Task

A task in AgentRQ is a discrete unit of work created by an AI agent. Tasks appear on your task board and serve as the primary collaboration object between the agent and the human — containing a title, description, current status, and a full conversation thread.

Anatomy of a Task

Field	Description
`title`	Short name for the work item
`description`	Detailed description of what the agent is doing
`status`	Current state: `pending`, `ongoing`, `completed`, `failed`
`chat_id`	Unique identifier for the task's conversation thread
`attachments`	Files uploaded by the agent or human
`messages`	Full conversation history between agent and human

Task Lifecycle

text

pending → ongoing → completed
                  ↘ failed

Pending — Task has been created but the agent hasn't started yet
Ongoing — Agent is actively working on the task
Completed — Task is finished successfully
Failed — Task encountered an unrecoverable error

Creating Tasks via MCP

Claude Code agents create tasks using the task MCP tool with the create action:

json

{
  "action": "create",
  "payload": {
    "title": "Refactor auth middleware",
    "body": "Rewriting the JWT validation logic to fix the token expiry bug"
  }
}

help {"action": "task.create"} lists every field the payload takes. The older createTask tool name still works for clients that are already installed.

The task immediately appears on the human's task board with real-time updates.

Tasks as Collaboration Units

Each task has its own conversation thread. The agent can send messages via task reply, and the human can respond directly. This makes tasks the natural unit for human-in-the-loop oversight — one task per work item, with full history preserved.