Forem: Daveu1983

Creating my portfolio website using GitHub's Spec-kit

Daveu1983 — Sat, 28 Feb 2026 21:13:05 +0000

For a long time I have wanted to create my own website portfolio. After many failed attempts of trying to write something that looked vaguely good, I read a couple of articles on GitHub's spec-kit and decided to give it a go, the full result can be found at repository, with the site hosted on github pages at portfolio

Spec-kit offers a framework and guideline for your AI tool of choice (many are supported) to build an application.

Prerequisites
Spec-kit is a command line interface tool built in python, and the following should be installed prior to installing the cli tool.

Python
Python package uv

Install
I chose to install the cli tool persistently using the command uv tool install specify-cli --from git+https://github.com/github/spec-kit.git

Creating the project
I did not make the project folder prior, so I navigated to the path were I wanted to create my project folder and used the command specify init

I then got the option to select your AI assistant

I then got the option to define what terminal type to use

The initialisation will run, and hopefully all stages will be green. I have never had this fail before, but hopefully any error message would be easy to resolve

Following that some guidance on what next steps you may want to take is given, note that the project with be initialised with git too.

Developing the application
The first thing I did was to create the constitution.md, this creates the principles and guidance that all future development steps will follow. Mine is pretty simple I stated that this must be a static website only, and must not capture any user data. This can be created using the command /speckit.constitution

I then did four cycles of the specify workflow, the first two I did in December 2025 using Gemini, the second two I did using Claude in February 2026. Specify workflows can be created using /speckit.specify and will be numbered in your repository like
, then the flow is

/speckit.plan to supply your plan for what you want for this feature, you can mention tech and any architecture choices
/speckit.tasks to create a list tasks the AI will action
/speckit.implement to action those tasks, these will then be checked against and create a checklists/requirements.md of what was checked inside each folder.

In between these four feature additions using Spec-kit I edited the content and removed some things I did not like manually. Then at the end I asked the AI to assess the final result against the specs, it detailed four attributes of the website that didn't fit into the specs, rather than change these we documented them in decision record files within the repository.

Conclusion
Using Spec-kit I was able to get a good looking (I think) responsive static website far quicker than I would have been able to without it.
It created detailed markdown files detailing the thought process, how it was going to build the site, what content it would generate, and what technology would be used. I am excited to see what can be built on larger projects.

Hello World with Agent Skills

Daveu1983 — Sun, 22 Feb 2026 21:07:05 +0000

After hearing about Agent skills, I thought I would try it out and where better to start than Hello World!

Agent skills is a way to define a skill that can be given to an agent and it should work with whatever AI tool you are using as it is an open standard. The SKILL.md details what the agent should do when triggered.

Resources used in this work can be found at

With the source code for what I did at https://github.com/Daveu1983/skills-hello-world

The Agent.md

# Agent Instructions

This repository is a collection of Agent Skills — reusable instructions that AI coding agents can load on demand to perform specific tasks.

## Repository structure

skills/<skill-name>/SKILL.md   # Skills (Agent Skills format)
AGENTS.md                              # This file

## Skills format

Skills follow the [Agent Skills](https://agentskills.io) open standard. Each skill is a directory containing a `SKILL.md` file with YAML frontmatter and Markdown instructions.

## Adding a new skill

1. Create a directory under `skills/` named after your skill (lowercase, hyphens only).
2. Add a `SKILL.md` file with valid frontmatter (`name`, `description`) and clear instructions.
3. Keep instructions agent-agnostic — avoid referencing tools specific to a single agent product.
4. Optionally add `scripts/`, `references/`, or `assets/` subdirectories for supporting files.

The hello-world SKILL.md

---
name: hello-world
description: "Generates a working Hello World application in a user-chosen programming language. Asks the user to pick a language, then returns correct source code that prints \"Hello, World!\" to the console. Handles both compiled and interpreted languages correctly."
---

Ask the user which programming language they would like a Hello World application in. Offer a selection of common languages (e.g. Python, JavaScript, TypeScript, Rust, Go, C, C++, Java, C#, Ruby, Swift, Kotlin, Zig) and allow them to specify any other language.

Once the user has chosen a language:

1. Determine whether the language is **compiled** or **interpreted**.
2. Produce a complete, minimal source file that prints exactly `Hello, World!` to standard output (console).
3. The code must be correct and complete — it should compile (for compiled languages) and run without any errors on a standard toolchain with no extra dependencies.
4. Determine the conventional filename for a Hello World program in that language (e.g. `main.go`, `hello.py`, `Main.java`).
5. Write the source code to that file in the root of the current project using the Write tool (or equivalent file-writing tool).
6. Confirm the file was created and show the filename to the user.
7. After creating the file, provide a short "How to run" section that shows the exact shell commands needed to:
   - **Compiled languages**: compile the source file and then run the resulting binary.
   - **Interpreted languages**: run the source file directly with the appropriate interpreter/runtime.

