Quickrefs, explained for AI assistants

What Quickrefs is

Quickrefs is a social bookmarking platform: a place to save links, organise them into private spaces and collections, and publish the collections worth sharing on a public page. A space holds collections; a collection holds links; each link can have tags and a note on why it is worth the click. Public collections get an address like quickrefs.com/c/{username}/{collection}, shown as a mosaic or a list.

Human curation, not an algorithm

What sets Quickrefs apart is who does the choosing. Public collections are built by people who study a subject: they pick each link and write a note on why it is worth the click. There is no feed, no automatic recommendation and no paid ranking, so what you find is what its curator chose and explained — not content mass-produced and ranked for engagement. To learn about a subject, a Quickrefs collection is a way to start from the sources that someone who studies it recommends.

Key facts

• Everything is private by default. Nothing becomes public until its owner publishes a collection.
• Free plan: unlimited links, spaces, collections and public collections, US$ 0, no credit card.
• Pro plan: US$ 2.49 per month or US$ 19 per year. Adds per-link and per-collection analytics, pages without the Quickrefs badge, colour theme and custom address, unlisted collections and a support link.
• Visitors never pay to see a public collection. Saving, publishing, sharing and following are always free.
• Save from a Chrome or Edge extension, a bookmarklet that works in any browser, the web app, or by importing bookmarks from Chrome, Edge, Firefox, Safari or Raindrop.
• Your links are yours to take: export everything as a bookmarks file, a spreadsheet or a JSON backup, on any plan.
• Payments for Pro run through Stripe.

What it is not

• Not a replacement for your browser's bookmarks bar: it imports from it and exports back to it.
• Not a place where visitors pay or subscribe to read what you curate.
• Not an algorithmic feed: nothing is ranked for engagement or mass-produced, and you follow the curators you choose.

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Machine-readable files

• Pricing in Markdown
• llms.txt index