Engsys

engsys

**An AI engineering team you install into any project.**

A complete Claude Code engineering system — agent personas, slash commands, skills, hooks, workflow docs, and curated lessons — plus a deterministic installer that materializes it **faithfully** into any project from one config file.

**[Live explainer ↗](https://eric-sabe.github.io/engsys/)** — or open [`index.html`](index.html) locally — for a visual tour of the system and the team.

Why

The system used to live copy-pasted across projects at different maturity levels. That caused two recurring pains:

1. Re-naturalization tax — hand-editing agent profiles per stack (the cloud architect as AWS vs Azure vs GCP) on every import.
2. Unfaithful plumbing — when commands were ported and a model was asked to "set up the folders," it improvised and skipped steps.

engsys fixes both. See [`docs/architecture.md`](docs/architecture.md) for the full design.

The core idea: three layers

Layer	Question	Stability	Lives in
Persona	Who does the work	Stable everywhere	core/agents/
Capability	Which stack/tech	Chosen per project	stacks/**/skills/ (packs)
Project facts	What's true about this repo	Unique per project	generated CLAUDE.md

The cloud architect (Melvin) never changes; you install `cloud-architecture-aws` **or** `-azure` **or** `-gcp` **or** `-cloudflare` and he auto-loads whichever is present. Adapting to a project becomes *choosing packs*, not *editing prose*.

Quickstart

**Option A — install from npm** (global CLI):

npm install -g engsys

cd your-project
engsys init                 # scaffold engsys.config.yaml from the bundled example
$EDITOR engsys.config.yaml  # pick cloud / iac / lang / platform / db / agents
engsys install --into .     # materialize .claude/, CLAUDE.md, settings, .mcp.json

# open the project in Claude Code and run /naturalize  (the one model-d