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list_omnifocus_tasks

Retrieve OmniFocus tasks to enable AI agents to review pending items, track deadlines, and assist with project management.

Instructions

List tasks from OmniFocus

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • server.js:82-86 (registration)
    Tool registration loop that registers list_omnifocus_tasks (and all other tools) with the MCP server using a stub handler
    for (const [name, desc] of TOOLS) {
      server.tool(name, desc, {}, async () => ({
        content: [{ type: "text", text: "This is an inspection stub. Install Pilot MCP on macOS: npx -y local-mcp@latest setup" }],
      }));
    }
  • server.js:39-39 (registration)
    Definition of the list_omnifocus_tasks tool name and description in the TOOLS array
    ["list_omnifocus_tasks", "List tasks from OmniFocus"],
  • Import statements and server initialization - includes MCP SDK imports and zod for validation
    #!/usr/bin/env node
    /**
     * Minimal MCP stub for Glama inspection.
     * Lists all Pilot MCP tools so Glama can detect them.
     * The real server is a native macOS binary.
     */
    const { McpServer } = require("@modelcontextprotocol/sdk/server/mcp.js");
    const { StdioServerTransport } = require("@modelcontextprotocol/sdk/server/stdio.js");
    const { z } = require("zod");
    
    const server = new McpServer({ name: "pilot-mcp", version: "2.2.0" });
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 but fails to indicate whether the operation is read-only, if pagination is supported, what task statuses are included (completed vs. active), or the expected return format.

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 extremely brief (4 words) with no wasted language. However, given the lack of annotations and sibling differentiation, it may be overly terse rather than appropriately concise.

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?

Despite low complexity (zero parameters), the description is incomplete as it omits critical scope information (what subset of tasks is returned) and fails to distinguish from similar listing/searching siblings, leaving the agent uncertain about which tool to select.

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 contains zero parameters, establishing a baseline score of 4. With no parameters to describe, the description appropriately does not attempt to add parameter semantics.

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

Purpose3/5

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

The description states the basic action (List) and resource (OmniFocus tasks), but lacks specificity regarding scope (e.g., all tasks, incomplete only, inbox) and fails to differentiate from the sibling tool 'search_omnifocus_tasks'.

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?

No guidance provided on when to use this tool versus 'search_omnifocus_tasks' or 'list_omnifocus_projects', nor any mention of prerequisites or filtering capabilities.

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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