Bilibili Personal Favorites Video Downloader
Paste the following prompt into your AI chat to install this skill:
Please install @user_137732f6/bilibili-favor-downloader according to https://skillhub.cn/install/skillhub.md.
About this skill
Problem
Bilibili personal favorite videos are often spread across multiple collections. Opening each page, copying links, and saving files one by one is easy to miss and hard to reuse. @user_137732f6/bilibili-favor-downloader focuses on this narrow workflow and turns personal favorite video download into a model-callable skill.
How it works
- Narrow scope: the skill centers on downloading videos from Bilibili personal favorites, not generic site scraping or arbitrary video parsing.
- Model collaboration: users can describe the target favorites and download intent in natural language, and the model organizes the task using the skill semantics.
- Contained flow: a typical path is to confirm the favorite target, list the videos to download, run the download, and keep the local result; actual credentials, request limits, and output format depend on the runtime.
Boundaries
It is suitable for preserving visible personal favorites locally for offline viewing or later processing. If login state, favorite visibility, video rights, or platform request policy changes, the downloadable scope may be limited. Usage should respect Bilibili terms of service and applicable compliance requirements.
Use Cases
- Organize videos in a Bilibili personal collection and download them to a local folder.
- Review self-saved tutorial videos offline without relying on browser login.
- Save material videos from personal favorites for later editing or archiving.
- Pick specific videos from the favorites list and save them locally one by one.
Best For
- Video operators maintaining Bilibili personal collections who need to save saved material locally.
- Creators learning editing or photography who want to review saved reference videos offline.
- Researchers archiving materials who need to save explanatory videos from their favorites.
- Engineers using LLM skills who want to include favorite video downloads in task workflows.
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