Ai-Team-Orchestration
Ai-Team-Orchestration是一款code方向的AI技能,核心价值是Bootstrap and run a multi-agent AI development team,可用于解决开发者在code领域的实际问题,帮助用户提升效率、自动化重复任务或优化工作流。
Bootstrap and run a multi-agent AI development team. Use when: starting a new software project with AI agents, setting up parallel dev/QA teams, creating sprint plans, writing brainstorm prompts with
mkdir -p ./skills/ai-team-orchestration && curl -sfL https://raw.githubusercontent.com/github/awesome-copilot/main/skills/ai-team-orchestration/SKILL.md -o ./skills/ai-team-orchestration/SKILL.md Run in terminal / PowerShell. Requires curl (Unix) or PowerShell 5+ (Windows).
Skill Content
# AI Team Orchestration
When to Use
- Starting a new project that needs planning, development, testing, and deployment
- Setting up parallel AI agent teams (dev, QA, DevOps)
- Writing brainstorm prompts that produce real debate (not generic output)
- Creating sprint plans with cross-chat context survival
- Recovering from context overflow mid-sprint
Team Roles
| Agent | Name | Role | Focus |
|-------|------|------|-------|
| Producer | **Remy** | Sprint planning, coordination, merging PRs | Scope control, handoffs, issue triage |
| Product Designer | **Kira** | UX, mechanics, user experience | Fun factor, user flows, feature design |
| Visual/Art Director | **Milo** | CSS, animations, visual identity | Design system, polish, accessibility |
| Frontend Engineer | **Nova** | UI framework, state management, components | React/Vue/Svelte, client-side logic |
| Backend Engineer | **Sage** | API, database, auth, security | Server-side logic, infrastructure |
| DevOps Engineer | **Dash** | CI/CD, cloud deployment, pipelines | GitHub Actions, Azure/AWS/GCP |
| QA Engineer | **Ivy** | E2E tests, automation, playtesting | Playwright/Cypress, bug filing, sign-off |
Customize names and roles for your project. Not every project needs all roles.
Chat Architecture
The human (CEO) is the message bus between parallel chats:
┌────────────────────────────────────────┐
│ @ai-team-producer — Plans, merges │
│ NEVER writes code │
└────────────────┬───────────────────────┘
│ Human carries messages
┌──────────┼──────────┐
▼ ▼ ▼
┌──────────┐ ┌────────┐ ┌────────┐
│@ai-team │ │@ai-team│ │DevOps │
│-dev │ │-qa │ │(on │
│ │ │ │ │demand) │
│ Nova │ │ Ivy │ │ │
│ Sage │ │ │ │ │
│ Milo │ │ │ │ │
│ │ │feature/│ │feature/│
│ feature/ │ │qa-N │ │devops-N│
│ sprint-N │ └────────┘ └────────┘
└──────────┘Each team works in a **separate VS Code window** with its own clone:
git clone <repo> project-dev # Dev team
git clone <repo> project-qa # QA
git clone <repo> project-devops # DevOps (only when needed)Project Bootstrap
1. Create PROJECT_BRIEF.md
The single source of truth across all chats. See the [project brief template](./references/project-brief-template.md).
**Required sections (do not abbreviate):**
1. Project Overview
2. Concept / Product Description
3. Tech Stack
4. Architecture (ASCII diagram)
5. Key Files Map
6. Team Roles
7. Sprint Status (updated every sprint)
8. Current State (rewritten every sprint)
9. Security Rules
10. How to Run Locally
11. How to Deploy
12. **Cross-Chat Handoff Protocol** — how context survives between chats
13. **Bug & Fix Tracking** — GitHub Issues as single source of truth
14. **Multi-Repo Setup** — separate clones, branch strategy, merge rules
2. Run a Brainstorm
See the [brainstorm format](./references/brainstorm-format.md). Key: name each agent explicitly with distinct personality and perspective. Require at least 2 genuine disagreements to prevent groupthink.
3. Create Sprint Plans
See the [sprint plan template](./references/sprint-plan-template.md). Every sprint gets:
- `docs/sprint-N/plan.md` — prioritized tasks, success criteria
- `docs/sprint-N/progress.md` — live tracker, enables recovery
- `docs/sprint-N/done.md` — handoff doc written at sprint end
4. Execute Sprints
Read PROJECT_BRIEF.md, then read docs/sprint-N/plan.md. Execute Sprint N.
First: git pull origin main && git checkout -b feature/sprint-N
Close GitHub Issues in commits: "fix: description (Fixes #NN)"
Update docs/sprint-N/progress.md after each phase.
When done, push and create PR: git push origin feature/sprint-N
Follow Sections 12-14 of PROJECT_BRIEF.md.5. QA Sign-off
After dev merges, QA does a full playthrough:
Read PROJECT_BRIEF.md. You are Ivy (QA).
Sprint N is merged to main. Do full playth🎯 Best For
- Claude users
- GitHub Copilot users
- Software engineers
- Development teams
- Tech leads
💡 Use Cases
- Code quality improvement
- Best practice enforcement
📖 How to Use This Skill
- 1
Install the Skill
Copy the install command from the Terminal tab and run it. The SKILL.md file downloads to your local skills directory.
- 2
Load into Your AI Assistant
Open Claude or GitHub Copilot and reference the skill. Paste the SKILL.md content or use the system prompt tab.
- 3
Apply Ai-Team-Orchestration to Your Work
Open your project in the AI assistant and ask it to apply the skill. Start with a small module to verify the output quality.
- 4
Review and Refine
Review AI suggestions before committing. Run tests, check for regressions, and iterate on the skill output.
❓ Frequently Asked Questions
Is Ai-Team-Orchestration compatible with Cursor and VS Code?
Yes — this skill works with any AI coding assistant including Cursor, VS Code with Copilot, and JetBrains IDEs.
Do I need specific dependencies for Ai-Team-Orchestration?
Check the install command and Works With section. Most code skills only require the AI assistant and your codebase.
How do I install Ai-Team-Orchestration?
Copy the install command from the Terminal tab and run it. The skill downloads to ./skills/ai-team-orchestration/SKILL.md, ready to use.
Can I customize this skill for my team?
Absolutely. Edit the SKILL.md file to add team-specific instructions, examples, or workflows.
⚠️ Common Mistakes to Avoid
Skipping validation
Always test AI-generated code changes, even for simple refactors.
Missing dependency updates
Check if the skill requires updated dependencies or new packages.