A professional DevOps tool designed to minimize Docker image footprints, accelerate build pipelines, and enforce production-grade security standards.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install cm-dockerfile-optimizer
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install cm-dockerfile-optimizer using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Dockerfile Optimizer?
Dockerfile Optimizer is a high-performance utility within the Openclaw Skills ecosystem that automates the auditing and refinement of containerization workflows. It analyzes existing Dockerfiles to identify inefficiencies such as bloated base images, redundant layers, and security vulnerabilities. By synthesizing best practices like multi-stage builds and distroless transitions, it ensures that your containers are lean, fast, and ready for production deployment.
This skill is essential for developers looking to reduce cloud storage costs and shorten CI/CD feedback loops. By leveraging the intelligence of Openclaw Skills, users can transform standard Dockerfiles into optimized, secure assets without manually calculating layer offsets or researching the latest security patches for base images.
Dockerfile Optimizer Use Cases
- Reducing container image sizes by migrating from standard distributions to alpine or slim variants.
- Accelerating CI/CD build times through strategic layer reordering and BuildKit cache mounting.
- Hardening production security by implementing non-root users and eliminating build-time secret leaks.
- Transitioning legacy single-stage Dockerfiles to efficient multi-stage build patterns.
How Dockerfile Optimizer Works
- Scans the local workspace to identify all Dockerfiles and analyzes their current layer history and image sizes.
- Evaluates the base image selection and suggests smaller alternatives based on the application runtime requirements.
- Optimizes layer ordering to ensure that frequently changing source code does not invalidate cached dependency layers.
- Audits the configuration for security risks, including root-level execution and missing .dockerignore files.
- Generates a side-by-side comparison report and a fully optimized, production-ready Dockerfile.
Dockerfile Optimizer Setup
To utilize this feature within Openclaw Skills, ensure your project contains a Dockerfile and that the Docker daemon is accessible if you wish to perform size audits.
# The skill will typically search for Dockerfiles using:
find . -name "Dockerfile*" -not -path "*/node_modules/*"
# To analyze image history, the agent may run:
docker history <image_name> --no-trunc
Dockerfile Optimizer Data Schema & Taxonomy
The skill organizes its optimization findings into a structured report to provide clear ROI on changes:
| Component | Description |
|---|---|
| Size Impact | A table comparing current image size vs. projected size after optimization. |
| Critical Issues | A list of high-priority security or performance bottlenecks discovered during the audit. |
| Layer Breakdown | An analysis of which specific RUN or COPY commands contribute most to image bloat. |
| BuildKit Config | Recommendations for persistent cache mounts and secret handling. |
Dockerfile Optimizer Advanced Features
- Multi-stage build refactoring for Node.js, Python, Go, and Rust applications.
- Implementation of BuildKit --mount=type=cache to persist package manager caches (npm, pip, cargo) across builds.
- Automated generation of .dockerignore files to reduce build context overhead.
- Integration of HEALTHCHECK instructions and graceful shutdown signal handling for Kubernetes readiness.
SKILL.md
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