Stars and mentions
Last 30 days, Oct 4 – Nov 2
Package downloads
Cumulative recorded downloads · since 2025-10-29
Across 1 known packages in repositories XiaoMi owns. Cumulative totals include recorded downloads before the selected range. Missing observations leave gaps; totals may be incomplete.
Top repositories
XiaoMi’s repositories ranked by new forks, as on trending.
Contributes to
Repositories outside XiaoMi’s account where XiaoMi opened or reviewed pull requests in the past 365 days.
Who noticed XiaoMi
Everyone who starred or forked XiaoMi’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
- 31st place finishes
- Silver
- 72nd place finishes
- Bronze
- 43rd place finishes
- Awarded repositories
- 3Owned by XiaoMi now
Repositories
Ordered by gold, then silver, then bronze.
- maceBest: 1st by stars, 585 stars310
- ha_xiaomi_homeBest: 2nd by stars, 3,578 stars062
- soarBest: 3rd by stars, 409 stars002
Every award
Top-three finishes of these repositories in completed trending days and weeks, newest first.
- #2 by starsDaily trending
1,766 starsha_xiaomi_home - #2 by starsDaily trending
2,543 starsha_xiaomi_home - #2 by starsDaily trending
3,072 starsha_xiaomi_home - #2 by forksDaily trending
147 forksha_xiaomi_home - #2 by starsDaily trending
3,578 starsha_xiaomi_home - #3 by forksDaily trending
129 forksha_xiaomi_home - #3 by starsWeek of
12,973 starsha_xiaomi_home - #2 by starsDaily trending
1,203 starsha_xiaomi_home
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
I built BSWorld — a virtual Bluetooth world where AI agents can develop and test Bluetooth software Hi r/embedded I’ve been working on an open-source project called BSWorld — a deterministic Bluetooth simulation framework designed to make Bluetooth development accessible to AI coding agents and CI. GitHub: XiaoMi/bsworld The idea came from a problem we encountered when using AI for embedded development: AI can write Bluetooth code, but it can’t operate a hardware Bluetooth lab. A real Bluetooth test may require multiple boards, flashing firmware, serial ports, power cycling devices, RF interaction, packet capture, and reproducing timing-sensitive failures. This creates a hard boundary for AI agents. They can modify and compile the code, but once testing requires the physical world, autonomous development largely stops. BSWorld tries to move that physical Bluetooth lab into software. Instead of mocking Bluetooth APIs, we run real Bluetooth software inside a deterministic simulated environment and connect simulated controllers to BabbleSim’s radio/PHY simulation. So an AI agent can potentially complete the whole loop: modify code → build → boot multiple devices → communicate over simulated RF → run tests → inspect HCI/OTA traces → diagnose failures → modify code again without anyone touching a physical board. The simulated RF environment can reproduce things that are normally difficult for an AI agent — or even a human developer — to control precisely: - multiple Bluetooth devices - advertising/connection timing - interference and collisions - attenuation and packet loss - HCI traces - over-the-air packet traces - deterministic reproduction of failures - accelerated discrete-time execution We’re also experimenting with QEMU + BabbleSim discrete-time synchronization, so larger embedded/Linux systems can participate in the same virtual RF world. Another direction we’re working on is a pure-Python Bluetooth Controller, which would make it much easier for AI agents to manipulate LL behavior, timing and edge cases during testing. The long-term idea is not just to simulate one Bluetooth stack. We’d like BSWorld to become a virtual Bluetooth lab for AI agents where different open-source Hosts and Controllers can be composed, tested against each other, and debugged entirely in software. I’m curious what Bluetooth developers here think: If an AI agent had access to a fully controllable virtual Bluetooth lab, what Bluetooth bugs or test scenarios would you want it to handle automatically?