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get_pipeline

Retrieve all leads currently in the sales pipeline for revenue tracking and business management.

Instructions

Get all leads in the pipeline

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The handler for the 'get_pipeline' tool. It calls the shared callAPI helper with action 'getPipeline', which proxies the request to a Google Apps Script backend handling the actual pipeline logic.
    case "get_pipeline":
      result = await callAPI("getPipeline");
      break;
  • index.js:158-165 (registration)
    Registration of the 'get_pipeline' tool in the listTools response, including its name, description, and input schema (no required parameters).
    {
      name: "get_pipeline",
      description: "Get all leads in the pipeline",
      inputSchema: {
        type: "object",
        properties: {},
      },
    },
  • Input schema for 'get_pipeline': an empty object (no parameters expected).
    inputSchema: {
      type: "object",
      properties: {},
    },
  • Shared helper function callAPI used by all tools (including get_pipeline) to forward requests to the external Google Apps Script API at the configured URL.
    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. It states 'Get all leads' but doesn't disclose behavioral traits such as whether this is a read-only operation, if it requires authentication, how data is returned (e.g., pagination, format), or any rate limits. This leaves significant gaps for a tool with potential data retrieval implications.

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 to understand at a glance.

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?

Given the complexity of retrieving 'all leads' (which could involve large datasets), no annotations, and no output schema, the description is incomplete. It lacks details on return values, data structure, or any constraints, making it inadequate for informed tool selection by an AI agent.

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 doesn't add param info, but that's acceptable here as there are no params to explain, warranting a baseline score above minimum.

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 action ('Get') and resource ('all leads in the pipeline'), making the purpose understandable. However, it doesn't explicitly differentiate from sibling tools like 'get_metrics' or 'get_dashboard' that might also retrieve data, so it lacks sibling distinction for a perfect 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 'check_new_leads' or 'update_lead' that might handle leads differently, there's no indication of context, prerequisites, or exclusions for usage.

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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