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@dedalus-labs/hollywood

v0.1.0-alpha.1

Published

AI-native TypeScript scripts for GitHub Actions, without shell-in-YAML.

Readme

Hollywood

Lights, cameras, Actions!

Hollywood lets you write GitHub Actions logic as typed TypeScript, run it locally, and generate ordinary GitHub Actions files for CI/CD.

"Lights, Cameras, (GitHub) Actions!"

Hollywood is AI-native and AI-friendly. The docs ship copy-page controls and generated agent context. Point your agents at the docs, hand them llms.txt or llms-full.txt, and let them rip on typed TypeScript actions instead of hand-writing YAML.

GitHub Actions is a good orchestration layer. It knows when jobs should run, which runner labels they need, which secrets exist, and how jobs depend on each other.

It is a rough programming environment. Real DevOps logic often turns into shell inside YAML: untyped strings, quoting bugs, hidden input coercion, and commits whose only purpose is "try CI again".

Our position is simple: people should not spend their time painstakingly handwriting imperative GitHub Actions YAML. YAML should orchestrate. TypeScript should program.

Hollywood moves the imperative part into TypeScript scripts you can test before they run on GitHub. The generated output is still boring GitHub Actions: action.yml, uses: ./.github/actions/..., and JavaScript actions that run through GitHub's official action toolkit.

This works because GitHub Actions can run JavaScript actions directly. An action.yml file points at a Node entrypoint, and Hollywood generates the thin adapter around your typed script.

See CONTRIBUTING.md for the CLA/Vouch contribution flow and ROADMAP.md for planned contribution areas. See SECURITY.md for the GitHub Actions hardening policy.

Docs

Published docs live at https://oss.dedaluslabs.ai/hollywood.

Build them locally:

python3 -m venv .venv
. .venv/bin/activate
python -m pip install -r docs/requirements.txt
python -m mkdocs serve -f mkdocs.yml

Contributions

Hollywood accepts external code from vouched contributors. Due to the increased volume of AI-generated code, Hollywood uses Vouch as the arbiter of contributor trust and CLA eligibility for external pull requests. Being listed in VOUCHED.td means a maintainer has verified the GitHub account and recorded that the contributor accepted CLA.md.

The flow is:

  1. Open a "Vouch request" issue.
  2. Confirm that you have read and accept CLA.md.
  3. Link public GitHub work, a project website, or another public identity that helps a maintainer recognize you.
  4. If an existing vouched contributor knows you, ask them to comment on the issue.
  5. A maintainer adds your GitHub handle to VOUCHED.td.

Do not add yourself to VOUCHED.td in your first contribution. The CLA check reads that file from the trusted base branch, so normal pull requests cannot self-vouch.

For code and docs changes, fork the repository and open a pull request from your branch into dedalus-labs/hollywood:main. See CONTRIBUTING.md for the full checklist.

Node Requirements

The package runtime and the repository toolchain have different Node requirements:

| Surface | Node requirement | | -------------------------- | ---------------------------- | | Installed package and CLI | Node 20 or newer | | Generated GitHub actions | GitHub's Node 24 action runtime | | Building Hollywood locally | Node 22.18+ or Node 24.11+ |

The published package declares engines.node >=20 in package.json. The build output targets Node 20 in tsdown.config.ts. tsconfig.json is only the typecheck configuration; it is not the runtime support contract.

Use Node 22.18+ or Node 24.11+ when contributing because the local build and declaration-generation toolchain has stricter engine requirements than the published runtime package.

Install

npm install --save-dev @dedalus-labs/hollywood

That installs a local hollywood binary at node_modules/.bin/hollywood. Run it with npx hollywood ..., or put hollywood ... inside an npm script.

Small Dependency Surface

Hollywood is intentionally lightweight. The package has six direct runtime dependencies:

  • @actions/core
  • @actions/exec
  • @actions/expressions
  • @actions/workflow-parser
  • esbuild
  • yaml

Most of that surface is GitHub's own action toolkit and schema parser. The published package only ships runtime files, type declarations, package metadata, the README, and the license. A smaller dependency graph is easier to audit and reduces npm supply-chain exposure.

