ai-sdlc-kit 0.1.4

Spec-driven SDLC skills for AI coding agents — Claude Code, Cursor, Windsurf, Gemini CLI

ai-sdlc-kit

Spec-driven SDLC skills that make AI coding agents work like real engineers.

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What is it?

ai-sdlc-kit installs a set of skills for Claude Code, Cursor, Windsurf, and Gemini CLI that take an agent through a real engineering workflow instead of one-shot code generation:

understand → decide → plan in verifiable steps → build with checks after every step → gate → ship

Skill	Does
sdlc-init	One-time setup: project facts + the code-craft rulebook (.sdlc/CRAFT.md)
roadmap	Splits a PRD into ordered, shippable features
spec	Plans one feature: decisions, tasks with contracts + verify commands
build	Executes the spec task-by-task, verifying after every step
qa	Re-runs verifies + acceptance checks; failures become fix-tasks
ship	Branch guard, staged commit built from the spec — never pushes
architecture-diagram	Renders a self-contained HTML/SVG architecture diagram

Install

pip install ai-sdlc-kit
# or: uv tool install ai-sdlc-kit

Use

ai-sdlc install --agent claude   # or cursor / windsurf / gemini / all

This copies the skills into your agent's skills directory. They then appear as slash commands: /sdlc-init, /roadmap, /spec, /build, /qa, /ship.

Flag	Effect
--agent all	install for every supported agent at once
--target PATH	install into a specific project directory (default: .)
--global	install into your home directory instead of a project
--force	overwrite existing skill folders

ai-sdlc list         # see bundled skills
ai-sdlc --version    # print the installed version

Getting started

Every project starts with /sdlc-init — run it once, in your agent, inside your project folder. It writes .sdlc/PROJECT.md (project facts + commands), .sdlc/CRAFT.md (the code rulebook: pinned stack versions with modern-idiom rules, folder structure, coding style, config & security rules — every build follows it), and .sdlc/STATE.md (feature tracker). It works two ways:

• New project — /sdlc-init <path-to-your-PRD-or-description>. It reads the doc and asks a few multiple-choice questions to fill any gaps (framework, DB, test runner, etc.).
• Existing codebase — /sdlc-init with no argument. It detects your stack and rules from lockfiles, manifests, and a handful of source files instead of asking you to describe it.

Either way you choose how the rules are set — provide your own, answer questions, or let the agent propose best practices — and it always shows you the stack and rules for approval before writing anything.

From there, pick the path that matches what you're doing:

Situation	Commands
Building a whole project from a PRD	/sdlc-init <PRD> → /roadmap <PRD> → then /spec <feature> → /build <feature> → /qa <feature> → /ship <feature> for each feature in order
Adding one feature to an existing codebase	/sdlc-init (skip if already run) → /spec <feature description> → /build <feature> → /qa <feature> → /ship <feature>
Something else — bugfix, refactor, exploration	Skills are for planned feature work; for anything smaller just talk to your agent directly

/roadmap only makes sense for a whole project — it turns a PRD into an ordered feature list. For a single feature, skip straight to /spec.

The /build → /qa → /build loop is self-healing: QA never edits code, it appends fix-tasks to the spec, and /build executes them like any other task. /ship commits once QA passes — it never pushes.

Changelog

• 0.1.4 — code-craft rulebook: .sdlc/CRAFT.md pins stack versions + modern idioms, enforces folder structure (one concern per file), env-based config with .env.example, and a security baseline across /spec, /build, /qa
• 0.1.3 — added a Getting started section: how to actually invoke the skills for a new project, an existing codebase, or a single feature
• 0.1.2 — automated PyPI releases via GitHub Actions trusted publishing
• 0.1.1 — cleaner README, professional package presentation
• 0.1.0 — initial release: 6 core skills + architecture-diagram, pip-installable CLI

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Related prior art: github/spec-kit.