Devops
nicepkg/auto-company
Deploy to Cloudflare (Workers, R2, D1), Docker, GCP (Cloud Run, GKE), Kubernetes (kubectl, Helm).
This skill should be used when containerizing applications with Docker, creating Dockerfiles, docker-compose configurations, or deploying containers to various platforms.
Install Docker Containerization
$ npx skills add ailabs-393/ai-labs-claude-skills --skill docker-containerization -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install ailabs-393/ai-labs-claude-skills docker-containerization --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/ailabs-393/ai-labs-claude-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/packages/skills/docker-containerization .claude/skills/docker-containerization && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "docker-containerization" agent skill from https://github.com/ailabs-393/ai-labs-claude-skills/tree/main/packages/skills/docker-containerization into .claude/skills/docker-containerization/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "docker-containerization", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/ailabs-393/ai-labs-claude-skills/tree/main/packages/skills/docker-containerizationType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add ailabs-393/ai-labs-claude-skills --skill docker-containerization -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install ailabs-393/ai-labs-claude-skills docker-containerization --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ailabs-393/ai-labs-claude-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/packages/skills/docker-containerization .agents/skills/docker-containerization && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "docker-containerization" agent skill from https://github.com/ailabs-393/ai-labs-claude-skills/tree/main/packages/skills/docker-containerization into .agents/skills/docker-containerization/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "docker-containerization", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add ailabs-393/ai-labs-claude-skills --skill docker-containerization -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install ailabs-393/ai-labs-claude-skills docker-containerization --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ailabs-393/ai-labs-claude-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/packages/skills/docker-containerization .cursor/skills/docker-containerization && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "docker-containerization" agent skill from https://github.com/ailabs-393/ai-labs-claude-skills/tree/main/packages/skills/docker-containerization into .cursor/skills/docker-containerization/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "docker-containerization", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/ailabs-393/ai-labs-claude-skills.git --path packages/skills/docker-containerization--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add ailabs-393/ai-labs-claude-skills --skill docker-containerization -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install ailabs-393/ai-labs-claude-skills docker-containerization --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ailabs-393/ai-labs-claude-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/packages/skills/docker-containerization .gemini/skills/docker-containerization && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "docker-containerization" agent skill from https://github.com/ailabs-393/ai-labs-claude-skills/tree/main/packages/skills/docker-containerization into .gemini/skills/docker-containerization/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "docker-containerization", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install ailabs-393/ai-labs-claude-skills docker-containerizationInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add ailabs-393/ai-labs-claude-skills --skill docker-containerization -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/ailabs-393/ai-labs-claude-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/packages/skills/docker-containerization .github/skills/docker-containerization && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "docker-containerization" agent skill from https://github.com/ailabs-393/ai-labs-claude-skills/tree/main/packages/skills/docker-containerization into .github/skills/docker-containerization/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "docker-containerization", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add ailabs-393/ai-labs-claude-skills --skill docker-containerization -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install ailabs-393/ai-labs-claude-skills docker-containerization --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ailabs-393/ai-labs-claude-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/packages/skills/docker-containerization .opencode/skills/docker-containerization && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "docker-containerization" agent skill from https://github.com/ailabs-393/ai-labs-claude-skills/tree/main/packages/skills/docker-containerization into .opencode/skills/docker-containerization/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "docker-containerization", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
docker-containerization- GitHub stars
- 454
- Token cost
- ~2.1k tokens
- SKILL.md length
- 739 words
- Files
- 15 (incl. scripts, references, assets)
- Skills in repo
- 22
- Repo updated
- First seen
- Licence
- MIT
At a glance
This skill should be used when containerizing applications with Docker, creating Dockerfiles, docker-compose configurations, or deploying containers to various platforms.
- Works in 10 steps: Dockerfile Generation → Docker Compose Configuration → Bash Scripts for Container Management → …
- Users need Docker configurations
- SKILL.md covers Overview, Core Capabilities, Workflow Decision Tree and Usage Examples, plus 5 more sections
- Runs Shell and JavaScript scripts from its folder; calls docker, kubectl and docker-compose
What it does
Docker Containerization is an agent skill from ailabs-393/ai-labs-claude-skills. This skill should be used when containerizing applications with Docker, creating Dockerfiles, docker-compose configurations, or deploying containers to various platforms. Ideal for Next.js, React, Node.js applications requiring containerization for development, production, or CI/CD pipelines. Use this skill when users need Docker configurations, multi-stage builds, container orchestration, or deployment to Kubernetes, ECS, Cloud Run, etc.
Its SKILL.md is about 2.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 17 other files, including scripts, reference files and assets (for example `assets/docker-compose.yml`, `index.js` and `package.json`).
