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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;
      }
    }
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 implies a read operation ('Get') but doesn't specify whether it requires authentication, has rate limits, returns real-time or cached data, or what happens on errors. For a tool with zero annotation coverage, this is a significant gap in transparency.

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 any wasted words. It's appropriately sized and front-loaded, making it easy for an agent to parse quickly.

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 tool's simplicity (0 parameters, no output schema), the description is adequate but has clear gaps. It lacks behavioral details (e.g., authentication needs, data freshness) and usage guidelines compared to siblings, making it minimally viable but not fully complete for informed tool selection.

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 0 parameters with 100% coverage, so no parameter documentation is needed. The description adds value by clarifying the scope ('current revenue dashboard with all key metrics'), which isn't captured in the schema, earning a score above the baseline of 3 for such cases.

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 tool's purpose with a specific verb ('Get') and resource ('current revenue dashboard with all key metrics'), making it easy to understand what it does. However, it doesn't explicitly distinguish itself from sibling tools like 'get_metrics' or 'get_pipeline', which might also retrieve related data, so it misses the highest score.

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 siblings like 'get_metrics' and 'get_pipeline' that might retrieve similar or overlapping data, there's no indication of context, prerequisites, or exclusions, leaving the agent to guess based on tool names alone.

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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