
Agentic Scrum
- 8 repo stars
- Updated July 7, 2026
- atusy/agentic-scrum
A plugin that facilitates Agile Scrum project management
About
agentic-scrum is a Claude Code skill in the AI & Agent Building category. A plugin that facilitates Agile Scrum project management
- agentic-scrum
- AI & Agent Building
- AI-coding skill
Agentic Scrum by the numbers
- Data as of Jul 30, 2026 (Skillselion catalog sync)
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| repo stars | ★ 8 |
|---|---|
| Last updated | July 7, 2026 |
| Repository | atusy/agentic-scrum ↗ |
What it does
A plugin that facilitates Agile Scrum project management
README.md
🚧WIP🚧 This project is under active development. Expect breaking changes.
🤖 Agentic Scrum
Scrum optimized for AI agents for stable autonomous software development.
🚀 Getting Started
Optional dependencies: deno
For Claude Code Users
Use following prompts in Claude Code to add and install the plugin:
/plugin marketplace add https://github.com/atusy/agentic-scrum/plugin install agentic-scrum@agentic-scrumRun
/scrum:initin your project to createscrum.tsPrompt Claude Code to add a TODO in
scrum.ts(i.e., PBI)Run
/scrum:goto start autonomous development
💡 Why Agentic Scrum?
Stable autonomous software development requires a structured process:
- 🧩 Incremental decomposition — Break problems down vertically (end-to-end slices) then horizontally (layers) for reliable resolution
- 🔍 Continuous quality inspection — Verify completed functionality meets standards
- 🔄 Adaptive prompting — Evolve instructions based on what works
Scrum provides exactly this structure, and AI agents understand it well.
Why adapt Scrum? Traditional Scrum assumes human limitations: time-boxed sprints, sprint point estimation, and synchronous ceremonies. AI agents don't have these constraints.
Agentic Scrum adapts the framework:
| Traditional Scrum | Agentic Scrum |
|---|---|
| 📅 Sprint = 2-4 weeks | ⚡ Sprint = 1 PBI (any duration) |
| 📊 Velocity planning | 🚫 No estimation needed |
| 👥 Team ceremonies | 🤖 Autonomous coordination |
| 📋 Sprint backlog items | 🎯 Single focused goal |
The result: continuous autonomous iteration with all the benefits of Scrum's inspect-and-adapt loop.
🏗️ Core Concepts
📄 Single Source of Truth: scrum.ts
All Scrum artifacts live in one TypeScript file that AI agents read and write:
const scrum: ScrumDashboard = {
product_goal: { statement: "...", success_metrics: [...] },
product_backlog: [...], // Ordered by priority
sprint: { goal: "...", subtasks: [...] },
definition_of_done: { checks: [...] },
completed: [...], // Sprint history
retrospectives: [...] // Process improvements
};
🎭 AI Agent Roles
┌─────────────────────────────────────────────────────────────┐
│ 🧭 SCRUM MASTER │
│ Facilitates • Enforces • Removes Impediments │
└─────────────────────────────────────────────────────────────┘
│ │
▼ ▼
┌───────────────────┐ ┌───────────────────────┐
│ 📋 PRODUCT OWNER │ │ 💻 DEVELOPER │
│ │ ready PBI │ │
│ • Product Goal │ ───────────────▶│ • TDD Cycle │
│ • Backlog Order │ │ • RED → GREEN → │
│ • Acceptance │ ◀───────────────│ REFACTOR │
│ │ done PBI │ │
└───────────────────┘ └───────────────────────┘
🔄 Status Lifecycles
PBI: draft → refining → ready → done
Sprint: planning → in_progress → review → done
Subtask: pending → 🔴 red → 🟢 green → 🔧 refactoring → ✅ completed
│ │ │
(test) (commit) (commit×N)
📌 Key Principles
- ⚡ 1 Sprint = 1 PBI — Maximize iteration speed
- 📊 Order = Priority — Array position determines importance
- 🗂️ Git is History — No timestamps in dashboard
- 🔀 Behavioral ↔ Structural — Separate commits for features vs refactoring
- ✅ Commits at GREEN only — Never commit failing tests
📜 License
MIT © 2025 atusy