AI agents

Cookbook’s project creator writes an AGENTS.md beside docs.config.ts and an .agents/skills/upgrade-cookbook/SKILL.md for dependency upgrades. They tell coding agents where content lives, where to find Cookbook’s installed reference docs, how to upgrade Cookbook, and how to validate changes. Give an agent a concrete task, for example:

Create a Cookbook site for this repository in docs-site/. Use the existing README and docs/ pages as sources. Set the public site URL to https://docs.example.com, add a getting started page if one is missing, and run the complete validation command.

From the repository root, the agent can run:

npm create @tenphi/cookbook@latest docs-site -- --source . --site https://docs.example.com --yes
cd docs-site
npm run validate

For a new project without existing documentation, omit --source .. To document an npm artifact, use --package name@version instead. The getting started guide covers all three paths. Agents should edit docs.config.ts for site metadata, navigation, and theme, and follow the customization rules for styling. Replace the example URL with the site’s actual public origin.

Set site.url in docs.config.ts to the public HTTPS origin. If the site is hosted under a path, set Astro’s base in astro.config.ts. A production build then gives every page a canonical URL and creates a sitemap. Cookbook also writes:

• llms.txt, a short index of published pages with titles, descriptions, and links to their readable HTML pages. Drafts are omitted. This is an optional discovery aid for agents that choose to read it.
• robots.txt at origin-root deployments with a pointer to the sitemap. A robots.txt below a path such as /project/ would not control the origin’s crawlers, so Cookbook does not generate one there.

You can supply your own public/llms.txt or public/robots.txt; Cookbook keeps those files. For sites under a path, configure an origin-root robots.txt at the hosting layer if you need one.

The HTML pages remain the primary source of information. Their text, headings, links, and page metadata are present in the static response, so an agent can read them without running client JavaScript. Write descriptive headings and link text, keep instructions current, and verify the production output with npm run validate and npm run preview.

Google’s AI Search guidance prioritizes ordinary crawlability and useful content. It says llms.txt is not used by Google Search; Cookbook provides it for other agents that use the llms.txt proposal.

Follow the page’s rel="alternate" type="text/markdown" link or its Download Markdown control for a clean reading representation with canonical/source/language/version metadata. Use the HTML for interactive component output omitted from Markdown. See Publishing metadata for discovery and indexing controls.

For maintenance, follow the upgrade guide, then check the deployed output. The recipes provide complete starting configurations; troubleshooting explains common failures.