behavioral-modes

Name: behavioral-modes
Availability: InStock
Author: skeletorflet

Coordinate AI behavior by switching among predefined operating modes.

7|1|Updated Mar 28, 2026

Search Tags:#workflow #multi-agent #mode-detection #ai-behavior #development-automation #adaptive-modes

Ready to run

npx skills add https://github.com/skeletorflet/opencode-kit --skill behavioral-modes-skeletorflet

💬 Prompt for ChatGPT / Claude Chat▼

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

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Behavioral modes provide structured strategies to tailor AI behavior to the current task, improving clarity, efficiency, and safety.

Core Features & Use Cases

Brainstorm mode for ideation and exploration of multiple approaches
Implement mode for code development and feature delivery with concise output
Debug mode for systematic troubleshooting and root-cause analysis
Review mode for formal code and architecture critique
Teach mode for explanations, onboarding, and knowledge transfer
Ship mode for deployment readiness and release polish

Quick Start

Switch to BRAINSTORM mode to generate multiple solution ideas for 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 software development tasks?▼

To switch AI behavior modes for software development, coordinate tasks by selecting from predefined operating modes like brainstorm, implement, debug, review, teach, or ship. Each mode enforces specific output formats, safety constraints, and structured transitions tailored to that particular development phase.

What is multi-agent mode detection for adaptive AI workflows?▼

Multi-agent mode detection for adaptive AI workflows is the process of automatically coordinating AI behavior by switching among predefined operating modes. This enforces mode-specific safety constraints and structured transitions, ensuring task-appropriate behavior for ideation, coding, debugging, review, teaching, and deployment.

Can I use adaptive AI modes for both code debugging and architecture review?▼

Yes, you can use adaptive AI modes for both code debugging and architecture review. The system includes a dedicated Debug mode for systematic troubleshooting and root-cause analysis, alongside a Review mode specifically designed for formal code and architecture critique.

What's the best way to structure AI output for software deployment readiness?▼

The best way to structure AI output for software deployment readiness is using the dedicated Ship mode. This predefined operating mode enforces mode-specific output formats and safety constraints to ensure deployment readiness and release polish for your software project.

When do I need structured AI behavioral modes for development automation?▼

You need structured AI behavioral modes for development automation when tailoring AI behavior to current tasks to improve clarity, efficiency, and safety. Applicable scenarios include ideation, feature delivery, systematic troubleshooting, formal critique, knowledge transfer, and release polishing in software projects.

Does this multi-agent mode system require external dependencies to function?▼

No, the multi-agent mode system does not require external dependencies to function. It operates independently by enforcing mode-specific output formats, safety constraints, and structured transitions defined internally through frontmatter and descriptions to coordinate adaptive AI behavior across software tasks.