magic-spec 1.4.77

Magic Specification-Driven Development (SDD) Workflow

🪄 Magic Spec

📖 Description

The Specification-Driven Development (SDD) Operating System for AI Coding Agents.

Stop your AI from writing fragile code before it fully understands the problem. magic-spec installs a high-performance, structured pipeline — Thought → Spec → Task → Run → Code — directly into any project, regardless of the tech stack.

Whether you are a coding novice building your first application or a senior engineer architecting enterprise systems, Magic Spec brings maximum automation and professional rigor to your development process. It enforces a deterministic workflow that ensures your AI agent perfectly aligns with your vision before writing a single line of code.

The Core Concept

magic-spec is a set of markdown-based workflow instructions specifically designed for AI coding agents like Cursor, Windsurf, Claude, and Gemini. It acts as a project-level operating system that orchestrates agentic development.

Instead of chaotic prompt-engineering, Magic Spec provides a rigorous pipeline:

💡 Idea  →  📋 Specification  →  🗺️ Task & Plan  →  ⚡ Run  →  🚀 Code

Once initialized, your AI agent will automatically:

• Formulate a strong conceptual and technical specification.
• Build a phased implementation plan with hierarchical dependencies.
• Decompose the plan into prioritized, atomic, trackable tasks.
• Facilitate safe architectural brainstorming via Explore Mode.
• Analyze its own workflow and suggest improvements via Auto-Retrospectives.

What Gets Installed

After running the installer, your project directory will be augmented with the following structure:

root-project/
├── .agent/workflows/         # Slash commands wrapper (e.g., magic.spec, magic.task)
├── .magic/                   # The SDD Engine (workflow logic and scripts - read-only)
└── .design/                  # Your Project Design Workspace (INDEX.md, RULES.md, PLAN.md)

1. .magic/: Deploys the core SDD engine.
2. .agent/: Sets up workflows for your AI.
3. .design/: Initializes your project's workspace for Specifications, Rules, and Plans.
4. Onboarding: An interactive tutorial (magic.onboard) helps you and your AI get started smoothly.

[!TIP] Magic Workspaces: Magic Spec supports multiple, isolated design environments within a single repository (e.g., .design/engine/, .design/installers/). This allows you to manage fundamentally different project domains without specification overlap, while sharing a single core engine. See workspaces.md for details.

🧠 The SDD Philosophy

"No code without a spec. No spec without a plan."

Magic Spec is built around a single conviction: AI agents write better code when they are forced to think before they act. Left unconstrained, they jump straight to implementation — producing code that is fragile, misaligned, and expensive to refactor. Magic Spec installs a structured pipeline that makes this impossible.

Human-Minimal Engineering

The core design goal is to keep humans out of the loop as much as possible — without sacrificing control over what actually matters.

Once you describe what you want, the engine takes over:

• Specifications are drafted, reviewed, and promoted through their lifecycle automatically.
• Tasks are decomposed, prioritized, and assigned default values without prompting.
• Phases execute end-to-end: retrospective snapshots fire, changelogs are compiled, and context files are regenerated — all silently.
• The only moments requiring human input are deliberate gates: approving a spec before implementation begins, and signing off on an external release changelog.

Everything else is automated. The agent does the engineering. You approve the direction.

Two-Layer Specification Model

Every specification in Magic Spec belongs to one of two layers, and this separation is strictly enforced:

Layer 1 — Concept (layer: concept) Technology-agnostic. Describes what the system must do: business rules, domain invariants, data contracts, and behavioral requirements. A Layer 1 spec can be ported to any tech stack without modification. It is the source of truth for the entire implementation.

Layer 2 — Implementation (layer: implementation) Stack-specific. Describes how a Layer 1 concept is realized in a concrete technology (e.g., a Node.js REST API, a PostgreSQL schema, a React component). Every Layer 2 spec must declare its parent via Implements: {l1-file.md} and cannot reach RFC or Stable status until its parent is Stable.

