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Wiki — API Reference (endpoints · params)

A Stripe-style REST API reference page for the fictional Aurora DB service, with a persistent left nav of resources and endpoints, a readable main column, and a sticky dark code panel. Each endpoint block pairs an HTTP method badge and path with a parameters table and a responses section of status badges. The panel offers cURL, JavaScript and Python tabs, copy buttons, and a collapsible JSON response tree. JS adds an endpoint filter, a required-only param toggle, deep-link anchors and TOC scrollspy.

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API Reference (endpoints · params)

A complete REST API reference view for Aurora DB, a fictional distributed database, built in the clean white knowledge-base palette. A persistent left sidebar groups resources and endpoints — Clusters, Snapshots and reference topics — each entry carrying a coloured GET / POST / DELETE method chip. The centered main column documents real-feeling endpoints: an HTTP method badge and path, a description, a parameters table (name, type, required, description) and a responses section of 2xx / 4xx / 5xx status badges, alongside callouts and code blocks.

A sticky dark code panel rides the right rail. Language tabs switch the request example between cURL, JavaScript and Python, copy buttons lift either the request or the response to the clipboard, and the sample JSON response renders as a fully collapsible tree — every object and array node can be folded to a one-line summary. Each parameters table has a required-only toggle that filters the rows, and every endpoint head exposes a deep-link anchor you can copy.

Navigation is wired throughout: the left nav doubles as an endpoint filter (press / to jump to it), clicks smooth-scroll and move focus, and an IntersectionObserver scrollspy highlights the endpoint you are reading while keeping its nav entry in view. The sidebar collapses into a drawer below 820px, the code panel drops beneath the prose on tablets, and everything runs on vanilla JS with no frameworks or build step.

Illustrative UI only — fictional articles, products, and data.