Static, no-build landing page for the Netresearch Agent Engineering System — how real agent sessions become durable, verifiable, distributable engineering knowledge (retro → skills → checkpoints → harness → distribution).
Live: https://netresearch.github.io/agent-engineering/ (German) · https://netresearch.github.io/agent-engineering/en/ (English)
public/index.html— complete German page, styles, search, theme switching, JSON-LD, local ChromeLanguageModelQ&A and deterministic search fallbackpublic/en/index.html— English version, same structure; keep content in sync with the German pagepublic/og-image.png,public/og-image-en.png— social previews, rendered fromscripts/og-template*.html(npm run og)public/robots.txt,public/sitemap.xmlpublic/llms.txt— compact machine-readable knowledge summary
No external JavaScript, CSS, analytics, tracking or font request. The CSS declares Netresearch's Raleway/Open Sans typography with system fallbacks.
The Q&A feature uses globalThis.LanguageModel when Chrome exposes the
built-in Prompt API. It checks availability() without creating a model
session; a session is created only after a visitor submits a question. The
system prompt contains a compact extraction of this page and requires answers
to use that source only. If the API or model is unavailable, the UI does not
fake an AI response — it returns the highest-scoring relevant sections of the
same page instead.
python3 scripts/verify_site.py # markup-decidable gate
npm ci --ignore-scripts && npm run axe # WCAG 2.1 AA, real browser, light + dark
verify_site.py checks: one h1, heading order, unique IDs, accessible
controls, canonical/OG/JSON-LD, no broken internal links, no third-party
requests, and that robots.txt, sitemap.xml and llms.txt agree with the
page about the base URL and section anchors.
Every push to main runs both gates and publishes public/ via
.github/workflows/pages.yml (org-reusable pages-build/pages-deploy
workflows). A red gate blocks the deploy.