agent-scaffold-cli 0.4.576

Generate runnable AI agent projects from markdown specs in the agent-deployments repo.

agent-scaffold

agent-scaffold generates runnable AI agent projects from markdown specs. It fetches the agent-deployments catalog at runtime (one URL hardcoded, overridable via --catalog-url) and falls back to an embedded snapshot when offline — pick a recipe, target language, and framework, and the CLI assembles the relevant docs, asks Claude to emit a complete project, validates the response, and writes the files atomically into your destination of choice.

The three-repo ecosystem

agent-blueprints and agent-deployments are the two arms that feed this CLI — the engine that composes a selection into a real, running agent:

agent-blueprints ──────────┐
(design core)              │
kernel · patterns · IR     ├──>  agent-scaffold  ──>  running agent
                           │     (composition        (code + server,
agent-deployments ─────────┘      engine)             live)
(verified options)
adapters · recipes · catalog

• agent-blueprints — the design core: the kernel, framework-agnostic patterns at five levels, and the spec/IR a selection compiles to. What the agent is and how it's shaped.
• agent-deployments — the verified options: a port-typed registry of vetted adapters and production-shaped recipes, indexed by catalog.yaml. Which concrete options realize each port.
• agent-scaffold (this repo) — the composition engine: validates a selection, binds each port to a deployments option, and emits a complete, running project.

Install

The package is published on PyPI as agent-scaffold-cli and installs two equivalent binaries: agent-scaffold (long form) and scaffold (short, claude-style). Bare scaffold (no subcommand) drops you straight into the interactive REPL.

One-line install (recommended). Installs the CLI, adds it to your PATH, and offers to store your Anthropic key:

curl -fsSL https://raw.githubusercontent.com/jagguvarma15/agent-scaffold/main/install.sh | sh

Or install manually. A plain pip install can't put the binaries on your PATH (wheels run no code at install time), so use pipx/uv tool and run their one-time PATH step:

pipx install agent-scaffold-cli && pipx ensurepath
# or
uv tool install agent-scaffold-cli && uv tool update-shell
# or, for one-off use (no install, no PATH change):
uvx --from agent-scaffold-cli scaffold --help

Either way, restart your shell afterward, then store your Anthropic key once with scaffold auth login (the one-line installer prompts for it during setup). scaffold won't start without a key.

Quickstart

export ANTHROPIC_API_KEY=sk-ant-...
agent-scaffold scaffold   # interactive shell — recommended
# or, one-shot:
agent-scaffold new

By default the interactive flow chains generation into a running stack: install deps, start docker, run migrations, seed data, launch the frontend, open the browser. See the quickstart guide for the full lifecycle and its escape hatches.

Documentation

The full manual lives at jagguvarma15.github.io/agent-scaffold:

• Installation and quickstart
• Interactive shell — slash commands, free-text refinement, the /new wizard
• Configuration — env vars, TOML fallback, effort presets
• Project lifecycle — up, update, down, logs, eval
• CLI reference and REPL reference
• Recipe format — frontmatter, dependencies, external services
• Credentials and the security model
• Troubleshooting

Contributor docs stay in the repo: CONTRIBUTING.md, SECURITY.md, CHANGELOG.md.

Local development

git clone https://github.com/jagguvarma15/agent-scaffold
cd agent-scaffold
uv sync
make install-dev   # exposes `scaffold` + `agent-scaffold` on PATH (editable)

License

MIT (see LICENSE).