Before / After

Before Hollywood, a container publish step might look like this:

- name: Publish container image
  run: |
    set -euo pipefail
    IMAGE_REF="ghcr.io/acme/api:${GITHUB_SHA}"
    docker buildx build \
      --file Dockerfile \
      --tag "${IMAGE_REF}" \
      --push \
      --provenance false \
      .
    echo "image_ref=${IMAGE_REF}" >> "$GITHUB_OUTPUT"

With Hollywood, the program is typed TypeScript instead of text hidden in YAML:

import {
	type ActionInputValues,
	type ActionOutputValues,
	action,
	booleanInput,
	choiceInput,
	integerInput,
	pathInput,
	stringInput,
	stringOutput,
} from "@dedalus-labs/hollywood";

const publishInputs = {
	image: stringInput({ description: "Container image name, including registry." }),
	tag: stringInput({ description: "Container image tag." }),
	context: pathInput({ description: "Build context path.", default: "." }),
	dockerfile: pathInput({ description: "Dockerfile path.", default: "Dockerfile" }),
	platform: choiceInput({
		description: "Build target platform.",
		options: ["linux/amd64", "linux/arm64"] as const,
		default: "linux/amd64",
	}),
	provenance: choiceInput({
		description: "Build provenance mode.",
		options: ["false", "min", "max"] as const,
		default: "false",
	}),
	cacheFrom: stringInput({ description: "Optional build cache source.", default: "" }),
	buildAttempt: integerInput({ description: "CI build attempt number." }),
	push: booleanInput({ description: "Push instead of loading locally.", default: "true" }),
} as const;

const publishOutputs = {
	imageRef: stringOutput({ description: "Published image reference." }),
} as const;

type PublishImageInput = ActionInputValues<typeof publishInputs>;
type PublishImageOutput = ActionOutputValues<typeof publishOutputs>;

const imageRef = (input: Pick<PublishImageInput, "image" | "tag">): string =>
	`${input.image}:${input.tag}`;

const dockerBuildArgs = (input: PublishImageInput, ref: string): readonly string[] => {
	const args = [
		"buildx",
		"build",
		"--file",
		input.dockerfile,
		"--platform",
		input.platform,
		"--tag",
		ref,
		"--label",
		`ci.build-attempt=${input.buildAttempt}`,
		"--provenance",
		input.provenance,
	] as string[];

	if (input.cacheFrom.length > 0) {
		args.push("--cache-from", input.cacheFrom);
	}
	args.push(input.push ? "--push" : "--load", input.context);
	return args;
};

export const publishImage = action({
	name: "publish-container-image",
	description: "Build and publish a container image without embedding shell in workflow YAML.",
	inputs: publishInputs,
	outputs: publishOutputs,
	run: async ({ exec, input }): Promise<PublishImageOutput> => {
		const ref = imageRef(input);
		await exec("docker", dockerBuildArgs(input, ref));
		return { imageRef: ref };
	},
});

Hollywood parses GitHub's string inputs into PublishImageInput before run starts. You can still layer Zod, Effect Schema, or your own parser on top for repository-specific policy:

import { z } from "zod";

const publishPolicy = z.object({
	image: z.string().regex(/^ghcr\.io\/[a-z0-9-]+\/[a-z0-9._/-]+$/),
	tag: z.string().min(1).max(128).regex(/^[A-Za-z0-9_.-]+$/),
	context: z.string().refine((path) => !path.includes(".."), "context must stay inside workspace"),
	push: z.boolean(),
});

const validatePublishPolicy = (input: PublishImageInput): void => {
	publishPolicy.parse(input);
};

export const publishImage = action({
	// ...
	run: async ({ exec, input }): Promise<PublishImageOutput> => {
		validatePublishPolicy(input);
		const ref = imageRef(input);
		await exec("docker", dockerBuildArgs(input, ref));
		return { imageRef: ref };
	},
});

Those schema packages live in your workflow repository. Hollywood does not pull them into its own runtime dependency graph.

