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Workflow Setup

Community
athola
workflow-setup

Configures GitHub Actions CI/CD workflows for testing, linting, and deployment. Use when setting up automation for a Python, Rust, or TypeScript project.

Overview

Publisherathola
Repositoryclaude-night-market
Skill nameworkflow-setup
Stars
343
Forks
37
Bundled files
Instructions only
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.

  • Self-contained

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

  • Open source

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

Installation

Install the Workflow Setup 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/athola/claude-night-market/tree/master/plugins/attune/skills/workflow-setup
  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/athola/claude-night-market.git /tmp/claude-night-market
mkdir -p .claude/skills
cp -r /tmp/claude-night-market/plugins/attune/skills/workflow-setup .claude/skills/workflow-setup
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Workflow Setup 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 Workflow Setup 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 Workflow Setup 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.

Workflow Setup Skill

Set up GitHub Actions workflows for continuous integration and deployment.

When To Use

  • Need CI/CD for a new project
  • Adding missing workflows to existing project
  • Updating workflow versions to latest
  • Automating testing and quality checks
  • Setting up deployment pipelines

When NOT To Use

  • GitHub Actions workflows already configured and current
  • Project uses different CI platform (GitLab CI, CircleCI, etc.)
  • Not hosted on GitHub
  • Use /attune:upgrade-project instead for updating existing workflows

Standard Workflows

Python Workflows

  1. test.yml - Run pytest on push/PR
  2. lint.yml - Run ruff linting
  3. typecheck.yml - Run mypy type checking
  4. publish.yml - Publish to PyPI on release

Rust Workflows

  1. ci.yml - Combined test/lint/check workflow
  2. release.yml - Build and publish releases

TypeScript Workflows

  1. test.yml - Run Jest tests
  2. lint.yml - Run ESLint
  3. build.yml - Build for production
  4. deploy.yml - Deploy to hosting (Vercel, Netlify, etc.)

Workflow

1. Check Existing Workflows

bash
ls -la .github/workflows/

Verification: Run the command with --help flag to verify availability.

2. Identify Missing Workflows

python
from project_detector import ProjectDetector

detector = ProjectDetector(Path.cwd())
language = detector.detect_language()

required_workflows = {
    "python": ["test.yml", "lint.yml", "typecheck.yml"],
    "rust": ["ci.yml"],
    "typescript": ["test.yml", "lint.yml", "build.yml"],
}

missing = detector.get_missing_configurations(language)

Verification: Run pytest -v to verify tests pass.

3. Render Workflow Templates

python
workflows_dir = Path(".github/workflows")
workflows_dir.mkdir(parents=True, exist_ok=True)

for workflow in required_workflows[language]:
    template = templates_dir / language / "workflows" / f"{workflow}.template"
    output = workflows_dir / workflow

    engine.render_file(template, output)
    print(f"✓ Created: {output}")

Verification: Run the command with --help flag to verify availability.

4. Validate Workflows

bash
# Syntax check (requires act or gh CLI)
gh workflow list

# Or manually check YAML syntax
python3 -c "import yaml; yaml.safe_load(open('.github/workflows/test.yml'))"

Verification: Run pytest -v to verify tests pass.

Workflow Best Practices

Use Latest Action Versions

yaml
# Good - pinned to major version
- uses: actions/checkout@v4
- uses: actions/setup-python@v5

# Avoid - unpinned or outdated
- uses: actions/checkout@v2
- uses: actions/setup-python@latest

Verification: Run pytest -v to verify tests pass.

Matrix Testing (Python)

yaml
strategy:
  matrix:
    python-version: ["3.10", "3.11", "3.12"]
    os: [ubuntu-latest, macos-latest, windows-latest]

Verification: Run pytest -v to verify tests pass.

Caching Dependencies

yaml
- uses: actions/setup-python@v5
  with:
    python-version: '3.10'
    cache: 'pip'  # Cache pip dependencies

Verification: Run python --version to verify Python environment.

Shell Script Safety in Workflows

When writing inline shell scripts in workflows, ensure proper exit code handling:

yaml
# BAD - pipeline masks exit code
- run: |
    make typecheck 2>&1 | grep -v "^make\["
    echo "Typecheck passed"  # Runs even if make failed!

# GOOD - use pipefail
- run: |
    set -eo pipefail
    make typecheck 2>&1 | grep -v "^make\["

# GOOD - capture exit code explicitly
- run: |
    output=$(make typecheck 2>&1) || exit_code=$?
    echo "$output" | grep -v "^make\[" || true
    exit ${exit_code:-0}

For complex wrapper scripts, run /pensive:shell-review before integrating.

Updating Workflows

To update workflows to latest versions:

bash
/attune:upgrade-project --component workflows

Verification: Run the command with --help flag to verify availability.

Related Skills

  • Skill(attune:project-init) - Full project initialization
  • Skill(sanctum:pr-prep) - PR preparation with CI checks

Exit Criteria

  • All required workflow files for the detected language exist under .github/workflows/ (Python: test.yml + lint.yml + typecheck.yml; Rust: ci.yml; TypeScript: test.yml + lint.yml + build.yml) and contain valid YAML syntax verified by python3 -c "import yaml; yaml.safe_load(open('...'))".
  • gh workflow list returns each created workflow file as an entry, confirming GitHub recognizes the workflow definitions.
  • Any inline shell script in a workflow uses set -eo pipefail or explicit exit-code capture; pipeline-masked failures (cmd | grep) without pipefail are flagged as errors.
  • If the project uses a CI platform other than GitHub Actions (GitLab CI, CircleCI), the skill reports this incompatibility and stops rather than generating GitHub-specific files.

Frequently asked questions

What does the Workflow Setup AI skill do?

Configures GitHub Actions CI/CD workflows for testing, linting, and deployment. Use when setting up automation for a Python, Rust, or TypeScript project.

Why use Workflow Setup on TypingMind?

Because you install it once and use it with any model. Workflow Setup 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 Workflow Setup in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/athola/claude-night-market/tree/master/plugins/attune/skills/workflow-setup. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Workflow Setup?

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 Workflow Setup?

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

Is the Workflow Setup AI skill free?

Yes. It is published on GitHub by athola 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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