This separation prevents a common failure mode in AI-assisted development: mixing "what we want" with "how we build it" in a single document, which leads to specs that are impossible to reuse, validate, or evolve independently.

Why this matters in practice: Imagine you built your backend on Node.js + PostgreSQL. Six months later, performance demands require a migration to Go + ScyllaDB. With a two-layer model, your Layer 1 specs — authentication rules, data contracts, business logic — remain completely intact. Only the Layer 2 specs are rewritten to reflect the new stack. Your AI agent gets a clean, unambiguous brief for the migration without you having to re-explain the entire domain from scratch.

Integrity by Design

The engine actively protects specification integrity throughout the project lifecycle:

• Quarantine Cascade: If a Layer 1 spec is destabilized (demoted from Stable), all dependent Layer 2 specs are automatically flagged and their tasks are blocked. The plan cannot proceed on a broken foundation.
• Registry Parity: Every spec that exists on disk must be registered in INDEX.md. Every registered spec must appear in the implementation plan or the backlog. Orphaned specs are treated as critical blockers.
• Rules Parity: If project conventions change (RULES.md), any existing task plan is flagged as stale. The agent will not execute tasks generated under outdated rules without an explicit sync.
• Engine Integrity: Core engine files are checksummed. Any untracked modification halts all workflows until the engine state is reconciled.

Self-Improving Feedback Loop

Magic Spec includes a built-in retrospective engine that runs automatically at two levels:

• Level 1 fires after every phase completes: captures a lightweight snapshot of spec health, task metrics, and signal status.
• Level 2 fires when the full plan is complete: performs a deep audit — identifying spec drift, blocked-task patterns, shadow logic, and workflow friction — then produces actionable recommendations.

These retrospectives feed back into the specification layer, closing the loop between what was planned and what was actually built.

🖼️ Visuals

The engine enforces a rigorous, unskippable pipeline: Idea → Specification → Task & Plan → Code. AI agents are prevented from jumping straight to coding. They must first formally specify the solution, then break it down into a concrete plan and tasks, and only then proceed to execution.

flowchart TB
    IDEA(["💡 Idea"])

    subgraph BOX ["Magic Spec"]
        direction TB

        SPEC["📋 Spec"]

        subgraph TASK ["🗺️ Task"]
            direction TB
            PLAN["📐 Plan"]
            TASKS["📌 Tasks"]
            PLAN --> TASKS
        end

        RUN["⚡ Run"]

        SPEC  --> PLAN
        TASKS --> RUN
    end

    CODE(["🚀 Code"])

    IDEA --> SPEC
    RUN  --> CODE

    style IDEA  fill:#1e1e2e,stroke:#89b4fa,color:#cdd6f4
    style CODE  fill:#1e1e2e,stroke:#a6e3a1,color:#cdd6f4

    style BOX   fill:#181825,stroke:#fab387,stroke-width:3px,color:#fab387

    style SPEC  fill:#1e1e2e,stroke:#89b4fa,color:#cdd6f4
    style RUN   fill:#1e1e2e,stroke:#89b4fa,color:#cdd6f4

    style TASK  fill:#11111b,stroke:#89b4fa,stroke-dasharray:5 5,color:#89b4fa
    style PLAN  fill:#1e1e2e,stroke:#45475a,stroke-dasharray:4 4,color:#cdd6f4
    style TASKS fill:#1e1e2e,stroke:#45475a,stroke-dasharray:4 4,color:#cdd6f4

⚙️ Requirements

Before installing Magic Spec, ensure you have one of the following available on your system:

Requirement	Details
Node.js	Version 16.x or higher (for npx method)
Python	Version 3.8 or higher (for uvx or pipx methods)
Git	Required for installing edge versions directly from GitHub
Terminal	tar utility (pre-installed on Windows/Linux/macOS)

📦 Installation

Works perfectly with any project — Rust, Go, Python, JavaScript, C++, or anything else. No runtime lock-in.

