Automatically complete Bilibili daily tasks like login and video watching to accumulate level experience without manual effort.
Run the tool in a Docker container on a home server so tasks execute on schedule without keeping a PC on.
Receive a daily Telegram or Slack summary report of which Bilibili tasks completed and which failed.
Bulk-unfollow accounts added during live-stream lottery entries using the cleanup task.
Requires a Bilibili account login via QR code scan during first setup, Docker is the easiest deployment method.
BiliBiliToolPro is an automation tool written in C# for Bilibili, a large Chinese video-sharing platform similar in some ways to YouTube. The platform has a leveling system tied to daily activities, and members accumulate points by logging in, watching videos, sharing videos, and spending in-platform currency. This tool runs those activities automatically on a schedule so users earn their daily points without doing them manually. The specific tasks it can automate include: daily login to earn experience, watching and sharing videos to complete the daily quota toward level progression, idle check-in inside live-streaming rooms to build fan badges, manga check-in, exchanging live-stream silver coins for hard currency, claiming monthly free coupons that paid members receive, and participating in live-stream lottery draws. Tasks that accumulate unwanted follows (from lottery entries) can be cleaned up in bulk with an unfollow task. Each task can be turned on or off individually through a configuration file. The tool supports multiple Bilibili accounts. After initial setup and a QR code scan to log in, it stores session cookies and reuses them on the configured schedule. Deployment options include running it as a Docker container, using a container platform called Qinglong (popular in the Chinese self-hosting community for scheduled scripts), deploying to a Kubernetes cluster via Helm, or running the binary directly on a local machine or server. After each scheduled run, the tool can send a notification report to messaging platforms including Telegram, DingTalk, Slack, WeChat Work, Microsoft Teams, and several others, or to any custom webhook URL. The README notes the software is intended for learning and testing purposes and that the author takes no responsibility for misuse. All source code is open and auditable. The project is MIT licensed and accepts community contributions.
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