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SDLC Studio

Getting started

SDLC Studio installs as an Agent Skill - a folder of instructions, templates and deterministic scripts that your AI coding agent reads. There is nothing to import into your code, no account, and no server. It runs entirely in your own repository.

The mental model (read this first)

Section titled “The mental model (read this first)”

If you last used SDLC Studio when it was mostly human-driven, or you have only ever vibe-coded, three ideas are worth thirty seconds before you install.

  1. Two backlogs, not one. A discovery backlog holds requests - change requests (CRs) and RFCs. A request is not work yet. It becomes delivery work - epics, stories and bugs, each with acceptance criteria - only when refine decomposes and sizes it. This one rule keeps “ideas” and “committed, sized work” from ever being the same list.

  2. Done is proven, not declared. A story reaches Done only when its executable acceptance criteria pass and an independent reviewer - never the author - signs it off. The tools recompute status from the files, so you cannot simply write Status: Done and have it stick.

  3. You are in the lead; the tooling holds the discipline. You set the goal and approve each step. The agent carries the cost of the ceremony - authoring the spec, keeping it current, running the checks - so the discipline stays affordable.

Install

Section titled “Install”
Terminal window
curl -fsSL https://raw.githubusercontent.com/DarrenBenson/sdlc-studio/main/install.sh | bash

You do this once. It installs into your agent’s skills directory; --list-targets shows the map, --local installs into just the current project. See Works with your agent for the per-agent detail, and For AI agents if an agent is doing the install.

Requirements: Python 3.10+ for the bundled scripts (standard library only; PyYAML is the one optional dependency, needed only if you set a project .config.yaml). The gh CLI only for GitHub sync. Whatever test runners your acceptance criteria invoke.

Your first project: one command

Section titled “Your first project: one command”

You do not need to know the pipeline order. init guided walks you from an empty (or existing) repo all the way to a ready first sprint plan, one stage at a time:

/sdlc-studio init guided

It works out for itself whether you are greenfield (nothing yet) or brownfield (existing code) from the files in your repo, and forks each stage accordingly - you never have to choose create versus generate. It walks these seven stages:

  1. agents - seeds AGENTS.md and CLAUDE.md so every AI agent you use reads the same discipline.
  2. prd - the PRD: interviewed from scratch on greenfield, reverse-engineered from your code on brownfield.
  3. trd - the TRD, generated from the PRD.
  4. tsd - the TSD, the test strategy the sprint plan will later read.
  5. personas - your project’s team, grown from the PRD and its risk signals for you to accept or edit.
  6. decompose - the PRD broken into epics and sized stories.
  7. plan - your first sprint plan. Onboarding ends exactly where delivery begins.

Each stage drafts its document for you to review, then advances only when you confirm:

/sdlc-studio init guided --confirm   # accept the drafted stage and move on
/sdlc-studio init guided --skip      # skip this stage (a recorded decision)
/sdlc-studio init guided --reset     # start the walk again

Prefer to try before you commit to anything? On existing code, /sdlc-studio audit --profile repo runs a read-only, refute-panel-verified audit of the repo and files what it finds - zero setup.

Never lose your place

Section titled “Never lose your place”
/sdlc-studio status   # the at-a-glance dashboard: what is specified, built, proven, checked
/sdlc-studio hint     # the single next thing to do

While guided onboarding is under way, hint points you straight back at the next stage; once you are past the first plan it becomes the ordinary next-step ladder. Either way you do not need to memorise commands - say what you want in plain language (“plan the next sprint”, “extract the spec from this code”) and the agent maps it.

Where to next

Section titled “Where to next”