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CLUSTER KEYBOARD-PHOTOGRAPHERS-PHOTOS · 4 ENTRIES · EARLIEST ENTRY 2025-08-04

Keyboard-first photo culling tools

This cluster consists of desktop/macOS apps for photographers to cull photos quickly by making keyboard-driven keep/delete decisions, including a game-like sorting workflow and burst-grouped RAW keeper selection. Its dated history is too thin to read a shape from: only one dated entry exists before the index start, so it either predates the index or its members are undated. Firstcut leads on traction with 1 star; siftroll-ios-app and flick have 0 stars.

Entry timeline

ENTRY TIMELINE

AUG 2025: 1SEP 2026: 2OCT 2026: 1
AUG 2025OCT 2026

Each bar is the month a member carries, which is a creation date where the source published one and a crawl date otherwise. Nothing in the index was found before 11 August 2026, and coverage broadened sharply on 14–15 August, so a bar from then on reports how much we found that month, not how much was built; an earlier bar reports how far back a member's own source dated it — not how long we have been watching.

Members by activity

Activity signals, not revenue.

Build origin · 1 ai-built · 3 unlabelled

Operator · 4 hobby

Two labels per entry, never collapsed into one: how it was built, and who stands behind it. Counted over the 4 listed below. Unlabelled means nothing has decided yet — not that the answer is small.

  1. 01Firstcut1★20 days—hobbymacOS app that groups RAW photos from a shoot into bursts and lets photographers select keepers using the keyboard.
  2. 02siftroll-ios-app0★24 dayslivehobbyPhoto sorting app that displays camera roll photos as cards and lets users swipe right to keep or left to delete in batches.
  3. 03flick0★11 dayslivehobbyDesktop app for macOS that helps photographers quickly cull photos from a folder or camera card using keyboard keep and delete decisions.
  4. 04VibeCulling22★1 yrabandoned—ai-builthobbyDesktop application that helps photographers rapidly sort and delete photos using keyboard shortcuts in a game-like workflow.

Ranked by traction, highest first, and paged 20 at a time — this is a window on the cluster, never the whole of it. Ties are broken by a stable id so a product cannot appear on two pages or fall between them. Browse every cluster.