Color Pinboard vs ReadTrace Pro

Color Pinboard is a clean, native iOS client for Pinboard.in — the fast, no-nonsense bookmarking service for people who value the web. BROWSE & SEARCH Your entire Pinboard collection, beautifully rendered on iOS. Search across titles and notes instantly. Infinite scroll with pull-to-refresh keeps your list always up to date. SAVE LINKS INSTANTLY Add bookmarks directly from the app. Set a title, write notes, organize with space-separated tags, and mark items for your Reading List — all in a few taps. IN-APP BROWSER Tap any bookmark to read it without leaving the app. Use the toolbar to jump back to your list, or open the page in Safari with a single tap. TAGS WITH COLOR Every tag gets a consistent color based on its name — the same algorithm as the Pinboard web client. Instantly recognize your collections at a glance. FEEDS Stay curious. Browse Pinboard's Popular feed to discover what the web is reading today, and follow your Network feed to see what people you trust are saving. SWIPE ACTIONS Swipe left on any bookmark to open it in Safari or delete it. Fast, frictionless, and always one swipe away. —— REQUIREMENTS • A Pinboard.in account (pinboard.in — paid bookmarking service) • Your Pinboard API token, found at pinboard.in/settings/password Color Pinboard is an independent project and is not affiliated with Pinboard.in.

A quiet, serif-first read-later app for people who treat long-form articles like books. — Save anything from the web — Tap "share" in Safari, or paste a URL inside the app. ReadTrace pulls out the body and images, strips the chrome, and saves a clean copy to your private library. Once it's saved, the network can vanish. Articles, images, and fonts are cached for fully offline reading. — Read on cream paper — Every article renders in Fraunces — a warm contemporary serif — over a soft cream background that's easier on the eyes than stark white. No ads, no related stories, no tap-to-load-more. The reader remembers your scroll position so you can return weeks later and pick up exactly where you left off. — Organize favorites with collections — Drop favorites into custom buckets — "Work", "Travel", "Things to write about someday". Each collection is its own shelf inside the Favorites tab. Tap a chip to narrow the library; tap it again to clear. — Search what you remember, not what you typed — Built-in semantic search uses Apple's on-device language embeddings to understand intent. Search "AI startups" and find articles about Vibe Coding training camps — no exact keyword required. Combined with literal substring matching across titles, authors, hostnames and tags, you'll find anything you've read. — Auto-tagging via on-device NLP — Every saved article is read once by Apple's NaturalLanguage framework and labeled with 3–5 keyword tags. As your library grows from ten articles to a thousand, tags keep it browsable. — Reading time, done right — Counts Chinese characters and Latin words separately at native reading speeds, so a long bilingual article gets an honest minute estimate instead of an English formula glued onto Chinese prose. — A safety net for what you save — Deleted articles don't vanish. They sit in the Recycle Bin for 30 days, then quietly clear themselves out. Restore anything with one tap — no second-guessing your gestures. — iCloud backup — A single backup file holds every article and every cached image. Restore on a new phone in seconds — fully offline-restorable, no servers to depend on. — Built for privacy — No accounts. No analytics. No tracking pixels. Your reading is between you and your phone. iCloud Drive is the only network endpoint we touch, and only if you choose to back up. — Built for iOS — Safari Share Extension. App Intents. Dynamic Type-aware reader. SwiftData persistence. Light-only by design — the cream palette is the point. — Quietly made — ReadTrace Pro is small. One developer, one design system, one belief: the web is full of writing worth reading carefully, and that writing deserves a calm, paper-feeling home you can return to. For people who want a smaller, quieter library — not an algorithmic feed.