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Dockerfile Optimizer

Checked
patricio0312rev·vlatest·backend·MIT

Optimizes Dockerfiles for smaller image sizes and faster builds, improving deployment efficiency and reducing storage costs.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add patricio0312rev/skills --skill dockerfile-optimizer -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

patricio0312rev

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No undeclared network calls: passed

    Makes no network calls.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned patricio0312rev/skills at 79ea6af485.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
79ea6af485
Manifest
ci-cd/dockerfile-optimizer/SKILL.md
Scanned
1 file, 582 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

What it does

The Dockerfile Optimizer skill helps AI agents build optimized, secure, and cache-efficient Docker images based on production best practices. It analyzes existing Dockerfiles, identifies areas for improvement, and implements techniques like multi-stage builds, efficient layer caching, and the use of smaller base images to reduce image size and improve build speed. The skill also incorporates security hardening measures such as creating non-root users and minimizing permissions.

When to use it

  • You need to reduce the size of your Docker images for faster deployments and lower storage costs.
  • Your Docker builds are slow, and you want to improve their efficiency.
  • You're looking to enhance the security posture of your containerized applications.
  • You’re working with Node.js, Python, Go, Rust, or Java projects and need guidance on optimal base image selection.
  • You want to automate the process of creating multi-stage Docker builds.

Key capabilities

  • Dockerfile Analysis: Identifies optimization opportunities within existing Dockerfiles.
  • Multi-Stage Builds: Separates build and runtime environments for smaller images.
  • Layer Caching Optimization: Orders instructions in the Dockerfile to maximize cache utilization.
  • Image Size Minimization: Recommends and utilizes slim base images (e.g., node:20-slim, node:20-alpine, gcr.io/distroless/nodejs20).
  • Security Hardening: Creates non-root users and minimizes permissions within containers.
  • Health Check Configuration: Adds health checks to ensure container monitoring.
  • Base Image Recommendations: Provides guidance on selecting appropriate base images for various languages (Node.js, Python, Go, Rust, Java).

Example prompts

  • "Optimize this Dockerfile: [Dockerfile content]"
  • "Suggest a smaller base image for my Node.js application."
  • "Create a multi-stage Dockerfile for a Next.js project."

Tips & gotchas

  • The skill provides recommendations based on common best practices; review the generated Dockerfiles carefully before deploying to production.
  • Consider the trade-offs between image size and functionality when selecting base images (e.g., Alpine is smaller but may require additional dependencies).
  • For maximum security, consider using distroless base images like gcr.io/distroless/nodejs20.