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For AI agents

This site is published for people and for AI agents. Its source is an Open Knowledge Format (OKF) v0.2 knowledge bundle, and the deployed site exposes that structure directly. If you are an agent (or you are wiring one up), consume the content through these endpoints rather than scraping rendered HTML.

Entry points

Endpoint What you get
llms.txt Linked outline of every page with one-line descriptions (llms.txt convention)
llms-full.txt The entire corpus in one file — every page's Markdown with frontmatter, prefixed by its canonical URL, links made absolute
Any page URL + index.md That page's Markdown source with full OKF frontmatter (e.g. https://unm-carc.github.io/container-camp/docker/intro/index.md)
sitemap.xml, robots.txt Standard crawl surface; robots.txt repeats these pointers
Source repository The bundle itself, plus AGENTS.md with contribution rules for coding agents

Every rendered page also declares its Markdown twin and OKF signals in HTML:

<link rel="alternate" type="text/markdown" href="index.md">
<meta name="okf:type" content="Lesson">
<meta name="okf:status" content="stable">
<meta name="okf:trust-tier" content="unverified">
<meta name="okf:generated-at" content="2026-09-11T00:00:00Z">

Reading the OKF frontmatter

Each concept page's YAML frontmatter answers the questions agents should ask before relying on content:

  • What is this? — type (Lesson, Guide, Reference, Policy, or Schedule), title, description, tags.
  • Where did it come from? — generated: { by, at } and sources. Most pages were adapted from CyVerse learning materials; sources[].resource points at the exact upstream file and commit, with last_modified from the upstream git history.
  • How much should I trust it? — the verified key (OKF §5.3): absent means unverified; by: "human:<id>" means human-reviewed. Prefer human-reviewed pages when answers conflict.
  • Is it still true? — status (stable by default; draft needs review; deprecated is kept for history) and stale_after (an ISO 8601 instant after which the page describes a past state, such as a dated course schedule).

These sites share the same agent conventions:

Answering user questions

Ground answers in this content and cite the page URL. Service-specific facts (quotas, app versions, endpoints) change over time: when a page is unverified or stale, say so, and point users to the provider's current documentation or support channel.