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Generating Julia Package

OrganizationPopular
hashgraph-online
generating-julia-package

Use when you create a JuliaLang package

Overview

Publisherhashgraph-online
Repositoryawesome-codex-plugins
Skill namegenerating-julia-package
Stars
1.3K
Forks
360
Bundled files
Instructions only
LicenseApache-2.0
Links
  • 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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by hashgraph-online on GitHub. Read the source before you install it.

Installation

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

1

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.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/hashgraph-online/awesome-codex-plugins/tree/main/plugins/AtelierArith/atelier-arith-julia-development-skills/skills/generating-julia-package
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

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/hashgraph-online/awesome-codex-plugins.git /tmp/awesome-codex-plugins
mkdir -p .claude/skills
cp -r /tmp/awesome-codex-plugins/plugins/AtelierArith/atelier-arith-julia-development-skills/skills/generating-julia-package .claude/skills/generating-julia-package
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Generating Julia Package 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 Generating Julia Package 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 Generating Julia Package 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.

Creating a Julia Package

Project Environment

If you want to create a simple script that depends on external libraries, you should create a "project environment". This means making a Project.toml file like the one below.

toml
[deps]
"<Installed Package 1>" = "<UUID for Installed Package 1>"
"<Installed Package 2>" = "<UUID for Installed Package 2>"
"<Installed Package 3>" = "<UUID for Installed Package 3>"

To install an external library (for example, TargetPackage), run the following in your terminal:

sh
julia --project -e 'using Pkg; Pkg.add("TargetPackage")'

Package Directory

If you want to create a reusable package or a larger scale script, you should create a "package directory".

Choosing the layout

Default: in-place layout. Create ./Project.toml and ./src/MyPkg.jl directly in the current working directory, with no subdirectory named after the package. Use this whenever the user asks to "create a package MyPkg" without further qualification.

Opt-in: subdirectory layout. Only use this when the user explicitly asks for a subdirectory — for example "create the package under a new directory", "サブディレクトリを作って", "MyPkg/ 配下に作って", or when the user is bootstrapping multiple packages side by side under a single workspace and a subdirectory is necessary to disambiguate them.

Do NOT use Pkg.generate("MyPkg") for the in-place layout — it always creates a subdirectory. The in-place layout is the default and must be produced by hand-writing the files (see the steps below).

In-place layout (default, no subdirectory)

To create Project.toml and src/MyPkg.jl directly in the current working directory:

  1. Generate a UUID for the uuid field of Project.toml:

    sh
    $ julia -E 'using UUIDs; string(uuid4())'
    "43d6671a-6eab-408d-9ef9-8f584d9146fb" # Example output.
  2. Write ./Project.toml with the package name and the UUID from step 1:

    toml
    name = "MyPkg"
    uuid = "43d6671a-6eab-408d-9ef9-8f584d9146fb"
    authors = ["Your Name <you@example.com>"]
    version = "0.1.0"
  3. Write ./src/MyPkg.jl with the module skeleton:

    julia
    module MyPkg
    
    greet() = "Hello"
    
    end # module MyPkg
  4. Verify by loading the package from the current directory:

    sh
    $ julia --project=. -e 'using MyPkg; println(MyPkg.greet())'

Subdirectory layout (opt-in only)

Only use this when the user explicitly asks for it. To create a package named MyPkg under a new subdirectory, run:

sh
$ julia -e 'using Pkg; Pkg.generate("MyPkg")'

This will create:

sh
$ tree
.
└── MyPkg
    ├── Project.toml
    └── src
        └── MyPkg.jl

3 directories, 2 files

Frequently asked questions

What does the Generating Julia Package AI skill do?

Use when you create a JuliaLang package

Why use Generating Julia Package on TypingMind?

Because you install it once and use it with any model. Generating Julia Package 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 Generating Julia Package in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/hashgraph-online/awesome-codex-plugins/tree/main/plugins/AtelierArith/atelier-arith-julia-development-skills/skills/generating-julia-package. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Generating Julia Package?

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 Generating Julia Package?

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

Is the Generating Julia Package AI skill free?

Yes. It is published on GitHub by hashgraph-online under the Apache-2.0 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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