Spec Kit 🤖 Agent Free

What it does

Spec Kit is GitHub's open-source toolkit for giving AI coding agents a structured process instead of ad-hoc prompts. Its core process is spec-driven development: you describe what you want and why, the agent turns that into a specification, a technical plan and a task list, and only then implements against those documents. Two optional processes sit alongside it, one for diagnosing and fixing bugs and one for assessing whether an idea is worth building.

What is inside / how it works

A Python command-line tool, specify, sets up a project with templates, helper scripts and the agent-side commands or skills for your chosen agent. Inside the agent you then run the steps one at a time and review each result: /speckit-constitution for project principles, then /speckit-specify, /speckit-plan, /speckit-tasks, /speckit-implement and /speckit-converge, repeating implement and converge until the code matches the artifacts. Extra steps add clarification, checklists and cross-artifact consistency analysis. The bug extension separates assess, fix and test, and the assessment extension ends with a go, clarify or stop decision. Extensions, presets, workflows and community bundles let teams adapt the process. Invocation syntax varies by agent, for example $speckit-specify in Codex.

Works with

The documentation lists dozens of integrations, including GitHub Copilot (the default), Claude Code, Gemini CLI, Codex CLI, Cursor, Amp, Cline, opencode, Kilo Code, Qwen Code, Kiro CLI, Goose, Zed and Antigravity, plus a generic option for other agents.

How to install or start

You need Python 3.11+ and uv. Install the CLI from PyPI, then create a project for your agent:

uv tool install specify-cli
specify init my-project --integration claude

The docs also document installing from a pinned GitHub release tag. Bug fixing and assessment are added with specify extension add bug and specify extension add assess.

Pricing

Free and open source under the MIT licence. You pay only for the coding agent you run it with.

Who should use it

Developers and teams building features large enough that a written spec and plan pay off, and anyone who wants the same process across several agents. For one-line fixes the ceremony is overkill, and the output is only as good as the specification and reviews you put in at each step.