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behavioral-modes

Define AI operating modes with YAML frontmatter for task-specific behavior.

Updated Feb 19, 2026
Search Tags:#workflow#multi-agent#orchestration#ai-safety#ai-modes#behavior-switching#task-based-control
One-click install
npx skills add https://github.com/jonnathan-ls/ai-context-kit --skill behavioral-modes-jonnathan-ls
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: behavioral-modes
Source: https://github.com/jonnathan-ls/ai-context-kit/tree/main/skills/behavioral-modes
Command: npx skills add https://github.com/jonnathan-ls/ai-context-kit --skill behavioral-modes-jonnathan-ls

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

The Behavioral Modes skill provides a structured framework for dynamically adapting AI behavior to the current task by selecting from predefined operating modes (BRAINSTORM, IMPLEMENT, DEBUG, REVIEW, TEACH, SHIP, ORCHESTRATE). This helps ensure the AI uses the appropriate strategy, communication style, and prioritization to improve outcomes.

Core Features & Use Cases

  • Mode catalog: seven named modes with explicit behavioral guidance for ideation, coding, debugging, analysis, explanation, production delivery, and multi-agent orchestration.
  • Explicit switching: allow users to switch modes for a session or task, ensuring predictable AI behavior and reduced cognitive load.
  • Collaboration patterns: supports multi-agent planning and cyclic role transitions for complex tasks (PLAN-EXECUTE-CRITIC).
  • Use Case: switch to IMPLEMENT mode when building a feature, then to REVIEW for code quality, and to TEACH to explain the rationale to a stakeholder.

Quick Start

Switch to BRAINSTORM mode for ideation before starting the task.

Frequently Asked Questions about behavioral-modes

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

FAQPage Schema
How do I switch AI behavior modes for different tasks in a workflow?▼

You can switch AI behavior modes by selecting from predefined operating states like BRAINSTORM, IMPLEMENT, or REVIEW, which dynamically adjusts the AI's strategy, communication style, and prioritization to match the specific task.

What is multi-agent orchestration and how do discrete operating modes control it?▼

Multi-agent orchestration coordinates multiple AI agents using discrete operating modes to govern cyclic role transitions like PLAN-EXECUTE-CRITIC, ensuring predictable and safe collaborative behavior for complex tasks.

Can I use behavior switching for AI safety and predictable task execution?▼

Yes, behavior switching enforces AI safety by applying mode-specific guidance that constrains the AI's problem-solving approach, ensuring predictable and controlled execution for each distinct task.

How do I define a framework of operating modes for AI task-based control?▼

You define a framework of operating modes by providing a YAML frontmatter with a name and description, then applying explicit behavioral guidance for each mode to control task-based execution.

What's the best way to manage AI communication style during code review versus implementation?▼

Switching to IMPLEMENT mode prioritizes feature building, while REVIEW mode adjusts communication style and strategy to focus on code quality analysis, ensuring appropriate behavior for each phase.

Does multi-agent collaboration require explicit mode switching for role transitions?▼

Yes, multi-agent collaboration relies on explicit mode switching to manage cyclic role transitions, ensuring each agent operates within the correct behavioral framework for safe and predictable outcomes.

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