behavioral-modes

Switch AI behavior across six operational modes using prompt-based mode detection.

Updated Jan 27, 2026

Search Tags:#workflow #ai #debug #behavior #brainstorm #modes #mode-detection

Ready to run

npx skills add https://github.com/BrunoSantanaDeveloper/flyeelab-agent-kit --skill behavioral-modes-brunosantanadeveloper

💬 Prompt for ChatGPT / Claude Chat▼

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

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill provides a structured framework to adapt AI behavior by switching between distinct operating modes to match task type, reducing misaligned responses and improving efficiency.

Core Features & Use Cases

Six defined modes (Brainstorm, Implement, Debug, Review, Teach, Ship) with explicit behavioral guidelines to match different task phases.
A mode-detection mechanism that selects the appropriate mode from user prompts to streamline collaboration.
Clear output expectations and transition rules to maintain consistency across tasks.

Quick Start

Prompt the AI to activate Brainstorm mode for ideation and exploration.

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 workflow tasks?▼

Switch AI behavior modes by prompting the AI to activate a specific mode like Brainstorm or Debug. The mode-detection mechanism analyzes your prompt to automatically trigger the appropriate operational behavior and output format.

What are the available AI modes for software engineering workflows?▼

The available AI modes for software engineering workflows are Brainstorm, Implement, Debug, Review, Teach, and Ship. Each mode defines explicit behavioral guidelines, output expectations, and transition rules to match different task phases.

How does mode-detection work when switching between ideation and debugging?▼

Mode-detection works by analyzing user prompts to select the appropriate operational mode. When you transition from ideation to debugging, the mechanism automatically switches the AI's behavior and output format to align with the new task phase.

Can I use adaptive AI modes across implementation and deployment tasks?▼

Yes, you can use adaptive AI modes across implementation and deployment tasks. The framework coordinates AI behavior by switching between operational modes like Implement and Ship to reduce misaligned responses and improve efficiency.

Do I need external dependencies to coordinate AI behavior with operational modes?▼

No, you do not need external dependencies to coordinate AI behavior with operational modes. The framework operates independently, using a mode-detection mechanism to trigger behavioral changes based on your prompts without requiring additional components.