Keep the code idiomatic and minimal — no unnecessary boilerplate beyond what the language requires for a valid runnable program.

Testing it out
When running on Gemini with the instruction run hello-world skill, it initially attempted to run a skill I assume you can set up for Gemini to run globally on your system, when it could not find the skill it asked if I wanted to run the local one it found. After confirmation of this it found the skill.
Through the thought process it decided that I should just be given four options of what language to create a Hello World Application for with the fifth option being another language, this was not prompted by myself and not part of Agent.md or SKILL.md.
I chose Go and it gave me a source code file and instructions to run that were successful.

When running on GitHub CoPilot it found the skill straight away and gave me a free format question with what language I would like it to create the Hello World application for. I typed in Java and it produced a working source code file and instructions to run that were successful. Interestingly the instructions and source code that was given were out of date with new versions of Java, since Java 11 you can run in one line with 'java Main.java', and since Java 25 (preview from 21) you can use the code

void main() {
  System.out.println("Hello World!");
}

CoPilot gave me

The below shows the chat with CoPilot to generate this

Conclusion
Was this the best and most sustainable use of AI probably not! But the results across the two agents I tested were consistent, and working code was produced. Skills are being used widely see https://agents.md/#examples for more details and only likely to become more and more sophisticated in the future.

Switching from docker to podman on Ubuntu

Daveu1983 — Mon, 27 May 2024 11:42:45 +0000

I wanted to switch my local container development tool from docker to podman. The reason is that podman uses pods to link containers together, and the pod specification used is the kubernetes pod specification, making transistioning the apps to Kubernetes easier.

Remove docker

I could not remember how I installed docker so I followed this guide how-to-completely-uninstall-docker.

I ran the command dpkg -l | grep -i docker.

This returned

ii  docker-buildx-plugin                       0.11.2-1~ubuntu.20.04~focal             amd64        Docker Buildx cli plugin.
ii  docker-ce                                  5:24.0.7-1~ubuntu.20.04~focal           amd64        Docker: the open-source application container engine
ii  docker-ce-cli                              5:24.0.7-1~ubuntu.20.04~focal           amd64        Docker CLI: the open-source application container engine
ii  docker-ce-rootless-extras                  5:24.0.7-1~ubuntu.20.04~focal           amd64        Rootless support for Docker.
ii  docker-compose-plugin                      2.21.0-1~ubuntu.20.04~focal             amd64        Docker Compose (V2) plugin for the Docker CLI.

I than ran sudo apt-get purge -y and sudo apt-get purge -y on each of the packages above. Then ran the following commands.

sudo rm -rf /var/lib/docker /etc/docker
sudo rm /etc/apparmor.d/docker
sudo groupdel docker
sudo rm -rf /var/run/docker.sock
sudo rm -rf /var/lib/containerd
sudo rm -r ~/.docker

Install podman

Using the podman documentation I ran the command sudo apt-get -y install podman
From there I ran the commands to check if podman was installed.

$ podman version
Version:      3.4.4
API Version:  3.4.4
Go Version:   go1.18.1
Built:        Thu Jan  1 01:00:00 1970
OS/Arch:      linux/amd64

When running docker commands the following was returned

$ docker ps
Command 'docker' not found, but can be installed with:
sudo snap install docker         # version 24.0.5, or
sudo apt  install podman-docker  # version 3.4.4+ds1-1ubuntu1.22.04.2
sudo apt  install docker.io      # version 24.0.5-0ubuntu1~22.04.1
See 'snap info docker' for additional versions.

However after using docker for a number of years, and the muscle memory kicking in, it would be useful to still be able to use the docker command. Luckily there is a package that can help with this sudo apt-get -y install podman-docker will install a docker emulator.
So running a docker command will now give you this.

$ docker ps
Emulate Docker CLI using podman. Create /etc/containers/nodocker to quiet msg.
CONTAINER ID  IMAGE       COMMAND     CREATED     STATUS      PORTS       NAMES

And as the result suggests you can switch of the message.

$ sudo touch /etc/containers/nodocker
$ docker ps
CONTAINER ID  IMAGE       COMMAND     CREATED     STATUS      PORTS       NAMES

Word of caution, this approach did mean that I lost all local images and containers that I had on my system, so make sure you have saved everything you need prior to making the change.

Hope this helps! I hope to publish more articles about developing apps with podman in the near future.