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github/ai-team-orchestration

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ai-team-orchestration

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 distinct agent voices, recovering a project workflow, or planning sprints.

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v1.0Saved Jun 26, 2026

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.

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. 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. 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 playthrough.
File bugs as GitHub Issues. Write docs/qa/sprint-N-signoff.md.

Context Recovery

When a chat gets long (>100 messages), save state and start fresh:

Before closing:

  1. Update docs/sprint-N/progress.md with current status
  2. Update PROJECT_BRIEF.md sections 7+8
  3. Write docs/sprint-N/done.md

Cold start prompt:

Read PROJECT_BRIEF.md and docs/sprint-N/progress.md.
Continue from where it left off.

Anti-Patterns

See anti-patterns reference for the full list. Top 5:

Don't Do Instead
Rebase feature branches Merge (rebase loses commits)
Producer writes code Producer only plans, merges, files issues
Batch "fix everything" commits One commit per fix with issue reference
Vague brainstorm prompts Name each agent with distinct perspective
Keep bugs only in chat File GitHub Issues (chat context dies)

Tips for Better Results

  • "Take your time, do it right" in prompts produces better output than rushing
  • Test before merge — you playtest, file issues, dev fixes, then merge
  • Run team consiliums before major sprints — each agent reviews the plan from their perspective
  • Save lessons to memory after every milestone
Files5
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Overall Score

82/100

Grade

B

Good

Safety

85

Quality

82

Clarity

85

Completeness

76

Summary

This skill teaches a developer how to structure and coordinate multiple AI agents as a cohesive software development team across separate chats. It provides role definitions, chat architecture patterns, project bootstrapping steps, sprint execution workflows, and documentation templates to enable context survival across conversation boundaries. The skill emphasizes separation of concerns, explicit cross-chat handoff protocols, and anti-pattern guidance to prevent common multi-agent coordination failures.

Detected Capabilities

File reading (PROJECT_BRIEF.md, sprint plans, progress trackers)Structured documentation generation (plans, progress, done files)Git workflow guidance (branching, merging, PR creation)Team coordination and role delegationContext persistence across chat boundariesIssue tracking integration (GitHub Issues reference)Documentation templating and format specification

Trigger Keywords

Phrases that MCP clients use to match this skill to user intent.

multi-agent team setupsprint planning with aicoordinate parallel agentsai brainstorm formatcross-chat context recoveryagent role assignmentmulti-sprint orchestration

Use Cases

  • Bootstrap a multi-agent dev team for a new software project
  • Coordinate parallel AI development, QA, and DevOps teams across separate chats
  • Create sprint plans that survive context overflow by persisting state to files
  • Run brainstorms with distinct agent personas to surface genuine debate and avoid groupthink
  • Recover from context overflow mid-sprint using saved progress trackers and brief templates
  • Establish cross-team handoff protocols so work doesn't get duplicated or overwritten

Quality Notes

  • Comprehensive anti-patterns section documents lessons learned from real multi-agent projects, providing clear 'don't/do instead' guidance with justifications
  • Well-structured templates (project brief, sprint plan, brainstorm format) are provided as reference files, enabling agents to follow consistent patterns
  • Explicit cross-chat handoff protocol (Section 12-14) addresses the core challenge of context survival, a critical problem for extended projects
  • Team roles are clearly defined with names, responsibilities, and focus areas, reducing ambiguity in agent assignment
  • ASCII architecture diagrams and folder structure examples make abstract concepts concrete and actionable
  • Brainstorm format design (named personas with distinct tendencies, explicit disagreement requirements) is sophisticated and addresses real groupthink risks
  • Progress tracker and recovery prompt patterns enable agents to resume mid-sprint without losing context
  • Security considerations are documented but minimal — assumes dev teams manage secrets via env vars without deep guidance
  • Some templates are abbreviated (e.g., QA sign-off) and could benefit from more elaborate examples
  • Repo structure assumes GitHub and standard git workflows; no guidance for other VCS or organizational patterns
Model: claude-haiku-4-5-20251001Analyzed: Jun 26, 2026

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