Vue Mess Detector Action

A static code analysis tool for detecting code smells and best practice violations in Vue.js and Nuxt.js projects.

Easily integrate Vue Mess Detector into your CI pipeline to receive pull request alerts and display badges effortlessly.

Preview

Installation

Tip

Reference: How to Use Vue Mess Detector

You can add this action as a step in your GitHub Actions workflow. Here's an example of how to use it:

name: VMD Analysis

on:
  workflow_dispatch:
  pull_request:
    branches:
      - main
  push:
    branches:
      - main

permissions:
  contents: read
  pull-requests: write

jobs:
  detect-mess:
    runs-on: ubuntu-latest
    name: Detect Vue Mess
    steps:
      - name: Checkout
        uses: actions/checkout@v4

      - name: Set up Node.js
        uses: actions/setup-node@v4
        with:
          node-version: '20'

      - name: Vue Mess Detector Analysis
        uses: brenoepics/vmd-action@v0.0.5
        # with:
          # check inputs for full args list

Usage

After installing the vmd-action, Once a pull request is opened, you will start receiving comments and report artifacts.

Inputs

Tip

You can find the list of inputs and their descriptions in the action.yml file.

Input	Description	Required	Default
github-token	GitHub token for commenting on pull requests	false
version	Version of Vue Mess Detector	true	latest
skipInstall	Skip the installation of Vue Mess Detector	true	false
skipBots	Skip running analysis on pull requests from bots	true	true
commentsEnabled	Comment on Pull requests?	true	true
packageManager	Package manager to use	false	(detect)
runArgs	Arguments to pass to Vue Mess Detector	false	--group=file
entryPoint	Entry point for Vue Mess Detector	false	./
srcDir	Source directory to analyze	true	src/
deleteOldComments	Delete old report comments on pull requests?	false	false
relativeMode	Compare the current branch with the target (PR only)	true	true

Contributing

We welcome contributions to this project! Please read our Contributing Guide for more information on how to contribute.

If you've found this project useful, please consider giving it a ⭐ on GitHub. This helps to spread the awareness of the project and is a great way to show your support!

License

This project is licensed under the MIT License.