
AI Team Orchestration
OfficialFreeStreamline multi-agent development workflows.
Free · Opens the source repo
What AI Team Orchestration does
AI Team Orchestration is designed to facilitate the management of a lightweight multi-agent development team. It provides a structured approach for initiating or adopting projects, planning tasks, coordinating implementation, and performing optional quality assurance. This skill is particularly useful for teams that want to leverage distinct perspectives in their development process, ensuring that all aspects of a project are thoroughly considered and executed.
The skill utilizes three primary agents: @ai-team-producer, @ai-team-dev, and @ai-team-qa. Each agent has a specific role in the development workflow. The producer clarifies the project scope, coordinates tasks, and merges contributions. The development agent focuses on implementation, testing, and preparing pull requests, while the QA agent independently tests the software to ensure quality. This division of labor helps maintain clarity and efficiency throughout the development cycle.
The default workflow is straightforward: plan, implement, test (with optional review or QA), merge, and update the project state. Users are encouraged to keep the workflow proportional, adapting the level of planning and review based on the complexity and risk associated with each task. This flexibility allows teams to avoid unnecessary overhead while ensuring that critical changes are adequately vetted.
In addition to its core functionality, the skill includes templates for project briefs and sprint planning, which help teams document their progress and decisions. The brainstorm format encourages collaborative decision-making, allowing multiple perspectives to be considered for product or architectural choices. Overall, AI Team Orchestration is a valuable tool for development teams looking to enhance their collaboration and streamline their workflows.
When to use it
Use this skill when starting a new project or adopting an existing one, especially when coordinating multiple agents is required.
When not to use it
This skill may not be suitable for very small teams or projects where a single developer can manage all tasks without the need for orchestration.
What you can build with it
Starting a New Project
Utilize the skill to bootstrap a new project by defining the scope and creating a project brief.
Coordinating Team Efforts
Employ the skill to manage tasks among multiple agents, ensuring clear communication and efficient workflow.
Implementing Complex Features
Use the skill to plan and execute complex features that require careful consideration and testing.
How to install AI Team Orchestration
View source1. Install with the skills CLI
npx skills add github/awesome-copilot/ai-team-orchestration --agent claude-code2. Or install it manually
Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.
Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs
Inside SKILL.md
Written by githubAI Team Orchestration
Use three stable agents:
| Agent | Purpose |
|---|---|
@ai-team-producer | Clarify scope, plan proportionately, coordinate, and merge |
@ai-team-dev | Implement, test, self-review, and prepare the pull request |
@ai-team-qa | Independently test behavior when dedicated QA is useful |
Nova, Sage, and Milo are perspectives inside the Dev agent, not mandatory project layers.
Default Workflow
Plan -> Implement -> Test -> optional review or QA -> Merge -> update project state
Keep the workflow proportional:
- Skip formal planning for small, obvious changes.
- Use a short plan for multi-step or cross-cutting work.
- Add independent review or QA when risk, uncertainty, or repository policy justifies it.
- Let branch protection, required checks, permissions, and merge queues enforce repository merge policy.
Start or Adopt a Project
- Read existing repository instructions and documentation.
- Discover the actual stack, architecture, commands, deployment model, and risks.
- Create or update
PROJECT_BRIEF.mdonly when durable cross-session context is useful. Start from the project brief template and omit irrelevant sections. - For substantial work, create a concise plan from the sprint plan template.
- Use a separate branch or clone when parallel sessions could conflict, following the repository's own Git policy.
Execute
Producer
- Define the outcome, constraints, acceptance criteria, and explicit exclusions.
- Choose review and QA based on risk rather than ceremony.
- Keep durable project state concise and current.
Dev
- Follow repository conventions and implement the smallest complete solution.
- Run relevant checks and inspect the final diff.
- Open or update the pull request with summary, verification, and limitations.
QA
- Use only when dedicated behavioral verification adds value.
- Test the requested change and important regressions.
- Report reproducible findings and verify fixes.
Brainstorms
Use the brainstorm format for product or architecture decisions that benefit from competing perspectives. For ordinary implementation choices, let Dev decide using repository conventions.
Context Recovery
Before ending a long or interrupted session:
- Update the active plan or progress note if one exists.
- Record material decisions, blockers, and the next action in repository context.
- Use a cold-start prompt such as:
Read the repository instructions, then read whichever sources exist for this
work: the active issue or request, PROJECT_BRIEF.md, and the active plan or
progress note.
Continue from the recorded next action.
Tool and Model Inheritance
The bundled agents intentionally omit tools and model frontmatter:
- available built-in, MCP, and extension tools remain usable;
- developers keep control of model selection;
- role boundaries are defined by instructions and normal trust, permission, authentication, and approval controls.
If the environment exposes too many tools, deselect irrelevant tools or MCP servers, or use VS Code virtual-tool management. Do not add a machine-specific plugin allowlist.
Principles
- Prefer working software and clear handoffs over process artifacts.
- Follow repository policy instead of embedding universal Git commands.
- Preserve unknown work and ask before destructive or privileged actions.
- Keep bugs and important decisions in durable project systems, not only chat.
- See anti-patterns for concise lessons.
Frequently asked questions about AI Team Orchestration
Similar skills
Agent Skill Stack
Assemble compatible AI Agent Skills for workflows.
Advisor Orchestrator Worker
Efficiently manage complex tasks with multiple AI models.
Agent Orchestrator
Automate multi-agent workflows with zero manual intervention.
Agent Governance
Implement safety and trust controls for AI agents.
Microsoft Foundry
End-to-end management for Microsoft Foundry agents.
Arbor Optimization
Autonomous iterative improvement for artifacts using HTR.
