An AI SDLC bootstrapper. One command turns an empty directory into a fully-wired, AI-ready project — with skills, a docs hierarchy, templated context files, and an orchestrator (Polly) that walks your team through the whole software lifecycle.
Quickstart · Documentation · SDLC flow · Skills · Tool support
npx create-nonoise my-project
cd my-project
# Open in Claude Code, or tell Copilot: "start polly"The CLI asks which AI tools your team uses (Claude Code, GitHub Copilot), then scaffolds:
src/— your code. Stack-agnostic: pick .NET, Node, Python, Rust, Go. The SDLC flow doesn't care.docs/— the six-folder source-of-truth hierarchy (architecture/,requirements/,calls/,support/,prd/,sprints/) — seedocs/docs-hierarchy.md..claude/skills/— a library of 40+ AI skills: Polly orchestrator, BMAD-derived personas, Quint FPF validator, vendored superpowers, design / ops / testing packs.- Context files for every selected tool —
CLAUDE.md,.github/copilot-instructions.md,AGENTS.md,.cursor/rules.md,GEMINI.md— generated from one source of truth. tools/md-extractor/andtools/devops-push/— Node CLIs ready to use..nonoise/POLLY_START.md— auto-trigger marker. On first session, your AI reads it and invokes Polly; Polly asks "greenfield or brownfield?" and walks you through the rest.
Most AI tooling assumes a one-man-band developer with a chat window. Real companies have analysts, architects, multiple developers, shadow testers. Different phases need different models — discovery and architecture are [pair] work on a large model; implementation is [solo] on a smaller one. NONoise's orchestrator announces the mode for every step so nobody wastes the wrong model on the wrong problem.
A skill library is useless if nobody knows what to use when. Polly is the conductor that removes that problem entirely. It auto-triggers the moment scaffolding is complete, asks one question — greenfield or brownfield? — and then walks your team through the full SDLC in sequence, surfacing the right skill at every phase.
🚀 create-nonoise ──► 🎼 Polly
│
┌────────────┴────────────┐
Greenfield Brownfield
│ │
▼ ▼
📋 Requirements ──► 🔍 Discovery ──► 🏛️ Architecture ──► 📅 Sprint Planning
│
┌─────────────────────────────────────────────────────┘
▼
⚙️ Implementation ──► 🧪 Unit & Integration ──► 🤖 Test Automation ──► ✅ Acceptance
▲ │
└──────────────────────── 🔁 Next sprint ────────────────────────────┘
You never pick the wrong skill. You always know the next step.
Canonical architectures beat exotic ones because they're already in the parametric memory of every frontier LLM. NONoise's architectural skills push toward DDD, Clean Architecture, CQRS, standard REST — and only allow deviations that survive a formal Quint FPF validation. Every token you spend re-teaching the LLM your bespoke abstraction is a token it isn't spending on your actual problem.
Local tooling, no service. Everything runs inside your AI tool of choice. No server, no telemetry, no account. Skills are plain Markdown; a git clone carries them between projects. External tools (issue trackers, voice recorders, memory systems) are mentioned by Polly at the right moment — not wired, not required.
# Scaffold
npx create-nonoise my-project
# Enter the project and open your AI tool of choice
cd my-project
code . # VS Code + Claude Code / Copilot
cursor . # Cursor
# or in a terminal:
claude # Claude Code CLIOn first session the AI detects .nonoise/POLLY_START.md and invokes Polly automatically. If you missed the trigger, start Polly manually:
- Claude Code:
/polly - GitHub Copilot: "start polly" / "avvia polly" / "run polly"
- Cursor / Gemini CLI / Codex: read
.claude/skills/polly/SKILL.mdand follow
Polly will:
- Suggest voice-to-text tools for long sessions (Wispr Flow / Handy / Superwhisper) — info only, not installed.
- Ask: greenfield or brownfield?
- Walk the appropriate pipeline, announcing
[pair]vs[solo]for every step.
A full walkthrough of the SDLC lives in docs/sdlc.md; Polly's decision tree is documented in docs/polly.md.
| If you want to … | Read |
|---|---|
| See the big picture — what NONoise is and isn't | docs/overview.md |
| Understand the philosophy — 5 noise sources, parametric memory, canonical patterns | docs/philosophy.md |
| Follow the SDLC flow — greenfield + brownfield, step by step | docs/sdlc.md |
| Meet Polly — orchestrator decision tree, pair/solo modes, dev trio | docs/polly.md |
| See the team model — why NONoise is team-first, not one-man-band | docs/team-model.md |
| Browse the skill catalog — 40+ skills organized by domain | docs/skills-catalog.md |
| Understand the docs/ tree — six folders, each a source of truth | docs/docs-hierarchy.md |
| Check tool support — Claude Code, Copilot, Cursor, Gemini CLI, Codex | docs/cross-tool.md |
| See external tools Polly mentions (info-only) | docs/external-tools.md |
| Install, build, and extend the framework itself | docs/installation.md |
The same material feeds the public site at NONoise-frmw-site.
Prerequisites: Node >=20, pnpm 9.12.0 (pinned via packageManager).
pnpm install # workspace deps
pnpm --filter create-nonoise run build # build CLI + bundle assets
pnpm --filter create-nonoise exec vitest run # 47 CLI tests
pnpm -r run test # every package's tests
pnpm -r run typecheck # typecheck all
node scripts/sync-vendor.mjs # refresh vendored superpowersVersioning via Changesets: pnpm changeset → pnpm version → pnpm release.
Full dev loop, skill authoring flow, and release process: docs/installation.md.
MIT (see LICENSE, landing with the first tagged release). Use of the framework or its methodology in any project — commercial or internal — requires visible attribution per ATTRIBUTION.md: a short "powered by NONoise" note in the project README or About section, pointing to this repository.
NONoise was created by Alessandro Russo (@russosalv) as a lesson-learned, packaged and open-sourced so the method — not just one implementation — outlives the project it was born in.