goal-mode

Maintain a single active objective across turns with automatic scheduling.

22|2|Updated Feb 28, 2026
One-click install
npx skills add https://github.com/patleeman/neon-pilot --skill goal-mode
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: goal-mode
Source: https://github.com/patleeman/neon-pilot/tree/main/extensions/system-auto-mode/skills/auto-mode
Command: npx skills add https://github.com/patleeman/neon-pilot --skill goal-mode

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Goal mode enables sustained objectives across multiple turns, so the agent can own a task and keep progressing without waiting for user input.

Core Features & Use Cases

  • Maintains a single active objective and auto-schedules subsequent turns.
  • Supports updating, pausing, resuming, and completing the objective.
  • Use case: When a long-running task needs continuous progress, such as research or data collection, until it is achieved.

Quick Start

Start goal-mode with an objective and let it continue across turns until completion.

Frequently Asked Questions about goal-mode

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

FAQPage Schema
How do I automate long-running AI agent tasks across multiple turns?

Automate long-running AI agent tasks by maintaining a single active objective that schedules subsequent turns automatically, enabling continuous progress for research, data collection, and iterative work without waiting for user input.

Can an AI agent resume a paused objective and continue task execution?

Yes, an AI agent can resume a paused objective. The task management system supports create, pause, resume, and complete controls, allowing you to halt iterative work and continue automated progress exactly where it left off.

What is goal-mode for multi-turn workflow automation?

Goal-mode is a multi-turn workflow automation approach that coordinates ongoing objectives by maintaining a single active goal, automatically scheduling next turns with built-in safeguards to prevent infinite loops during task execution.

Does automating multi-turn objectives risk infinite loops in AI agents?

Automating multi-turn objectives includes safeguards to prevent infinite loops. The system manages automatic scheduling of subsequent turns while maintaining a single active objective, ensuring iterative work progresses and completes safely.

What's the best way to track iterative project work with an AI agent?

Track iterative project work by assigning a sustained objective to the AI agent. The agent owns the long-running task, maintains the active goal across turns, and auto-schedules progress until the objective is achieved.

Why does my AI agent stop working between turns on long research tasks?

AI agents stop between turns because they lack a sustained objective mechanism. By maintaining a single active goal and auto-scheduling subsequent turns, the agent can own long-running research tasks and keep progressing without user input.