It sits in DevOps & Cloud, covering Containers. It works with Docker, Kubernetes, Next.js and Cloud Run. The repository describes itself as: This package is use to remove the hustle of finding claudeskills and shift them into any of the user project. This project become a bridge between user's usage and claude skills. The licence is MIT.
When your agent uses it
- Users need Docker configurations
- Multi-stage builds
- Container orchestration
- Deployment to Kubernetes
Example prompts
- “/docker-containerization”
Requirements
- Node.js
- A Bash shell
- Docker
Workflow steps
10 steps, taken from the step headings in SKILL.md.
What it can do on your machine
Read from SKILL.md and the folder at commit 1a12bc7. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships 4 files in scripts/ (Shell and JavaScript), which the agent can run.
Shell commands in SKILL.md call:
dockerkubectldocker-composeaws
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md. Its commands use docker, kubectl and aws, which can reach the network depending on how they are called.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Docker Containerization loads about 2.1k tokens when it runs, and up to ~6.9k if it reads all its reference files. Until then it costs about 117 tokens; SKILL.md has 739 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check: notes
The automated check noted patterns worth knowing about, such as sudo or a known installer.
- NoteMentions a .env fileSKILL.md:53
./docker-run.sh -p 8080:3000 --env-file .env.production
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.
SKILL.md
The full file from ailabs-393/ai-labs-claude-skills at commit 1a12bc7, republished under its MIT licence (© ailabs-393). 739 words, ~2,132 tokens.
Download SKILL.mdSave it as
.claude/skills/docker-containerization/SKILL.md (or your agent's skills folder). This skill also uses 14 other files; get the full folder from GitHub.- name
- docker-containerization
- description
- This skill should be used when containerizing applications with Docker, creating Dockerfiles, docker-compose configurations, or deploying containers to various platforms. Ideal for Next.js, React, Node.js applications requiring containerization for development, production, or CI/CD pipelines. Use this skill when users need Docker configurations, multi-stage builds, container orchestration, or deployment to Kubernetes, ECS, Cloud Run, etc.
Docker Containerization Skill
Overview
Generate production-ready Docker configurations for modern web applications, particularly Next.js and Node.js projects. This skill provides Dockerfiles, docker-compose setups, bash scripts for container management, and comprehensive deployment guides for various orchestration platforms.
Core Capabilities
1. Dockerfile Generation
Create optimized Dockerfiles for different environments:
Production (assets/Dockerfile.production):
- Multi-stage build reducing image size by 85%
- Alpine Linux base (~180MB final image)
- Non-root user execution for security
- Health checks and resource limits
Development (assets/Dockerfile.development):
- Hot reload support
- All dev dependencies included
- Volume mounts for live code updates
Nginx Static (assets/Dockerfile.nginx):
- Static export optimization
- Nginx reverse proxy included
- Smallest possible footprint
2. Docker Compose Configuration
Multi-container orchestration with assets/docker-compose.yml:
- Development and production services
- Network and volume management
- Health checks and logging
- Restart policies
3. Bash Scripts for Container Management
docker-build.sh - Build images with comprehensive options:
./docker-build.sh -e prod -t v1.0.0
./docker-build.sh -n my-app --no-cache --platform linux/amd64docker-run.sh - Run containers with full configuration:
./docker-run.sh -i my-app -t v1.0.0 -d
./docker-run.sh -p 8080:3000 --env-file .env.productiondocker-push.sh - Push to registries (Docker Hub, ECR, GCR, ACR):
./docker-push.sh -n my-app -t v1.0.0 --repo username/my-app
./docker-push.sh -r gcr.io/project --repo my-app --also-tag stabledocker-cleanup.sh - Free disk space:
./docker-cleanup.sh --all --dry-run # Preview cleanup
./docker-cleanup.sh --containers --images # Clean specific resources4. Configuration Files
.dockerignore: Excludes unnecessary files (node_modules, .git, logs)nginx.conf: Production-ready Nginx configuration with compression, caching, security headers
5. Reference Documentation
docker-best-practices.md covers:
- Multi-stage builds explained
- Image optimization techniques (50-85% size reduction)
- Security best practices (non-root users, vulnerability scanning)
- Performance optimization
- Health checks and logging
- Troubleshooting guide
container-orchestration.md covers deployment to:
- Docker Compose (local development)
- Kubernetes (enterprise scale with auto-scaling)
- Amazon ECS (AWS-native orchestration)
- Google Cloud Run (serverless containers)
- Azure Container Instances
- Digital Ocean App Platform
Includes configuration examples, commands, auto-scaling setup, and monitoring.
