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Emdash Github Actions

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jdevalk
emdash-github-actions

Sets up GitHub Actions CI/CD workflows for EmDash plugins — TypeScript type-checking, ESLint linting, Vitest testing, npm publishing, and automated releases. ALWAYS use this skill when a user wants to create, add, set up, or configure GitHub Actions, CI/CD, automated checks, or deployment workflows for an EmDash plugin — even if they don't use the exact phrase "GitHub Actions". This includes any request to: add automated type-checking or linting to an EmDash plugin repo; set up testing in CI for a plugin; auto-publish a plugin to npm from GitHub; add security scanning or dependency auditing to a plugin pipeline; or generally "add CI", "add automated checks", "set up workflows", or "automate" anything related to an EmDash plugin's GitHub repository. Also trigger when someone wants quality gates on PRs or is setting up a new EmDash plugin repo and wants best practices for automation. If the user is inside an EmDash plugin repository and mentions anything about automated testing, code quality, deployment, or GitHub workflows, use this skill.

Overview

Publisherjdevalk
Repositoryskills
Skill nameemdash-github-actions
Stars
109
Forks
10
Bundled files
1
LicenseMIT
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.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by jdevalk on GitHub. Read the source before you install it.

Installation

Install the Emdash Github Actions 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/jdevalk/skills/tree/main/emdash-github-actions
  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/jdevalk/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/emdash-github-actions .claude/skills/emdash-github-actions
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Emdash Github Actions 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 Emdash Github Actions 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 Emdash Github Actions 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.

EmDash Plugin GitHub Actions

This skill helps you set up a comprehensive CI/CD pipeline for EmDash plugins using GitHub Actions. EmDash is a full-stack TypeScript CMS based on Astro, so its plugin ecosystem is entirely TypeScript-based.

What this skill covers

There are several categories of workflows that a healthy EmDash plugin should have. Not every plugin needs all of them — the right mix depends on the plugin's complexity, whether it has a React admin UI, whether it has tests, etc. Your job is to figure out which ones are relevant and set them up.

The workflows fall into these categories:

  1. Type checking — TypeScript strict mode with emdash peer dependency
  2. Code quality — ESLint with TypeScript support
  3. Testing — Vitest or similar TypeScript-native test runner
  4. Security — npm audit for dependency vulnerabilities
  5. Deployment — Automated npm publish on tag/release

Read references/workflows.md for the detailed configuration of each workflow, including ready-to-use YAML templates and configuration files.

How to approach a request

Step 1: Understand the plugin

Before writing any workflow files, figure out what you're working with:

  • What does the plugin do? Check the package.json description and src/index.ts exports. EmDash plugins typically hook into page:metadata, page:fragment, content hooks, or provide admin UI.
  • Does it have a React admin UI? Check for .tsx files or admin.tsx. If yes, the type-check needs @types/react and --jsx react-jsx.
  • Does it have tests? Check for a tests/ or __tests__/ directory, or a vitest.config.ts. If yes, set up the test workflow. If not, mention that adding tests would be valuable but don't force it.
  • What are its peer dependencies? Check package.json for peerDependencies. EmDash plugins always depend on emdash and may depend on react, astro, etc.
  • Does it use additional npm dependencies? Check for dependencies in package.json. If yes, the CI needs an npm install step.
  • Is it published to npm? Check if the package name is scoped (e.g., @org/emdash-plugin-foo) and whether it has a publishConfig. If yes, the deploy workflow is relevant.

Step 2: Recommend a set of workflows

Based on what you found, recommend which workflows to set up. A good default for most plugins:

  • TypeScript type-check (almost always — this is the most valuable check)
  • ESLint (if the plugin has more than a handful of files)
  • npm audit (cheap security check, almost always worth it)

And conditionally:

  • Vitest tests (if tests exist)
  • npm publish (if the plugin is published to npm)

Step 3: Create the workflow files

Create each workflow as a separate YAML file in .github/workflows/. Using separate files rather than one monolithic workflow gives clearer feedback in PRs (each check shows independently) and makes it easier to enable/disable individual checks.

Use the templates from references/workflows.md as starting points, but adapt them to the specific plugin. Common adaptations include:

  • Adding @types/react if the plugin has .tsx files
  • Adding additional peer dependencies that provide types
  • Adjusting file paths for the type-check and lint commands
  • Configuring the npm publish scope and access level

Step 4: Create supporting config files

Depending on which workflows you set up, you may also need:

  • tsconfig.json — TypeScript configuration (if not already present)
  • eslint.config.js — ESLint flat config with TypeScript support
  • vitest.config.ts — Vitest configuration

Step 5: Set up secrets reminder

If you're adding the npm publish workflow, remind the user that they need to configure a repository secret in GitHub:

  • NPM_TOKEN — Their npm access token with publish permissions

Walk them through: Repository Settings > Secrets and variables > Actions > New repository secret.

For scoped packages (@org/package-name), the token must have access to the organization.

Naming conventions

Use descriptive workflow file names that make it obvious what each one does:

  • ci.yml — TypeScript type-checking (the primary CI check)
  • lint.yml — ESLint
  • test.yml — Vitest/test runner
  • security.yml — npm audit
  • publish.yml — npm publish on release

Important details

Node.js version: Use Node.js 22 as the default. EmDash is built on modern TypeScript and Astro, so there's no need to support older Node versions. Use actions/checkout@v5 and actions/setup-node@v5 (v5 runs on Node.js 24 runners, avoiding the Node.js 20 deprecation).

Peer dependency installation: EmDash plugins declare emdash as a peer dependency. For type-checking in CI, you must explicitly install emdash (and @types/react if the plugin has .tsx files) since peer dependencies aren't auto-installed in a standalone plugin repo.

The --skipLibCheck flag: Use --skipLibCheck when running tsc in CI. EmDash and its transitive dependencies may have internal type issues that aren't relevant to the plugin author. --skipLibCheck skips checking .d.ts files while still fully checking the plugin's own source code.

The find command for file discovery: Don't use shell globs like src/**/*.ts in CI commands — they fail when no files match at a given depth. Use $(find src -name '*.ts' -o -name '*.tsx') instead.

Branch naming: Most EmDash plugin repos use main as the default branch. Always check the actual repo and use the correct branch name in workflow triggers.

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 Emdash Github Actions AI skill do?

Sets up GitHub Actions CI/CD workflows for EmDash plugins — TypeScript type-checking, ESLint linting, Vitest testing, npm publishing, and automated releases. ALWAYS use this skill when a user wants to create, add, set up, or configure GitHub Actions, CI/CD, automated checks, or deployment workflows for an EmDash plugin — even if they don't use the exact phrase "GitHub Actions". This includes any request to: add automated type-checking or linting to an EmDash plugin repo; set up testing in CI for a plugin; auto-publish a plugin to npm from GitHub; add security scanning or dependency auditing...

Why use Emdash Github Actions on TypingMind?

Because you install it once and use it with any model. Emdash Github Actions 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 Emdash Github Actions in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/jdevalk/skills/tree/main/emdash-github-actions. 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 Emdash Github Actions?

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 Emdash Github Actions?

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

Is the Emdash Github Actions AI skill free?

Yes. It is published on GitHub by jdevalk 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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