for earnings data, or how it differs from fundamentalData_ipoCalendar for calendar data. There's no context about prerequisites, timing considerations, or limitations.

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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