Workflow Decision Tree
1. What environment?
- Development →
Dockerfile.development(hot reload, all dependencies) - Production →
Dockerfile.production(minimal, secure, optimized) - Static Export →
Dockerfile.nginx(smallest footprint)
2. Single or Multi-container?
- Single → Generate Dockerfile only
- Multi → Generate
docker-compose.yml(app + database, microservices)
3. Which registry?
- Docker Hub →
docker.io/username/image - AWS ECR →
123456789012.dkr.ecr.region.amazonaws.com/image - Google GCR →
gcr.io/project-id/image - Azure ACR →
registry.azurecr.io/image
4. Deployment platform?
- Kubernetes → See
references/container-orchestration.mdK8s section - ECS → See ECS task definition examples
- Cloud Run → See deployment commands
- Docker Compose → Use provided compose file
5. Optimizations needed?
- Image size → Multi-stage builds, Alpine base
- Build speed → Layer caching, BuildKit
- Security → Non-root user, vulnerability scanning
- Performance → Resource limits, health checks
Usage Examples
Example 1: Containerize Next.js App for Production
User: "Containerize my Next.js app for production"
Steps:
- Copy
assets/Dockerfile.productionto project root asDockerfile - Copy
assets/.dockerignoreto project root - Build:
./docker-build.sh -e prod -n my-app -t v1.0.0 - Test:
./docker-run.sh -i my-app -t v1.0.0 -p 3000:3000 -d - Push:
./docker-push.sh -n my-app -t v1.0.0 --repo username/my-app
Example 2: Development with Docker Compose
User: "Set up Docker Compose for local development"
Steps:
- Copy
assets/Dockerfile.developmentandassets/docker-compose.ymlto project - Customize services in docker-compose.yml
- Start:
docker-compose up -d - Logs:
docker-compose logs -f app-dev
Show full SKILL.md (304 more words)Show less
Example 3: Deploy to Kubernetes
User: "Deploy my containerized app to Kubernetes"
Steps:
- Build and push image to registry
- Review
references/container-orchestration.mdKubernetes section - Create K8s manifests (deployment, service, ingress)
- Apply:
kubectl apply -f deployment.yaml - Verify:
kubectl get pods && kubectl logs -f deployment/app
Example 4: Deploy to AWS ECS
User: "Deploy to AWS ECS Fargate"
Steps:
- Build and push to ECR
- Review
references/container-orchestration.mdECS section - Create task definition JSON
- Register:
aws ecs register-task-definition --cli-input-json file://task-def.json - Create service:
aws ecs create-service --cluster my-cluster --service-name app --desired-count 3
Best Practices
Security
✅ Use multi-stage builds for production
✅ Run as non-root user
✅ Use specific image tags (not latest)
✅ Scan for vulnerabilities
✅ Never hardcode secrets
✅ Implement health checks
Performance
✅ Optimize layer caching order ✅ Use Alpine images (~85% smaller) ✅ Enable BuildKit for parallel builds ✅ Set resource limits ✅ Use compression
Maintainability
✅ Add comments for complex steps ✅ Use build arguments for flexibility ✅ Keep Dockerfiles DRY ✅ Version control all configs ✅ Document environment variables
Troubleshooting
Image too large (>500MB) → Use multi-stage builds, Alpine base, comprehensive .dockerignore
Build is slow → Optimize layer caching, use BuildKit, review dependencies
Container exits immediately
→ Check logs: docker logs container-name
→ Verify CMD/ENTRYPOINT, check port conflicts
Changes not reflecting → Rebuild without cache, check .dockerignore, verify volume mounts
Quick Reference
# Build
./docker-build.sh -e prod -t latest
# Run
./docker-run.sh -i app -t latest -d
# Logs
docker logs -f app
# Execute
docker exec -it app sh
# Cleanup
./docker-cleanup.sh --all --dry-run # Preview
./docker-cleanup.sh --all # ExecuteIntegration with CI/CD
GitHub Actions
- run: |
chmod +x docker-build.sh docker-push.sh
./docker-build.sh -e prod -t ${{ github.sha }}
./docker-push.sh -n app -t ${{ github.sha }} --repo username/appGitLab CI
build:
script:
- chmod +x docker-build.sh
- ./docker-build.sh -e prod -t $CI_COMMIT_SHAResources
Scripts (scripts/)
Production-ready bash scripts with comprehensive features:
docker-build.sh- Build images (400+ lines, colorized output)docker-run.sh- Run containers (400+ lines, auto conflict resolution)docker-push.sh- Push to registries (multi-registry support)docker-cleanup.sh- Clean resources (dry-run mode, selective cleanup)
References (references/)
Detailed documentation loaded as needed:
docker-best-practices.md- Comprehensive Docker best practices (~500 lines)container-orchestration.md- Deployment guides for 6+ platforms (~600 lines)
Assets (assets/)
Ready-to-use templates:
Dockerfile.production- Multi-stage production DockerfileDockerfile.development- Development DockerfileDockerfile.nginx- Static export with Nginxdocker-compose.yml- Multi-container orchestration.dockerignore- Optimized exclusion rulesnginx.conf- Production Nginx configuration
© ailabs-393, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 14 other files (scripts, references, assets) in packages/skills/docker-containerization of ailabs-393/ai-labs-claude-skills.
