behavioral-modes

Define and switch AI behavior modes for different task types.

Updated Dec 22, 2025

Search Tags:#implementation #debug #behavior #brainstorm #mode-switching #ai-mode

Ready to run

npx skills add https://github.com/alaminmain/DoorAuthServer --skill behavioral-modes-alaminmain

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: behavioral-modes
Source: https://github.com/alaminmain/DoorAuthServer/tree/main/.agent/skills/behavioral-modes
Command: npx skills add https://github.com/alaminmain/DoorAuthServer --skill behavioral-modes-alaminmain

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill provides a structured approach to adapt AI behavior based on task type by defining a library of modes (brainstorm, implement, debug, review, teach, ship, orchestrate) and a consistent interaction pattern.

Core Features & Use Cases

Mode Library: Brainstorm, Implement, Debug, Review, Teach, Ship, Orchestrate
Contextual Reasoning: Modes adjust questioning style, prioritization, and output formats to fit the task
Use Case: Plan a feature in BRAINSTORM, then IMPLEMENT the solution and DEBUG any issues before SHIPping it

Quick Start

Invoke a mode explicitly, for example: "Switch to IMPLEMENT mode and generate production-ready code."

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 software engineering tasks?▼

AI behavior modes switch by invoking a specific mode explicitly, such as instructing the system to switch to IMPLEMENT mode. Mode definitions in the frontmatter guide mode switching and format responses for tasks like brainstorming or debugging.

What is the best way to structure an AI workflow from planning to shipping code?▼

The best way to structure an AI workflow is to use the mode library sequentially: plan a feature in BRAINSTORM mode, IMPLEMENT the solution, DEBUG any issues, and finally SHIP the code. This ensures contextual reasoning at each stage.

Can I adapt AI response formatting to fit specific project stages?▼

Yes, you can adapt AI response formatting using mode definitions. Output conventions defined in the frontmatter adjust questioning style and prioritization, tailoring the response format to fit the specific project stage or task type.

Does this mode-switching approach work for both code review and teaching?▼

Yes, this mode-switching approach works for both code review and teaching. The mode library includes distinct REVIEW and TEACH modes, which adjust the AI's contextual reasoning and output conventions to suit each specific task type.

Do I need any dependencies to use AI mode switching across projects?▼

No, you do not need any dependencies to use AI mode switching. The skill operates independently without external components, relying solely on frontmatter definitions to guide adaptive behavior across various software engineering projects.

Why should I use guided modes instead of standard AI prompts for implementation?▼

Guided modes provide structured mode switching and consistent interaction patterns that standard prompts lack. Defining a library of modes like IMPLEMENT ensures the AI applies contextual reasoning and appropriate output conventions for the specific task.