Spec Kit

What Is Spec Kit?

Spec Kit is GitHub's open-source toolkit for Spec-Driven Development (SDD) — a methodology that treats specifications as first-class executable artifacts rather than throwaway documents. Instead of jumping straight from idea to code, Spec Kit structures AI-assisted development into discrete phases where each step produces artifacts that feed the next.

The core insight: for decades, specifications were scaffolding we discarded once coding began. Spec Kit reverses this — specifications become the implementation pipeline.

How It Works

Spec Kit has two components:

1. specify CLI — initializes projects with the right scaffolding for your chosen AI agent
2. Slash commands — structured commands your AI agent uses during development

Installation

uv tool install specify-cli --from git+https://github.com/github/spec-kit.git
specify init my-project --ai claude

The CLI detects your AI agent and sets up the appropriate command integration. Supports --ai claude, --ai copilot, --ai cursor-agent, --ai gemini, and 15+ others.

The 4-Phase Workflow

Phase 0: Constitution (/speckit.constitution)

Establish project principles — coding standards, testing requirements, UX guidelines. This creates a governing document that constrains all subsequent phases.

/speckit.constitution Focus on code quality, testing standards, 
accessibility, and performance requirements

Phase 1: Specify (/speckit.specify)

Define what you want to build and why. No tech stack, no implementation details — pure requirements and user stories.

/speckit.specify Build a task management app with real-time 
collaboration, Kanban boards, and mobile support

Phase 2: Plan (/speckit.plan)

Now add the how — your tech stack, architecture choices, and technical constraints.

/speckit.plan Use React with TypeScript, Node.js backend, 
PostgreSQL database

Phase 3: Tasks (/speckit.tasks)

Break the plan into actionable, ordered implementation tasks. Each task is scoped for a single AI agent session.

Phase 4: Implement (/speckit.implement)

Execute all tasks sequentially, building the feature according to the plan. The AI agent works through the task list, producing code that matches the specification.

Optional Commands

Command	Purpose
/speckit.clarify	Resolve ambiguities before planning (recommended)
/speckit.analyze	Cross-artifact consistency check after tasks
/speckit.checklist	Generate quality validation checklists

Platform Support

Spec Kit supports 20+ AI coding agents — an unusually broad compatibility matrix:

• Full support: Claude Code, GitHub Copilot, Cursor, Gemini CLI, Windsurf, Amp, Codex CLI, Roo Code, Kilo Code, Qwen Code, opencode, Auggie CLI, CodeBuddy CLI, IBM Bob, Jules, SHAI, Antigravity, Qoder CLI
• Partial: Amazon Q Developer CLI (no custom slash command args)
• Generic: Bring any agent with --ai generic --ai-commands-dir <path>

This agent-agnostic design is deliberate — GitHub is positioning SDD as a methodology, not a product lock-in.

Why It Matters

The Anti-Vibe-Coding Framework

Spec Kit is the most structured counter-proposal to "vibe coding" — the practice of iterating with an AI in a single unstructured conversation until something works. By decomposing development into specify → plan → tasks → implement, it creates checkpoints where humans review and redirect.

Specifications as Source of Truth

In traditional development, code is the source of truth and specs rot. In SDD, specifications are living artifacts that generate implementations. Change the spec, regenerate the code. This is closer to how compiled languages treat source code — the spec is the source.

Multi-Agent Ready

The task decomposition phase (/speckit.tasks) naturally creates work units that could be distributed across multiple agents. While Spec Kit currently runs tasks sequentially, the architecture suggests future parallelization — relevant for orchestration tools like Tembo.

Enterprise Adoption Signal

GitHub building and open-sourcing this signals that structured AI development is becoming table stakes for enterprise. The constitution and checklist features specifically target compliance and governance requirements.

Development Phases

Spec Kit targets three scenarios:

• Greenfield (0-to-1): Generate new applications from specifications
• Creative Exploration: Parallel implementations across different tech stacks
• Brownfield Enhancement: Add features to existing codebases iteratively

Competitive Context

Spec Kit occupies a unique position — it's not an AI agent itself, but a workflow layer that sits on top of agents. Closest comparisons:

• Cursor Rules / Claude Project docs — static context, not structured workflow
• AGENTS.md — agent guidance, not phased development
• Tembo — orchestration layer; Spec Kit could feed into multi-agent orchestration
• Prompt.MD — template-based; Spec Kit is more opinionated about phases

Key Stats

• 71k GitHub stars (as of Feb 2026)
• 2.3k+ forks
• MIT licensed
• 20+ supported AI agents
• Prerequisites: Python 3.11+, Git, uv package manager