- SKILL.md
- assets/.dockerignore
- assets/Dockerfile.development
- assets/Dockerfile.nginx
- assets/Dockerfile.production
- assets/docker-compose.yml
- assets/nginx.conf
- index.js
- package.json
- references/container-orchestration.md
- references/docker-best-practices.md
- scripts/docker-build.sh
- scripts/docker-cleanup.sh
- scripts/docker-push.sh
- scripts/docker-run.sh
Open the folder on GitHubat commit 1a12bc7
Compare with similar skills
Docker Containerization next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Docker Containerization this skillailabs-393/ai-labs-claude-skills | 454 | — | ~2.1k | Automated safety check: Notes | MIT | |
| Devopsnicepkg/auto-company | 192 | 2 repos | ~814 | Automated safety check: Pass | MIT | |
| CI/CD Pipeline Principlesirahardianto/awesome-agv | 157 | — | ~2.7k | Automated safety check: Notes | MIT | |
| Deploy To Tempsgotempsh/temps | 822 | — | ~1.3k | Automated safety check: Notes | Apache-2.0 | |
| Nestjs DeploymentHoangNguyen0403/agent-skills-standard | 570 | — | ~692 | Automated safety check: Pass | MIT | |
| Containerization AssistantArabelaTso/Skills-4-SE | 253 | — | ~2.9k | Automated safety check: Notes | Apache-2.0 |
Similar skills
CI/CD Pipeline Principles
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Rules for designing CI/CD pipelines in layers: universal lint, test and scan stages, container builds with SBOM attestation, and GitOps for orchestrated deployments.
Deploy To Temps
gotempsh/temps
Deploy applications to the Temps platform with automatic framework detection, Dockerfile generation, and container orchestration.
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Containerization Assistant
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Questions about Docker Containerization
What does Docker Containerization do?
This skill should be used when containerizing applications with Docker, creating Dockerfiles, docker-compose configurations, or deploying containers to various platforms. Docker Containerization is an agent skill from ailabs-393/ai-labs-claude-skills. This skill should be used when containerizing applications with Docker, creating Dockerfiles, docker-compose configurations, or deploying containers to various platforms.
When should I use Docker Containerization?
Docker Containerization fits situations like: users need Docker configurations; multi-stage builds; container orchestration; deployment to Kubernetes.
How do I install Docker Containerization in Claude Code?
Run `npx skills add ailabs-393/ai-labs-claude-skills --skill docker-containerization -a claude-code`. Or copy the skill folder (packages/skills/docker-containerization in ailabs-393/ai-labs-claude-skills) into .claude/skills/docker-containerization in your project. Claude Code loads it when a task matches its description.
How do I install Docker Containerization in Codex?
Run `npx skills add ailabs-393/ai-labs-claude-skills --skill docker-containerization -a codex`. Or copy the skill folder (packages/skills/docker-containerization in ailabs-393/ai-labs-claude-skills) into .agents/skills/docker-containerization in your project. Codex loads it when a task matches its description.
Can I use Docker Containerization in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add ailabs-393/ai-labs-claude-skills --skill docker-containerization -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/docker-containerization, .gemini/skills/docker-containerization, .github/skills/docker-containerization and .opencode/skills/docker-containerization in your project.
What does Docker Containerization need to run?
Going by SKILL.md and its folder, Docker Containerization needs a shell and JavaScript for the scripts in its folder and the command-line tools its instructions call (docker, kubectl, docker-compose and aws). Our summary lists: Node.js; A Bash shell; Docker.
Does Docker Containerization access the network?
SKILL.md contains no URLs. Its commands use docker, which can reach the network depending on how they are called. This is read from the text; nothing was executed.
Is Docker Containerization safe to install?
Our automated static check of SKILL.md found notes only (mentions a .env file), nothing it rates as a warning. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
What licence does Docker Containerization use?
Docker Containerization is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Docker Containerization use?
About 2.1k tokens (SKILL.md is roughly 8.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 4.7k tokens, read only when the agent opens those files.
What are the alternatives to Docker Containerization?
Skills that share tags, products or a category with Docker Containerization: Devops (nicepkg/auto-company, 192 stars), CI/CD Pipeline Principles (irahardianto/awesome-agv, 157 stars), Deploy To Temps (gotempsh/temps, 822 stars) and Nestjs Deployment (HoangNguyen0403/agent-skills-standard, 570 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Docker Containerization?
ailabs-393 (a GitHub user) maintains it in ailabs-393/ai-labs-claude-skills, which has 454 GitHub stars. The repository holds 22 skills in this directory. The repository was last updated on November 11, 2025.
Source: ailabs-393/ai-labs-claude-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.