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Load Day Planner

load_day_planner

Open an interactive dashboard to view and manage your daily schedule by integrating calendar events, prioritized emails, and relevant documents in one interface.

Instructions

Opens an interactive day planning dashboard showing your calendar, emails, and docs.

The dashboard shows:

  • Today's calendar events (expandable to reveal related emails and docs)

  • Inbox emails prioritized by importance

  • Recent Drive documents surfaced by meeting context

  • Interactive buttons: expand events, mark emails handled, start meeting prep

Use this to give the user a holistic view of their day.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dateNoDate to plan for in YYYY-MM-DD format. Defaults to today.
maxEmailsNoMax email threads to surface (default 10)
maxDocsNoMax recent Drive docs to surface (default 5)

Implementation Reference

  • The handler function for load_day_planner tool - fetches calendar events, emails, and docs, cross-references them, and returns DayPlannerData JSON
    async ({ date, maxEmails, maxDocs }) => {
      date = date ?? new Date().toISOString().split('T')[0];
    
      const [events, emails, recentDocs] = await Promise.all([
        svc.fetchCalendarEvents(date),
        svc.fetchEmailThreads(maxEmails),
        svc.fetchRecentDocs(maxDocs),
      ]);
    
      const { eventEmailMap, eventDocMap } = svc.crossReference(events, emails, recentDocs);
    
      const data: DayPlannerData = {
        generatedAt: new Date().toISOString(),
        date,
        events,
        emails,
        recentDocs,
        eventEmailMap,
        eventDocMap,
      };
    
      return {
        content: [{ type: 'text' as const, text: JSON.stringify(data) }],
      };
    },
  • Zod schema LoadDayPlannerSchema defining input validation: optional date (YYYY-MM-DD), maxEmails (1-50), and maxDocs (1-20)
    const LoadDayPlannerSchema = z.object({
      date: z.string().regex(/^\d{4}-\d{2}-\d{2}$/).optional()
        .describe('Date to plan for in YYYY-MM-DD format. Defaults to today.'),
      maxEmails: z.number().int().min(1).max(50).default(10)
        .describe('Max email threads to surface (default 10)'),
      maxDocs: z.number().int().min(1).max(20).default(5)
        .describe('Max recent Drive docs to surface (default 5)'),
    });
  • registerAppTool call that registers the load_day_planner tool with MCP server, including title, description, inputSchema, and UI resource URI metadata
      registerAppTool(
        server,
        'load_day_planner',
        {
          title: 'Load Day Planner',
          description: `Opens an interactive day planning dashboard showing your calendar, emails, and docs.
    
    The dashboard shows:
    - Today's calendar events (expandable to reveal related emails and docs)
    - Inbox emails prioritized by importance
    - Recent Drive documents surfaced by meeting context
    - Interactive buttons: expand events, mark emails handled, start meeting prep
    
    Use this to give the user a holistic view of their day.`,
          inputSchema: LoadDayPlannerSchema.shape,
          _meta: { ui: { resourceUri: RESOURCE_URI } },
        },
        async ({ date, maxEmails, maxDocs }) => {
          date = date ?? new Date().toISOString().split('T')[0];
    
          const [events, emails, recentDocs] = await Promise.all([
            svc.fetchCalendarEvents(date),
            svc.fetchEmailThreads(maxEmails),
            svc.fetchRecentDocs(maxDocs),
          ]);
    
          const { eventEmailMap, eventDocMap } = svc.crossReference(events, emails, recentDocs);
    
          const data: DayPlannerData = {
            generatedAt: new Date().toISOString(),
            date,
            events,
            emails,
            recentDocs,
            eventEmailMap,
            eventDocMap,
          };
    
          return {
            content: [{ type: 'text' as const, text: JSON.stringify(data) }],
          };
        },
      );
  • src/index.ts:36-37 (registration)
    Imports and calls registerDayPlannerTools(server) to register both load_day_planner and handle_day_planner_action tools with the MCP server
    // Register day planner tools (load_day_planner + handle_day_planner_action)
    registerDayPlannerTools(server);
  • TypeScript interface LoadDayPlannerInput defining the type structure for tool input parameters
    export interface LoadDayPlannerInput {
      date?: string;           // YYYY-MM-DD, defaults to today
      daysAhead?: number;      // Include events N days ahead (default 0 = today only)
      maxEmails?: number;      // Max emails to fetch (default 20)
      maxDocs?: number;        // Max recent docs to fetch (default 10)
    }
Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It describes what the dashboard shows and interactive features, which adds useful context about the tool's behavior. However, it doesn't address important behavioral aspects like whether this is a read-only operation, if it requires specific permissions, or any rate limits. The description doesn't contradict annotations (none exist).

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 appropriately sized and well-structured with clear bullet points listing dashboard components. It's front-loaded with the core purpose. Some minor verbosity exists in the bullet descriptions, but overall it's efficient and each sentence adds value.

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

Completeness4/5

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

Given the tool's moderate complexity (interactive dashboard with multiple data sources), no annotations, and no output schema, the description does a reasonably complete job. It explains what the tool does, what the dashboard contains, and how to use it. However, it could be more complete by addressing the lack of output schema (what exactly gets returned) and providing more behavioral 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?

Schema description coverage is 100%, so the schema already fully documents all three parameters. The description doesn't add any parameter-specific information beyond what's in the schema. According to scoring rules, when schema coverage is high (>80%), the baseline is 3 even with no param info in the description.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Opens an interactive day planning dashboard showing your calendar, emails, and docs.' It uses specific verbs ('Opens', 'showing') and resources ('dashboard', 'calendar', 'emails', 'docs'), and distinguishes from the sibling tool 'handle_day_planner_action' by focusing on loading/displaying rather than handling actions.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context for when to use this tool: 'Use this to give the user a holistic view of their day.' It implies usage for day planning but doesn't explicitly state when NOT to use it or mention alternatives beyond the sibling tool, which is only referenced implicitly through differentiation.

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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