Added Markdown Checking (#39)

* Markdown Checks

* Added Markdown Checks

* Fixes MD

.github/workflows/linting.yml

@@ -0,0 +1,37 @@
+name: Perform markdown linting
+on:
+  workflow_dispatch:
+  push:
+    branches:
+      - main
+    paths-ignore:
+      - '.github/**'
+      - 'README.md'
+      - 'LICENSE'
+      - '.gitignore'
+      - '.gitattributes'
+      - '.editorconfig'
+  pull_request:
+    branches:
+      - main
+    paths-ignore:
+      - '.github/**'
+      - 'README.md'
+      - 'LICENSE'
+      - '.gitignore'
+      - '.gitattributes'
+      - '.editorconfig'
+
+jobs:
+  lint:
+    runs-on: ubuntu-20.04
+    steps:
+      - name: Clone this repo
+        uses: actions/checkout@v4
+
+      - name: Markdown Linting Action
+        id: lint
+        uses: avto-dev/[email protected]
+        with:
+          config: "./.markdownlint.yml"
+          args: "./services/**/*.md"

.markdownlint.yml

@@ -0,0 +1 @@
+{ "default": true, "MD013": false, "MD033": false }

services/jellyfin/README.md

@@ -1,10 +1,10 @@
 # Jellyfin with Tailscale Sidecar Configuration
 
-This Docker Compose configuration sets up [Jellyfin] (https://github.com/jellyfin/jellyfin) with Tailscale as a sidecar container to securely manage and access your media server over a private Tailscale network. By using Tailscale in a sidecar configuration, you can enhance the security and privacy of your Jellyfin instance, ensuring that it is only accessible within your Tailscale network.
+This Docker Compose configuration sets up [Jellyfin](https://github.com/jellyfin/jellyfin) with Tailscale as a sidecar container to securely manage and access your media server over a private Tailscale network. By using Tailscale in a sidecar configuration, you can enhance the security and privacy of your Jellyfin instance, ensuring that it is only accessible within your Tailscale network.
 
 ## Jellyfin
 
-[Jellyfin] (https://github.com/jellyfin/jellyfin) is an open-source, self-hosted media server that allows you to manage and stream your media collection, including movies, TV shows, music, and more, to various devices. It provides a rich user interface and supports multiple clients, making it a powerful alternative to other media server solutions. This configuration leverages Tailscale to securely connect to your Jellyfin instance, ensuring that your media server interface is protected from unauthorized access and that your instance is accessible only via your private Tailscale network.
+[Jellyfin](https://github.com/jellyfin/jellyfin) is an open-source, self-hosted media server that allows you to manage and stream your media collection, including movies, TV shows, music, and more, to various devices. It provides a rich user interface and supports multiple clients, making it a powerful alternative to other media server solutions. This configuration leverages Tailscale to securely connect to your Jellyfin instance, ensuring that your media server interface is protected from unauthorized access and that your instance is accessible only via your private Tailscale network.
 
 ## Configuration Overview
 

services/languagetool/README.md

@@ -6,7 +6,6 @@ This Docker Compose configuration sets up [LanguageTool](https://languagetool.or
 
 [LanguageTool](https://languagetool.org) is a powerful grammar and spell-checking tool available for various languages. It can be used in various applications, including web browsers, office suites, and as a standalone server for integration with other services.
 
-
 ## Configuration Overview
 
 In this setup, the `tailscale-adguardhome` service runs Tailscale, which manages secure networking for LanguageTool. The `languagetool` service utilizes the Tailscale network stack via Docker's `network_mode: service:`. This setup ensures that LanguageTool's service is only accessible through the Tailscale network (or locally, if preferred), providing an extra layer of security and privacy for your LanguageTool deployment.
@@ -19,7 +18,7 @@ In this setup, the `tailscale-adguardhome` service runs Tailscale, which manages
 
 [Download](http://languagetool.org/download/ngram-data/) the n-gram dataset(s) onto your local machine and unzip them into a local ngrams directory:
 
-```
+```plain
 home/
 ├─ /
 │  ├─ ngrams/
@@ -33,4 +32,4 @@ home/
 │  │  │  ├─ 3grams/
 ```
 
-Mount the local ngrams directory to the `/ngrams` directory in the Docker container [using the `-v` configuration](https://docs.docker.com/engine/reference/commandline/container_run/#read-only) and set the `languageModel` configuration to the `/ngrams` folder.
+Mount the local ngrams directory to the `/ngrams` directory in the Docker container [using the `-v` configuration](https://docs.docker.com/engine/reference/commandline/container_run/#read-only) and set the `languageModel` configuration to the `/ngrams` folder.