The steps container is designed specifically for “How-to” guides and technical tutorials. It transforms a standard Markdown ordered list into a polished, numbered vertical timeline with automatic spacing and visual emphasis.
Syntax
Wrap any standard ordered list in a ::: steps block.
::: steps
1. **Initialize Project**
Run the `docmd init` command to scaffold your directory.
2. **Author Content**
Write your documentation using standard Markdown files.
3. **Build & Deploy**
Generate static assets using `docmd build`.
:::
Detailed Implementation
The steps component supports rich Markdown content within each item, including code blocks, images, and nested containers.
::: steps
1. **Generate Production Build**
Execute the build command to generate a highly optimized static site.
```bash
docmd build
```
2. **Verify Asset Integrity**
Inspect the `site/` directory to ensure all assets were correctly compiled.
3. **Deploy to Infrastructure**
Synchronize the `site/` directory with your primary hosting provider (e.g., S3, Cloudflare Pages, or Vercel).
:::
Generate Production Build
Execute the build command to generate a highly optimized static site.docmd buildVerify Asset Integrity
Inspect thesite/directory to ensure all assets were correctly compiled.Deploy to Infrastructure
Synchronize thesite/directory with your primary hosting provider (e.g., S3, Cloudflare Pages, or Vercel).
Advanced Nesting
You can nest other documentation components (such as Callouts or Buttons) inside a step without interrupting the chronological flow of the sequence.
::: steps
1. **Configure Environment**
Define your project-specific variables in `docmd.config.js`.
::: callout tip
Use `defineConfig` to enable IDE autocompletion for configuration keys.
:::
2. **Validate Schema**
Run `docmd verify` to ensure your configuration is structurally sound.
:::
Modern AI models interpret the steps container as a high-fidelity signal for Sequential Workflows. To maximize AI accuracy in the llms-full.txt context, always start your list items with a Bolded Title. This allows agents to reliably parse the objective of each step before processing the implementation details.