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get_dashboard

Retrieve current revenue dashboard with key metrics for tracking business performance and managing revenue operations.

Instructions

Get current revenue dashboard with all key metrics

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • index.js:150-157 (registration)
    Registration of the 'get_dashboard' tool including name, description, and empty input schema in the ListToolsRequestSchema handler.
    {
      name: "get_dashboard",
      description: "Get current revenue dashboard with all key metrics",
      inputSchema: {
        type: "object",
        properties: {},
      },
    },
  • Input schema for get_dashboard tool: empty object (no parameters required). No output schema defined.
    inputSchema: {
      type: "object",
      properties: {},
    },
  • Handler implementation for get_dashboard: calls shared callAPI helper with action 'getDashboard' which proxies to external Google Apps Script API.
    case "get_dashboard":
      result = await callAPI("getDashboard");
      break;
  • Shared helper function callAPI used by get_dashboard (and other tools) to make POST requests to the Google Apps Script web app URL with the action parameter determining the backend operation.
    async function callAPI(action, data = {}) {
      debugLog('=== API CALL START ===');
      debugLog(`Action: ${action}`);
      debugLog(`Data: ${JSON.stringify(data)}`);
    
      try {
        // Build form-encoded body for POST
        const formData = new URLSearchParams();
        formData.append('action', action);
    
        // Add all data fields to form
        for (const [key, value] of Object.entries(data)) {
          if (value !== undefined && value !== null) {
            formData.append(key, value.toString());
          }
        }
    
        const formString = formData.toString();
        debugLog(`FormData: ${formString}`);
        debugLog(`API_URL: ${API_URL}`);
    
        // Use POST with proper content type
        const response = await fetch(API_URL, {
          method: 'POST',
          headers: {
            'Content-Type': 'application/x-www-form-urlencoded',
          },
          body: formString
        });
    
        debugLog(`Response status: ${response.status}`);
        debugLog(`Response ok: ${response.ok}`);
    
        if (!response.ok) {
          debugLog(`Response not OK: ${response.status} ${response.statusText}`);
          throw new Error(`API request failed: ${response.status} ${response.statusText}`);
        }
    
        const text = await response.text();
        debugLog(`Response text length: ${text.length}`);
        debugLog(`Response text: ${text}`);
    
        if (!text) {
          debugLog('ERROR: Empty response from API');
          throw new Error('Empty response from API');
        }
    
        const parsed = JSON.parse(text);
        debugLog(`Parsed successfully: ${JSON.stringify(parsed)}`);
        debugLog('=== API CALL END ===');
        return parsed;
    
      } catch (error) {
        debugLog(`ERROR in callAPI: ${error.message}`);
        debugLog(`ERROR stack: ${error.stack}`);
        throw error;
      }
    }

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.2/5.0
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 that this is a 'get' operation but doesn't describe return format, data freshness, required permissions, or any side effects; it adds little beyond the tool name.

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, front-loaded sentence with no filler. Every word contributes to identifying the resource and content.

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?

For a zero-parameter getter, the description lets an agent invoke the tool, but there is no output schema and no annotations, so the agent has no detail about the response structure or what 'all key metrics' concretely includes. It is minimally complete but leaves room for ambiguity.

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 tool has zero parameters and the schema is empty, so a baseline of 4 applies. There are no parameter semantics for the description to clarify.

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 uses a clear verb and resource: 'Get current revenue dashboard with all key metrics.' It distinguishes itself from sibling get_pipeline by specifying 'revenue dashboard,' though it doesn't enumerate the metrics or further delimit 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 given about when to use this tool versus alternatives such as get_pipeline. The phrase 'revenue dashboard' implies a use case, but there are no explicit conditions, exclusions, or alternative references.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.