Build with AI

Sudomimus’s documentation is published in a machine-readable form alongside the human-facing pages. If your editor or chat tool can fetch a URL, you can hand the whole docs corpus to your AI assistant in one shot and let it write the integration code for your stack — in one message, not a copy-paste marathon.

The one-shot prompt

Paste this into Claude, Cursor, ChatGPT, or any AI tool with web access, filling in the angle-bracketed parts:

Read https://docs.sudomimus.com/llms-full.txt and integrate Sudomimus
authentication into my application.

Stack: <your stack, e.g. Next.js 14 + Drizzle + Postgres>
Auth methods: <e.g. passkeys + email OTP>
Application anchor: <your-application>
Callback URL: <your callback URL>

The assistant reads the full corpus and writes the integration. The docs describe the protocol; you supply the surrounding context — your framework, your auth methods, your anchor.

If the assistant needs to operate your Sudomimus account or developer settings while it works, give it the Sudomimus CLI instead of browser instructions. The CLI exposes login, session, and account commands in a form an agent can call directly.

Where to go next

• What to feed your AI — the machine-readable endpoints (llms.txt, the abridged and full corpora, per-page Markdown) and the OpenAPI reference, with guidance on which to use when.
• Driving your AI assistant — tool-specific tips for Claude, Cursor, ChatGPT and others, and how to get better integration code out of them.
• Sudomimus CLI for AI agents — the command-line control surface for account checks, local automation, and future developer operations.

Why this works

Everything an integrator needs is in the docs: the choice between Connect, OIDC, and native direct-issue; their protocol flows; the shared identity model; and the three-layer rule model. An assistant with the corpus in context has the same material a human integrator reads — so it can both write the code and answer follow-up questions without re-fetching.