focus

Reset AI operational scope to the original user request when task drift occurs.

Updated Feb 25, 2026
One-click install
npx skills add https://github.com/LayerDynamics/Lore --skill focus-layerdynamics
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: focus
Source: https://github.com/LayerDynamics/Lore/tree/main/lore/skills/focus
Command: npx skills add https://github.com/LayerDynamics/Lore --skill focus-layerdynamics

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps refocus the AI when it drifts off-topic or starts working on tasks outside the original request, ensuring that the AI remains aligned with the user's primary objective.

Core Features & Use Cases

  • Scope Enforcement: Immediately brings the AI back to the original request.
  • Drift Correction: Addresses situations where the AI has deviated from the task.
  • Use Case: If you asked the AI to fix a bug in a specific file and it started refactoring unrelated code, you would use this skill to redirect it back to the bug fix.

Quick Start

Use the focus skill to reset the scope to the original request.

Frequently Asked Questions about focus

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

FAQPage Schema
How do I stop AI task drift when it starts refactoring unrelated code instead of fixing the requested bug?

To stop AI task drift, you need to reset the AI's operational scope to the original user request. This enforces task boundaries by identifying adjacent issues as TODOs without addressing them, then re-anchoring the AI to the primary objective.

What is AI scope enforcement and how does it correct task drift?

AI scope enforcement is the process of resetting the AI's operational scope when task drift is detected. It corrects deviations by surfacing adjacent issues as TODOs without addressing them, immediately re-anchoring the AI to your original request.

How do I keep AI aligned with my original request when it deviates to adjacent issues?

To keep AI aligned with your original request, enforce task boundaries by identifying adjacent issues and logging them as TODOs without addressing them. This immediately re-anchors the AI to the primary user objective.

Does AI scope enforcement work for general conversational drift or only code execution contexts?

AI scope enforcement applies to any conversational or execution context where the AI has deviated from the primary objective. It resets the operational scope regardless of the specific workflow or task type.

What is the best way to handle AI task drift without losing track of newly discovered adjacent issues?

The best way to handle AI task drift is to enforce task boundaries by identifying adjacent issues and surfacing them as TODOs without addressing them. This corrects the drift while preserving the new issues for later resolution.