Option A: Node.js (npx)

Stable Release:

# Basic installation (defaults to .agent/ folder)
npx magic-spec@latest

# Targeted installation for Cursor
npx magic-spec@latest --cursor

Edge Version (GitHub):

npx --yes github:teratron/magic-spec

Option B: Python (uvx)

Stable Release:

# Basic installation
uvx magic-spec

# Targeted installation for Windsurf
uvx magic-spec --windsurf

Edge Version (GitHub):

uvx --from git+https://github.com/teratron/magic-spec.git magic-spec

Option C: Python (pipx)

pipx run magic-spec

Option D: Multi-Adapter Installation

You can install support for multiple adapters at once:

npx magic-spec@latest --cursor --copilot --windsurf

Option E: Manual Installation

If automated installers do not fit your environment:

1. Engine: Download the .magic/ folder from the GitHub repository.
2. Workflows: Download command wrappers from .agent/workflows/.
3. Deploy: Place files into your AI agent's instruction directory (e.g., .cursor/commands).

🔄 Updating

Keep your SDD engine up to date with the latest logic and features:

# Check if update is available
npx magic-spec@latest --check

# Perform the update
npx magic-spec@latest --update

[!TIP] The update process preserves your .design/ workspace and automatically creates backups of .magic/ and .agent/ folders. If you have modified core engine files, the installer will detect conflicts and ask for your preference (overwrite, skip, or abort).

💬 Usage

Just talk to your AI agent naturally in your prompt interface. No complex commands to learn:

• "Dispatch this thought into specs..." → Triggers Specification workflow.
• "Create an implementation plan" → Triggers Task & Plan workflow.
• "Execute the next task" → Triggers Run workflow.
• "Add a rule: always use Inter font" → Triggers Rule workflow.

🤝 Compatibility

Magic Spec is heavily optimized and provides native workflow generation for the world's most powerful AI development environments.

You can install support for a specific adapter using the shortcut flag (e.g., --cursor) or the environment flag (e.g., --env cursor).

AI Agent / IDE	Shortcut Flag	Env Flag
Cursor (Agent Mode)	--cursor	--env cursor
Windsurf (Cascade)	--windsurf	--env windsurf
Claude Code	--claude	--env claude
Gemini CLI	--gemini	--env gemini
GitHub Copilot	--copilot	--env copilot
Roo Code	--roo	--env roo
Amp	--amp	--env amp
Amazon Q Developer	--q	--env q
Kilo Code	--kilocode	--env kilocode
Qwen Code	--qwen	--env qwen
OpenCode	--opencode	--env opencode
SHAI (OVHcloud)	--shai	--env shai
IBM Bob	--bob	--env bob
CodeBuddy	--codebuddy	--env codebuddy
Qoder IDE	--qoder	--env qoder
Codex CLI	--codex	--env codex
Auggie CLI	--augment	--env augment
Antigravity IDE	--antigravity	--env antigravity
Lingma IDE	--lingma	--env lingma

📚 Documentation

• Main Documentation — Detailed guide on workflows, architecture, and advanced features.
• Installers Guide — Advanced CLI options and platform specifics.
• Contributing — How to develop, test, and extend the engine.

🛟 Support

If you encounter issues or have questions:

• Open an Issue on GitHub.
• Run magic.onboard in your agent to restart the interactive tutorial.

🗺️ Roadmap

• Multi-agent adapter system.
• Phased implementation planning.
• Extended support for local-first LLM agents.
• Advanced visual dashboard for project health.
• Integration with CI/CD for automated spec validation.

🏗️ Contributing

We welcome contributions! Whether it's a bug fix, a new adapter, or an improvement to the workflow logic. Please see Contributing Guide for details.

👥 Authors and Acknowledgments

• Oleg Alexandrov — Creator and Lead Maintainer.
• Special thanks to the AI agent community for inspiration and testing.

📄 License

Distributed under the MIT License.

📊 Project Status

Active Development (v1.x). We are constantly refining the SDD engine based on real-world usage.