github/spec-kit

Analysis updated 2026-05-18

★ 92,895PythonAudience · developerComplexity · 3/5LicenseSetup · moderate

Mindmap

mindmap
  root((Spec Kit))
    What it does
      Spec-driven workflow
      AI code generation
      Specification first
    Core commands
      Constitution principles
      Specify requirements
      Plan implementation
      Tasks and checks
    How to use
      Install via Python
      Run in AI agent
      Six-stage process
    Use cases
      Brief AI assistants
      Team code standards
      Detailed specs

mindmap root((Spec Kit)) What it does Spec-driven workflow AI code generation Specification first Core commands Constitution principles Specify requirements Plan implementation Tasks and checks How to use Install via Python Run in AI agent Six-stage process Use cases Brief AI assistants Team code standards Detailed specs

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What do people build with it?

USE CASE 1

Set up a structured workflow where you write a detailed specification and let an AI agent generate the code from it.

USE CASE 2

Establish shared code quality and testing principles across a team before implementation begins.

USE CASE 3

Generate task lists and implementation plans from a written specification without manually breaking down the work.

What is it built with?

PythonCLIAI coding agents

How does it compare?

	github/spec-kit	hacksider/deep-live-cam	browser-use/browser-use
Stars	92,895	92,686	92,490
Language	Python	Python	Python
Setup difficulty	moderate	hard	moderate
Complexity	3/5	3/5	3/5
Audience	developer	vibe coder	developer

Figures from each repo's GitHub metadata at analysis time.

How do you get it running?

Difficulty · moderate Time to first run · 30min

Requires API key for AI service (OpenAI or similar) to run agents.

Use freely for any purpose including commercial, as long as you keep the copyright notice.

In plain English

github/spec-kit is a toolkit from GitHub that introduces what the README calls Spec-Driven Development: a workflow where the written specification of a piece of software is treated as the primary artefact, and an AI coding agent generates the implementation from that spec rather than the other way around. The README contrasts this with the older habit of writing throwaway specifications and then doing the "real work" purely in code, here the specification stays central and is meant to directly drive the build. The toolkit ships a command-line tool called Specify, installed through Python tooling such as uv or pipx and pulled from this GitHub repository. After running specify init in a project, the user works through a series of slash commands inside their AI coding agent. The README walks through six stages: /speckit.constitution sets governing principles for code quality, testing, UX, and performance, /speckit.specify describes what to build in user-facing terms, /speckit.plan adds the technical implementation plan and tech-stack choices, /speckit.tasks turns the plan into an actionable task list, /speckit.implement runs the tasks and produces the code, and a /speckit.check command verifies tooling. The README mentions integrations with multiple AI coding agents and a community-extensions catalog where third parties contribute additional commands. People might use Spec Kit when they want a structured way to brief an AI assistant on a project, when a team wants generated software to follow shared principles, or when they would rather write detailed specifications than start from a blank file.

Copy-paste prompts

Prompt 1

I want to use Spec Kit to build a project. Walk me through the six stages: constitution, specify, plan, tasks, implement, and check.

Prompt 2

How do I install Specify and initialize it in my project using uv or pipx?

Prompt 3

Show me how to write a specification that an AI coding agent can use to generate my implementation with Spec Kit.

Prompt 4

What slash commands do I use in my AI agent to go from a written spec to working code with Spec Kit?

Frequently asked questions

What is spec-kit?

A toolkit that treats software specifications as the primary artifact, using AI coding agents to generate implementation from detailed written specs rather than the reverse.

What language is spec-kit written in?

Mainly Python. The stack also includes Python, CLI, AI coding agents.

What license does spec-kit use?

Use freely for any purpose including commercial, as long as you keep the copyright notice.

How hard is spec-kit to set up?

Setup difficulty is rated moderate, with roughly 30min to a first successful run.

Who is spec-kit for?

Mainly developer.

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