Docker Development

Community

peterbamuhigire

docker-development

Use when containerizing PHP, Python, JavaScript, or API services with Dockerfiles, multi-stage images, Compose, CI builds, runtime permissions, and persistent dependencies.

Overview

Publisher	peterbamuhigire
Repository	`chwezi-dev-engine`
Skill name	`docker-development`
Stars	29
Forks	6
Bundled files	2
License	MIT
Links	Skill source Repository Homepage

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
2 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by peterbamuhigire on GitHub. Read the source before you install it.

Installation

Install the Docker Development AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/peterbamuhigire/chwezi-dev-engine/tree/main/skills/devops-cloud/docker-development
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/peterbamuhigire/chwezi-dev-engine/tree/main/skills/devops-cloud/docker-development

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/peterbamuhigire/chwezi-dev-engine.git /tmp/chwezi-dev-engine
mkdir -p .claude/skills
cp -r /tmp/chwezi-dev-engine/skills/devops-cloud/docker-development .claude/skills/docker-development

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Docker Development in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Docker Development on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Docker Development is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Docker Development

Acknowledgement: Shared by Peter Bamuhigire, techguypeter.com, +256 784 464178.

Use When

Containerizing PHP, Python, Node.js, JavaScript build, API, worker, queue, database, cache, or reverse-proxy services.
Creating or reviewing Dockerfile, compose.yml, CI build, registry, or runtime deployment patterns.
A project needs repeatable development environments, environment parity, production images, or service orchestration.

Do Not Use When

The task only needs application code and has no container, runtime, deployment, or environment concern.
Kubernetes-specific cluster design is the main task; use Kubernetes skills after this container baseline is correct.

Required Inputs

Application stack, local development needs, production runtime, ports, volumes, secrets/config, persistence services, and target OS.
Existing Dockerfile, Compose files, CI scripts, and deployment constraints when available.

Workflow

Identify runtime roles: web, app/FPM, worker, scheduler, database, cache, queue, reverse proxy, asset build, or test runner.
Choose separate development and production image strategies.
Build minimal, reproducible images with pinned base versions and deterministic dependency installation.
Use Docker Compose for local multi-service orchestration, networking, volumes, health checks, and developer commands.
Keep secrets and environment-specific config outside images.
Add CI image build, scan, tag, push, and promotion rules.
Verify startup, health checks, logs, permissions, volume behavior, and graceful shutdown.

Quality Standards

Images are reproducible, minimal, patched, scanned, and tagged with immutable release identifiers.
Development Compose is ergonomic without leaking dev-only tools into production images.
PHP, Python, and Node dependencies are installed deterministically from lockfiles.
Runtime config comes from environment/secrets, not baked source edits.
Containers expose health checks, structured logs, and graceful stop behavior.
Volumes are explicit and do not hide built artifacts unexpectedly.

Anti-Patterns

One container running web server, database, queue worker, and scheduler because it is convenient.
Using latest tags in production.
Copying .env, secrets, test data, or host-specific paths into images.
Installing debug tooling in production images.
Rebuilding separate artifacts per environment instead of promoting one tested image.
Assuming Windows file permissions and Linux container permissions behave the same.

Outputs

Dockerfile/Compose guidance, container architecture notes, review findings, CI image-build plan, or runtime checklist.

References

references/php-python-js-container-delivery.md
references/source-register.md

Evidence Produced

Category	Artifact	Format	Example
Operability	Container build and runtime verification	Command output plus manifest	pinned image, non-root run, health check, dependency failure, scan, and cleanup

Inputs

Input	Required	Purpose
Runtime, build context, and platform	yes	Build image
Dependencies and ports	yes	Define runtime
Secret and persistence boundaries	yes	Avoid embedded state

Degraded mode

If Docker or the target architecture is unavailable, perform static review and provide unverified build commands.

Decision rules

Condition	Action
Build tool not needed at runtime	Use multi-stage build
Process needs persistent state	Mount managed storage
Root is not justified	Redesign permissions

Pair With

php-modern-standards for PHP app/FPM/Composer rules.
python-modern-standards for Python services, workers, and dependency locking.
javascript-modern, nodejs-development, or TypeScript skills for Node/runtime asset builds.
api-design-first for API contract/runtime responsibilities.
deployment-release-engineering for build-once promotion, rollout, and rollback.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Docker Development AI skill do?

Use when containerizing PHP, Python, JavaScript, or API services with Dockerfiles, multi-stage images, Compose, CI builds, runtime permissions, and persistent dependencies.

Why use Docker Development on TypingMind?

Because you install it once and use it with any model. Docker Development is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Docker Development in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/peterbamuhigire/chwezi-dev-engine/tree/main/skills/devops-cloud/docker-development. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Docker Development?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Docker Development?

As many as you like. As long as a model supports skills, you can use Docker Development with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Docker Development AI skill free?

Yes. It is published on GitHub by peterbamuhigire under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Docker Development

Use When

Do Not Use When

Required Inputs

Workflow

Quality Standards

Anti-Patterns

Outputs

References

Evidence Produced

Inputs

Degraded mode

Decision rules

Pair With

Bundled files

Frequently asked questions

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