todo-manager

Name: todo-manager
Availability: InStock
Author: Joel

Automate AI agent task lifecycle management with changelog and error tracking.

1|Updated Feb 21, 2026

Search Tags:#automation #changelog #verification #task-management #agent-workflows #scheduler #git-ops

Ready to run

npx skills add https://github.com/joelmeaders/agent-skill-builder --skill todo-manager-joelmeaders

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: todo-manager
Source: https://github.com/joelmeaders/agent-skill-builder/tree/main/todo-manager
Command: npx skills add https://github.com/joelmeaders/agent-skill-builder --skill todo-manager-joelmeaders

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

Automates the end-to-end management of AI agent tasks—creating, tracking, executing, and verifying work while preserving history, so teams can scale autonomous workflows without manual micromanagement.

Core Features & Use Cases

End-to-end task lifecycle: not started, in progress, complete, and verified statuses, with automatic changelog updates.
Autonomous execution: WORK_MODE delegates subtasks to sub-agents and progresses tasks without user input, with VERIFY_MODE for quality.
Scheduling and persistence: integrates with a scheduler for recurring sessions and keeps a persistent record that is never deleted.
Use Case: Manage a multi-task project where tasks must be created, updated, and verified across multiple sessions while maintaining audit trails.

Quick Start

Load the todo-manager skill and start by creating a .todo.md with initial tasks to begin automated task execution.

Frequently Asked Questions about todo-manager

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

FAQPage Schema

How do I automate AI agent task management from creation to verification?▼

Autonomous AI agent task management is automated by orchestrating the full lifecycle from creation to verification while preserving history. The workflow cycles through INIT, WORK, VERIFY, CORRECTION, and ERROR modes to progress tasks without manual micromanagement.

What is the best way to track long-running project tasks across multiple sessions?▼

Tracking long-running project tasks across multiple sessions requires a persistent record that maintains status updates and audit trails. Integrating a scheduler handles recurring sessions, while a changelog keeps a continuous history of task transitions that is never deleted.

How do I start an automated task workflow for my project?▼

To start an automated task workflow, load the task management skill and create a .todo.md file with your initial tasks. This initializes the automated execution process, allowing the system to begin progressing tasks through their lifecycle.

Can I delegate subtasks to sub-agents without manual user input?▼

Subtasks can be delegated to sub-agents autonomously using WORK_MODE. This mode progresses tasks without requiring user input, while VERIFY_MODE subsequently checks the quality of the completed work before finalizing the task status.

Does autonomous task management support atomic commits and error tracking?▼

Autonomous task management enforces safe operation with strict task lifecycle rules and atomic commits. It maintains persistent error tracking alongside an automatic changelog to ensure safe execution and a complete audit trail for project workflows.

When should I not use an autonomous task lifecycle for my project?▼

An autonomous task lifecycle is not suited for workflows requiring manual micromanagement or those lacking recurring execution needs. It is designed for scaling autonomous agent workflows and long-running experiments rather than simple, single-session task lists.