Use when long-lived agents, project memories, system prompts, or playbooks are repeatedly summarized, rewritten, or optimized and risk losing domain detail, provenance, or execution learnings.
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Bootstraps and runs a multi-agent development team with roles (dev, QA, DevOps), parallel work, and sprint plans that survive context resets. Use when kicking off a project with parallel AI agents, writing brainstorm prompts that produce real debate, planning sprints across chats, or recovering from context overflow mid-sprint.
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安装前可以查看交给 AI 代理的指令内容。
Attribution: Sourced from github/awesome-copilot by GitHub Community, licensed MIT. Modified for this collection.
| 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.
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)
The single source of truth across all chats. See the project brief template.
Required sections (do not abbreviate):
See the brainstorm format. Key: name each agent explicitly with distinct personality and perspective. Require at least 2 genuine disagreements to prevent groupthink.
See the sprint plan template. Every sprint gets:
docs/sprint-N/plan.md — prioritized tasks, success criteriadocs/sprint-N/progress.md — live tracker, enables recoverydocs/sprint-N/done.md — handoff doc written at sprint endRead 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.
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.
When a chat gets long (>100 messages), save state and start fresh:
Before closing:
docs/sprint-N/progress.md with current statusPROJECT_BRIEF.md sections 7+8docs/sprint-N/done.mdCold start prompt:
Read PROJECT_BRIEF.md and docs/sprint-N/progress.md.
Continue from where it left off.
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) |
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Use when long-lived agents, project memories, system prompts, or playbooks are repeatedly summarized, rewritten, or optimized and risk losing domain detail, provenance, or execution learnings.
中文简介正在准备中。当前显示原文说明。
Use this skill when the user explicitly asks to map, document, or onboard into an existing codebase. Trigger for prompts like "map this codebase", "document this architecture", "onboard me to this repo", or "create codebase docs". Do not trigger for routine feature implementation, bug fixes, or narrow code edits unless the user asks for repository-level discovery.
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Adds educational comments to a code file so it becomes a learning resource, asking for the file (with a list of close matches) if none is given. Use when preparing code for learners, onboarding, or teaching.
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Write, debug, and optimize Adobe Illustrator automation scripts using ExtendScript (JavaScript/JSX). Use when creating or modifying scripts that manipulate documents, layers, paths, text frames, colors, symbols, artboards, or any Illustrator DOM objects. Covers the complete JavaScript object model, coordinate system, measurement units, export workflows, and scripting best practices.
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Patterns and techniques for adding governance, safety, and trust controls to AI agent systems. Use this skill when: - Building AI agents that call external tools (APIs, databases, file systems) - Implementing policy-based access controls for agent tool usage - Adding semantic intent classification to detect dangerous prompts - Creating trust scoring systems for multi-agent workflows - Building audit trails for agent actions and decisions - Enforcing rate limits, content filters, or tool restrictions on agents - Working with any agent framework (PydanticAI, CrewAI, OpenAI Agents, LangChain, AutoGen)
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Check any AI agent codebase against the OWASP Agentic Security Initiative (ASI) Top 10 risks. Use this skill when: - Evaluating an agent system's security posture before production deployment - Running a compliance check against OWASP ASI 2026 standards - Mapping existing security controls to the 10 agentic risks - Generating a compliance report for security review or audit - Comparing agent framework security features against the standard - Any request like "is my agent OWASP compliant?", "check ASI compliance", or "agentic security audit"
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