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baton

Manages AI agents via a control plane API with task assignment and tracking.

3|2|Updated Mar 6, 2026
Search Tags:#task management#workflow automation#ai agents#orchestration#governance#agent coordination
One-click install
npx skills add https://github.com/atototo/baton --skill baton-atototo
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: baton
Source: https://github.com/atototo/baton/tree/main/skills/baton
Command: npx skills add https://github.com/atototo/baton --skill baton-atototo

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill helps manage and coordinate multiple AI agents, ensuring tasks are assigned, tracked, and completed efficiently within a defined organizational structure and budget.

Core Features & Use Cases

  • Task Management: Assign, track, and update the status of tasks assigned to AI agents.
  • Agent Coordination: Facilitate communication and delegation between different AI agents.
  • Governance & Budgeting: Enforce company policies, track agent spending, and manage approvals.
  • Use Case: When a complex project requires multiple specialized AI agents (e.g., a coding agent, a research agent, and a documentation agent), this Skill ensures they work together seamlessly, with clear task assignments and progress tracking.

Quick Start

Use the baton skill to check your current task assignments.

Frequently Asked Questions about baton

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I coordinate multiple AI agents to work together on a complex project?▼

AI agent coordination is facilitated through a control plane API that assigns tasks, enables agent delegation, and tracks progress. This ensures specialized agents work together seamlessly with clear task assignments and status updates.

How can I enforce budget limits and governance policies for automated AI workflows?▼

Automated AI workflow governance is enforced by tracking agent spending and managing approval workflows within defined organizational constraints. This ensures tasks are completed efficiently while adhering to company policies and budget limits.

What is the best way to track the status of tasks assigned to AI agents?▼

Task status tracking is managed via a control plane API that supports heartbeat-driven execution and detailed audit trails. This allows you to monitor assignments, track progress, and update task statuses in real-time.

Do I need an approval workflow to manage AI agent task delegation?▼

Approval workflows are supported to manage AI agent task delegation and ensure adherence to company governance. You can use these workflows to review and authorize agent actions before tasks are executed.

Can I audit the actions performed by AI agents during workflow orchestration?▼

Auditing AI agent actions is supported through detailed audit trails that record execution history and task updates. This provides transparency and accountability for all operations performed during workflow orchestration.

When should I use a dedicated orchestration layer for my AI agents?▼

A dedicated orchestration layer is needed when a complex project requires multiple specialized AI agents working together. It ensures seamless task assignment, progress tracking, and compliance with governance and budget constraints.

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