Terminal.skills
Skills/dagger
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dagger

Write CI/CD pipelines as code with Dagger — portable, cacheable, container-based pipelines that run locally and in any CI system. Use when someone asks to "write CI pipeline in TypeScript", "portable CI/CD", "run GitHub Actions locally", "Dagger pipeline", "CI as code", "containerized build pipeline", or "test my CI locally before pushing". Covers Dagger SDK (TypeScript/Python), pipeline composition, caching, secrets, and multi-stage builds.

#ci-cd#containers#pipelines#dagger#docker
terminal-skillsv1.0.0
Works with:claude-codeopenai-codexgemini-clicursor
Source

Usage

$
✓ Installed dagger v1.0.0

Getting Started

  1. Install the skill using the command above
  2. Open your AI coding agent (Claude Code, Codex, Gemini CLI, or Cursor)
  3. Reference the skill in your prompt
  4. The AI will use the skill's capabilities automatically

Example Prompts

  • "Deploy the latest build to the staging environment and run smoke tests"
  • "Check the CI pipeline status and summarize any recent failures"

Documentation

Overview

Dagger lets you write CI/CD pipelines in TypeScript, Python, or Go instead of YAML. Pipelines run in containers, are fully cacheable, and work identically on your laptop and in GitHub Actions/GitLab CI/Jenkins. No more "works in CI but not locally" — test your entire pipeline before pushing.

When to Use

  • Tired of debugging YAML-based CI configs by pushing commits
  • Need to run the exact same pipeline locally and in CI
  • Complex build pipelines that benefit from TypeScript/Python logic (conditionals, loops)
  • Want container-level caching for build steps
  • Multi-language monorepo where different projects need different pipelines

Instructions

Setup

bash
# Install Dagger CLI (macOS/Linux)
brew install dagger/tap/dagger

# Initialize in your project
dagger init --sdk=typescript

Basic Pipeline

typescript
// dagger/src/index.ts — CI pipeline for a Node.js project
/**
 * Dagger pipeline that builds, tests, and creates a Docker image.
 * Runs identically on your laptop and in any CI system.
 */
import { dag, Container, Directory, object, func } from "@dagger.io/dagger";

@object()
class Ci {
  /**
   * Run the full CI pipeline: install → lint → test → build.
   */
  @func()
  async ci(source: Directory): Promise<string> {
    const node = this.base(source);

    // Run steps in sequence (each cached independently)
    await this.lint(source);
    await this.test(source);
    const built = await this.build(source);

    return "✅ CI passed";
  }

  /**
   * Base container with dependencies installed.
   * Cached — only re-runs if package.json changes.
   */
  @func()
  base(source: Directory): Container {
    return dag
      .container()
      .from("node:20-slim")
      .withDirectory("/app", source)
      .withWorkdir("/app")
      // Cache node_modules across runs
      .withMountedCache("/app/node_modules", dag.cacheVolume("node-modules"))
      .withExec(["npm", "ci"]);
  }

  @func()
  async lint(source: Directory): Promise<string> {
    return this.base(source)
      .withExec(["npm", "run", "lint"])
      .stdout();
  }

  @func()
  async test(source: Directory): Promise<string> {
    return this.base(source)
      .withExec(["npm", "run", "test", "--", "--run"])
      .stdout();
  }

  @func()
  async build(source: Directory): Promise<Directory> {
    return this.base(source)
      .withExec(["npm", "run", "build"])
      .directory("/app/dist");
  }

  /**
   * Build and push a Docker image.
   */
  @func()
  async publish(source: Directory, registry: string, tag: string): Promise<string> {
    const built = await this.build(source);

    const image = dag
      .container()
      .from("node:20-slim")
      .withDirectory("/app", built)
      .withWorkdir("/app")
      .withEntrypoint(["node", "index.js"]);

    const ref = await image.publish(`${registry}:${tag}`);
    return `📦 Published: ${ref}`;
  }
}

Run Locally

bash
# Run the full CI pipeline on your local code
dagger call ci --source=.

# Just run tests
dagger call test --source=.

# Build and publish Docker image
dagger call publish --source=. --registry=ghcr.io/myorg/myapp --tag=latest

Pipeline with Services (Database)

typescript
// dagger/src/index.ts — Pipeline with Postgres for integration tests
@object()
class Ci {
  @func()
  async integrationTest(source: Directory): Promise<string> {
    // Start a Postgres service container
    const db = dag
      .container()
      .from("postgres:16")
      .withEnvVariable("POSTGRES_PASSWORD", "test")
      .withEnvVariable("POSTGRES_DB", "testdb")
      .withExposedPort(5432)
      .asService();

    // Run tests with database available
    return this.base(source)
      .withServiceBinding("db", db)
      .withEnvVariable("DATABASE_URL", "postgresql://postgres:test@db:5432/testdb")
      .withExec(["npm", "run", "db:migrate"])
      .withExec(["npm", "run", "test:integration"])
      .stdout();
  }
}

Secrets

typescript
// Handle secrets safely — never baked into container layers
@func()
async deploy(source: Directory, apiKey: Secret): Promise<string> {
  return this.base(source)
    .withSecretVariable("API_KEY", apiKey)  // Mounted as env var, not in layer
    .withExec(["npm", "run", "deploy"])
    .stdout();
}

GitHub Actions Integration

yaml
# .github/workflows/ci.yml — Run Dagger pipeline in GitHub Actions
name: CI
on: [push, pull_request]

jobs:
  ci:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - uses: dagger/dagger-for-github@v7
        with:
          verb: call
          args: ci --source=.

Examples

Example 1: Monorepo CI pipeline

User prompt: "I have a monorepo with a Next.js frontend and a Python backend. Set up a CI pipeline that tests both."

The agent will create a Dagger pipeline with separate functions for frontend (Node.js container, npm test) and backend (Python container, pytest), both running from the same pipeline with shared caching.

Example 2: Replace GitHub Actions with Dagger

User prompt: "My GitHub Actions workflow is 200 lines of YAML and I can't test it locally. Convert it to Dagger."

The agent will translate each YAML step into a Dagger function, add caching for dependencies, and show how to run the same pipeline locally with dagger call.

Guidelines

  • Run locally firstdagger call on your laptop before pushing to CI
  • Cache aggressivelywithMountedCache for node_modules, pip cache, build artifacts
  • Secrets via Secret type — never pass secrets as plain strings or env vars in Dockerfiles
  • Services for databasesasService() + withServiceBinding() for Postgres/Redis in tests
  • Each @func() is independently callable — design for composability
  • Container layers are cached — order operations so rarely-changing steps come first
  • Dagger Cloud for team caching — share build cache across CI runners
  • Use withExec for each command — separate steps for better cache granularity

Information

Version
1.0.0
Author
terminal-skills
Category
DevOps
License
Apache-2.0