GitHub still sees a normal local action step:

- name: Publish container image
  uses: ./.github/actions/publish-container-image
  with:
    image: ghcr.io/acme/api
    tag: ${{ github.sha }}
    context: .
    dockerfile: Dockerfile
    platform: linux/amd64
    provenance: "false"
    build-attempt: ${{ github.run_attempt }}
    push: "true"

The important bit is the command shape:

const args = [
	"buildx",
	"build",
	"--file",
	input.dockerfile,
	"--platform",
	input.platform,
	"--tag",
	ref,
	"--label",
	`ci.build-attempt=${input.buildAttempt}`,
	input.context,
];

await exec("docker", args);

That is execve(2)-shaped: one executable path and one array of arguments. There is no shell interpolation and no YAML quoting puzzle.

Local Runs

Run an exported action directly on your machine:

npx hollywood run gha/containers/publish-image.ts \
  --with image=ghcr.io/acme/api \
  --with tag="$(git rev-parse --short HEAD)" \
  --with context=. \
  --with dockerfile=Dockerfile \
  --with buildAttempt=1 \
  --with provenance=false

Route every exec(file, args) call through a Lima VM when the script needs a Linux environment:

npx hollywood run gha/cache/s3-cache.ts \
  --lima default \
  --start-vm \
  --with mode=restore \
  --with bucket=ci-cache \
  --with prefix=node \
  --with key=linux-arm64 \
  --with archivePath=/tmp/cache.tar.gz \
  --with contentsPath=/tmp/node-cache

Hollywood invokes Lima with the same argument-array shape:

limactl shell --tty=false --start default -- <file> <arg>...

No command is rewritten into shell text. If the VM is stopped and --start-vm was not passed, the run fails before the action starts. See the execution backend docs for the supported Lima backend and planned backend directions.

Generate Actions

Generate local action metadata and entrypoints:

npx hollywood generate

Hollywood infers the source root from gha/ or ci/, and it uses @/* from tsconfig.json for generated imports when that path alias exists.

Hollywood writes ordinary GitHub Actions files:

.github/actions/publish-container-image/action.yml
.github/actions/publish-container-image/src/index.ts
.github/workflows/container-release.yml

Generated files include a marker:

# @generated by Hollywood. Do not edit by hand.

Edit the TypeScript source and regenerate. We recommend not hand-patching generated YAML.

Workflow Sources

Hollywood can generate workflow YAML from typed workflow objects too:

import { generateWorkflowFile, job, uses, workflow } from "@dedalus-labs/hollywood";
import { gh } from "@dedalus-labs/hollywood/expr";
import { publishImage } from "./containers/publish-image";

export const containerRelease = workflow({
	name: "Container Release",
	on: {
		push: { branches: ["main"] },
		workflow_dispatch: {},
	},
	permissions: { contents: "read", packages: "write" },
	jobs: {
		publish_image: job({
			"runs-on": "ubuntu-latest",
			steps: [
				{ uses: "actions/checkout@df4cb1c069e1874edd31b4311f1884172cec0e10" },
				uses(publishImage, {
					name: "Publish container image",
					with: {
						image: "ghcr.io/acme/api",
						tag: gh.github.sha,
						provenance: "false",
					},
				}),
			],
		}),
	},
});

export default generateWorkflowFile({
	sourcePath: "gha/container-release.ts",
	sourceRoot: "gha",
	workflowsDir: ".github/workflows",
	workflow: containerRelease,
});

Use Cases

Hollywood is useful when the CI/CD step is a real program:

  • publishing container images
  • creating release artifacts
  • promoting GitOps manifests between environments
  • running Terraform plan/apply wrappers
  • restoring and saving object-storage-backed caches
  • validating pull requests with path-dependent jobs

Hollywood is not a local GitHub Actions emulator. GitHub still decides event payloads, runner labels, secrets, permissions, and job scheduling.

Roadmap

Future work is tracked in ROADMAP.md. Concrete tasks should become GitHub issues before implementation, especially if they change the public API or generated YAML.

LICENSE

MIT.

Development

npm ci
npm test
npm run build
python3 -m venv .venv
. .venv/bin/activate
python -m pip install -r docs/requirements.txt
python -m mkdocs build --strict -f mkdocs.yml