Stars and mentions
Last 30 days, Oct 4 – Nov 2
Package downloads
Top repositories
onevcat’s repositories ranked by new stars, as on trending.
Contributes to
Repositories outside onevcat’s account where onevcat opened or reviewed pull requests in the past 365 days.
Who noticed onevcat
Everyone who starred or forked onevcat’s repositories since the archive began in 2011.
Notable accounts
Ordered by the stars their own repositories have received.
Biggest fans
Accounts that starred the most of these repositories.
Breakout weeks
Each repository’s best week of new stars, with the release published around it.
- Gold
- 01st place finishes
- Silver
- 12nd place finishes
- Bronze
- 03rd place finishes
- Awarded repositories
- 1Owned by onevcat now
Repositories
Ordered by gold, then silver, then bronze.
- KingfisherBest: 2nd by stars, 346 stars010
Every award
Top-three finishes of these repositories in completed trending days and weeks, newest first.
A repository earns an award for finishing first, second or third in a completed trending day or week, ranked by new stars, new forks or pull request authors. Awards follow a repository through renames and transfers and count toward its current owner. Weeks run Monday to Sunday, UTC.
Mentions
sim-use: Give your AI agent eyes and hands on iOS Simulator and Android emulator/devices (1.5k stars) What it does All text below is quoted directly from the project README. >Give AI agents the ability to observe and act on iOS Simulator and Android emulator / device screens. Why sim-use: - Token-efficient. The outline representation is ~16x more compact than a raw JSON accessibility tree. An LLM can read and reason about an entire screen in a few hundred tokens. - Nothing hidden. sim-use walks the full accessibility tree including WebViews, system overlays, and embedded content, no elements are silently skipped. - AI-native. Designed from day one for agent loops, not human testers. Alias-cached taps (@N), structured --json envelopes with actionable hint fields on errors, and a bundled agent skill (sim-use init --client claude) that teaches your AI client the full command surface. - Fast. A per-device background daemon amortises init cost across calls. After the first command, each observe-act round trip completes in ~300 ms. - Cross-platform. One command surface drives both iOS Simulator and Android emulator/device. Same verbs, same flags, same --json shape: write one agent loop that works on both. >brew install lycorp-jp/tap/sim-use Repository lycorp-jp/sim-use Repository stats |Metric|Value| |:-|:-| |Stars|1,452| |Forks|104| |Last release|v0.16.0 (2026-10-21)| |Languages|Swift 89.4%, Shell 4.7%, Kotlin 3.5%| |Contributors|17| |AI contributor accounts (Claude / Codex / Cursor / Copilot)|claude: 75| |AI co-authored commits|Claude: 268| Main contributor |Field|Value| |:-|:-| |Name|Wei Wang| |GitHub|@onevcat| |Commits to this repo|270 (top contributor)| |Bio|A creator creating for creators: thinking, building, evolving.| |Company / Location|LINE Corp. / Yokohama, Japan / China| |X / Twitter|@onevcat| |Followers|15,900| ────────────────────────────── 📌 How many great GitHub repos have you discovered and completely forgotten about? Don't let another useful tool disappear into your Reddit feed. Get the community's best repos, organized by category, plus key takeaways from real developer discussions, delivered to your inbox twice a week. 📬 Never lose track of great repos again. Subscribe free.
Mac上同时开Claude Codex 切窗口切到想砸电脑 Prowl原生终端管并行agent Canvas直接看谁卡住了 onevcat 649星 brew就能装 onevcat/Prowl t.co