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CornFedKratos
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aidlc-agent-team

Define role ownership and collaboration protocols for a six-chief AI development team.

Updated Apr 11, 2026
Search Tags:#workflow#orchestration#governance#ai-dlc#collision-detection#kb-management#team-roles
One-click install
npx skills add https://github.com/CornFedKratos/s3-aidlc --skill aidlc-agent-team
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: aidlc-agent-team
Source: https://github.com/CornFedKratos/s3-aidlc/tree/main/plugins/s3-aidlc/skills/aidlc-agent-team
Command: npx skills add https://github.com/CornFedKratos/s3-aidlc --skill aidlc-agent-team

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Defines the operating model for a multi-role AI development team, providing clear ownership, guardrails, and collaboration protocols so initiatives progress without cross-role conflicts or duplicative work.

Core Features & Use Cases

  • Six-chief governance model (CPO, CTO, CQO, CDO, CIO, CSO) with explicit ownership and decision rights.
  • Execution agents with a no-overlap invariant and collision-detection workflow.
  • Invocation protocol and human orchestrator approval steps to coordinate parallel work.
  • Comprehensive feature flow from design brief to merged code and knowledge dumps.
  • KB write responsibilities mapped to each role to ensure timely documentation.
  • Onboarding protocol to align agents with current project context before work starts.

Quick Start

Spin up the AI-DLC agent team for a new project and assign the six-chief roles to orchestrate the workflow.

Frequently Asked Questions about aidlc-agent-team

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

FAQPage Schema
How do I set up governance and role ownership for an AI agent team?▼

To set up AI agent team governance, use a six-chief operating model with explicit decision rights, assigning ownership across CPO, CTO, and CQO roles to prevent cross-role conflicts and duplicative work.

What is the AI-DLC workflow orchestration model for complex system builds?▼

The AI-DLC workflow orchestration model is a multi-role governance structure featuring six chiefs and execution agents, designed to align the playing field and clarify ownership for complex system builds.

How do I prevent task overlap and collisions when orchestrating parallel AI agents?▼

Prevent parallel AI agent collisions by enforcing a no-overlap invariant and utilizing a collision-detection workflow alongside an invocation protocol requiring human orchestrator approval steps.

Can I use this team operating model for onboarding new agents to an existing project?▼

Yes, you can use this operating model for onboarding scenarios, as it includes a specific onboarding protocol to align execution agents with the current project context before work starts.

How are knowledge base write responsibilities managed across AI team roles?▼

Knowledge base write responsibilities are explicitly mapped to each role, ensuring timely documentation and knowledge capture throughout the team's lifecycle from design brief to merged code.

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