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matrix_daily_summary

Generate formatted daily summaries of Matrix entries by parsing timestamps, bug UIDs, and time spent data. Creates human-readable reports for revenue tracking and business management.

Instructions

Generate formatted summary of Matrix entries for a specific date. Automatically parses timestamps, bug UIDs, time spent, and generates human-readable output.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dateNoDate in YYYY-MM-DD format (defaults to today)
formatNoOutput format

Implementation Reference

  • Handler for matrix_daily_summary tool call. Dispatches to external Google Apps Script API via callAPI function with action 'matrixDailySummary' and tool arguments.
    case "matrix_daily_summary":
      result = await callAPI("matrixDailySummary", args);
      break;
  • Input schema defining parameters for matrix_daily_summary: optional date (YYYY-MM-DD) and format (bullet, prose, slack).
    inputSchema: {
      type: "object",
      properties: {
        date: {
          type: "string",
          description: "Date in YYYY-MM-DD format (defaults to today)"
        },
        format: {
          type: "string",
          description: "Output format",
          enum: ["bullet", "prose", "slack"]
        }
      }
    }
  • index.js:499-516 (registration)
    Registration of the matrix_daily_summary tool in the ListToolsRequestHandler response, including name, description, and input schema.
    {
      name: "matrix_daily_summary",
      description: "Generate formatted summary of Matrix entries for a specific date. Automatically parses timestamps, bug UIDs, time spent, and generates human-readable output.",
      inputSchema: {
        type: "object",
        properties: {
          date: {
            type: "string",
            description: "Date in YYYY-MM-DD format (defaults to today)"
          },
          format: {
            type: "string",
            description: "Output format",
            enum: ["bullet", "prose", "slack"]
          }
        }
      }
    },
  • callAPI helper function that all proxied tools (including matrix_daily_summary) use to POST requests to the Google Apps Script backend URL with the action name and arguments as form data.
    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 mentions that the tool 'automatically parses timestamps, bug UIDs, time spent, and generates human-readable output,' which gives some insight into its processing behavior. However, it lacks details on error handling, performance characteristics (e.g., rate limits), or any side effects, which are important for a tool that processes data. The description doesn't contradict annotations, but it's insufficient for full transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise and front-loaded, stating the core purpose in the first sentence. The second sentence adds useful details about parsing and output generation without redundancy. It's appropriately sized for the tool's complexity, with no wasted words, though it could be slightly more structured to highlight key points.

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 moderate complexity (2 parameters, no output schema, no annotations), the description is somewhat complete but has gaps. It explains what the tool does and its output format, but lacks details on error cases, input validation, or how it interacts with sibling tools. Without an output schema, more information on return values would be helpful, but the description doesn't provide this, leaving room for improvement in overall context.

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?

The input schema has 100% description coverage, with clear documentation for both parameters ('date' and 'format'), including enum values for 'format'. The description adds minimal value beyond the schema, as it doesn't elaborate on parameter usage or provide examples. Since the schema coverage is high, the baseline score of 3 is appropriate, as the description doesn't compensate with additional semantic insights.

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: 'Generate formatted summary of Matrix entries for a specific date.' It specifies the verb ('generate'), resource ('Matrix entries'), and scope ('for a specific date'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate from sibling tools like 'matrix_time_analysis' or 'query_matrix', which might have overlapping functionality.

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 mentions what the tool does but doesn't indicate scenarios where it's preferred over siblings like 'matrix_time_analysis' or 'query_matrix', nor does it mention prerequisites or exclusions. This lack of context could lead to confusion in tool selection.

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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