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ainote-dev

AI Note MCP Server

by ainote-dev

create_task

Generate tasks in AI Note by specifying content, due date, importance, and category. Enables task management through natural language integration with Claude Desktop.

Instructions

Create a new task in AI Note

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
category_idNoCategory ID
contentYesTask content
due_dateNoDue date in ISO format
is_importantNoMark task as important

Implementation Reference

  • The handler function for the 'create_task' tool. It proxies the tool arguments to the backend API via apiClient.callTool('create_task', args) and returns the result.
    handler: async (args, { apiClient }) => {
      const result = await apiClient.callTool('create_task', args);
      return result;  // Return full result with { content: [...] }
    }
  • Schema definition for the 'create_task' tool, specifying the input parameters: content (required), is_important, due_date, category_id.
    function createTaskDefinition() {
      return {
        name: 'create_task',
        description: 'Create a new task in AI Note',
        inputSchema: {
          type: 'object',
          properties: {
            content: {
              type: 'string',
              description: 'Task content'
            },
            is_important: {
              type: 'boolean',
              description: 'Mark task as important'
            },
            due_date: {
              type: 'string',
              description: 'Due date in ISO format'
            },
            category_id: {
              type: 'string',
              description: 'Category ID'
            }
          },
          required: ['content']
        }
      };
    }
  • Registers the shared tools (including 'create_task') into the MCP tool registry via registry.registerMany(getSharedTools()).
    function registerTools(registry, { includeChatGpt }) {
      registry.registerMany(getSharedTools());
    
      if (includeChatGpt) {
        registry.registerMany(getChatGptTools());
      }
    }
  • The tool object for 'create_task' registered within the getSharedTools() array.
    {
      definition: createTaskDefinition(),
      handler: async (args, { apiClient }) => {
        const result = await apiClient.callTool('create_task', args);
        return result;  // Return full result with { content: [...] }
      }
    },
Behavior2/5

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 states the tool creates a task, implying a write operation, but lacks details on permissions, side effects (e.g., if it triggers notifications), error handling, or response format. This is a significant gap for a mutation tool without annotation support.

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 fluff or redundancy. It is front-loaded and appropriately sized, 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.

Completeness2/5

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

Given the complexity of a mutation tool with no annotations and no output schema, the description is incomplete. It fails to address behavioral aspects like what happens on success or failure, and it doesn't compensate for the lack of structured data, leaving gaps in understanding how to use the tool effectively.

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 schema description coverage is 100%, with clear descriptions for all parameters (e.g., 'Task content', 'Due date in ISO format'). The description adds no additional parameter semantics beyond what the schema provides, so it meets the baseline of 3 for adequate but not enhanced coverage.

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 ('Create a new task') and the target resource ('in AI Note'), which is specific and unambiguous. It distinguishes from siblings like 'delete_task' and 'update_task' by focusing on creation. However, it doesn't explicitly contrast with 'list_tasks' or 'list_categories', keeping it from 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 like 'update_task' for modifications or 'list_tasks' for viewing. There are no prerequisites, exclusions, or context for usage, leaving the agent to infer 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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