Bilibili Transcribe Agent Skill

by chubbyguan

> 哔哩哔哩视频 → 下载 → 转录 → 存为 Markdown 的完整工作流。支持 BV 号和完整链接，无需登录。

3k tokens

context cost

the whole folder, loaded on every use

files

ships runnable scripts

copies elsewhere

how many repositories repackaged it

588

stars on the repo

on the repository, not the skill itself

Install

one command, takes just this skill from the repository

npx skills add https://github.com/chubbyguan/chubbyskills --skill bilibili-transcribe

The instruction itself

4 sections, as written by the author

B 站视频转录 Skill

字幕优先：先尝试抓取官方/自动字幕（秒级、免 GPU、免 funasr）；抓不到再下载音频用 SenseVoice-Small 转录，存为 Markdown 文件。加 --no-subtitle 可强制走音频转录。

环境要求

# Python 3.9+
python -m venv .venv
source .venv/bin/activate

# 依赖
pip install funasr modelscope torch torchaudio

# 系统依赖
# macOS: brew install ffmpeg yt-dlp
# Ubuntu: sudo apt install ffmpeg && pip install yt-dlp

使用方法

python scripts/transcribe.py "https://www.bilibili.com/video/BV1rrQGBeEen/"
python scripts/transcribe.py "BV1rrQGBeEen"
python scripts/transcribe.py "BV1rrQGBeEen" --no-subtitle   # 强制音频转录

# 批量处理：每行一个 B站 URL 或 BV 号
python scripts/batch_transcribe.py ../../examples/bilibili-urls.txt -o ./output

流程

Step 1: yt-dlp 下载音频

B 站有反爬机制，需要加 User-Agent 和 Referer：

yt-dlp --extract-audio --audio-format mp3 --audio-quality 128K \
  --user-agent "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) ..." \
  --referer "https://www.bilibili.com" \
  "https://www.bilibili.com/video/BV1rrQGBeEen/"

Step 2: SenseVoice-Small 转录

from funasr import AutoModel
from funasr.utils.postprocess_utils import rich_transcription_postprocess

model = AutoModel(
    model="iic/SenseVoiceSmall",
    trust_remote_code=True,
    vad_model="fsmn-vad",
    vad_kwargs={"max_single_segment_time": 30000},
    device="cpu",
)

result = model.generate(input=audio_path, language="zh", use_itn=True, batch_size_s=60)

Step 3: 生成 Markdown

自动创建带 frontmatter 的 Markdown 文件。

批量模式

scripts/batch_transcribe.py 会逐条调用单篇转录脚本，默认单条失败后继续处理下一条；需要严格模式时加 --stop-on-error。

性能数据

| 视频时长 | 转录耗时 |

|------|------|

| 5 min | ~10s |

| 10 min | ~20s |

| 30 min | ~60s |

已知限制

B 站 4K/1080P60 需要大会员，普通用户可下载 720P 以下
SenseVoice-Small 模型首次下载约 893MB
不支持说话人分离
合集视频会下载第一个分 P

参考项目

yt-dlp/yt-dlp - 视频下载工具
FunAudioLLM/SenseVoice - 语音识别模型

⚖️ 合规声明

仅供个人学习与研究使用。请遵守目标平台的服务条款（ToS）与 robots 规则，控制请求频率，不要用于批量抓取、商用爬取或侵犯他人权益的场景。下载内容的版权归原作者所有。

Other skills for the same job

different authors, same section of the catalogue

Canvas Design

by anthropics

vendor ×13

Create beautiful visual art in .png and .pdf documents using design philosophy. You should use this skill when the user asks to create a poster, piece of art, design, or other static piece. Create original visual designs, never copying existing artists' work to avoid copyright violations.

Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use this when users request creating art using code, generative art, algorithmic art, flow fields, or particle systems. Create original algorithmic art rather than copying existing artists' work to avoid copyright violations.

Improves the quality of images, especially screenshots, by enhancing resolution, sharpness, and clarity. Perfect for preparing images for presentations, documentation, or social media posts.

Downloads videos from YouTube and other platforms for offline viewing, editing, or archival. Handles various formats and quality options.

Lightweight WSI tile extraction and preprocessing. Use for basic slide processing tissue detection, tile extraction, stain normalization for H&E images. Best for simple pipelines, dataset preparation, quick tile-based analysis. For advanced spatial proteomics, multiplexed imaging, or deep learning pipelines use pathml.

Microscopy data management platform. Access images via Python, retrieve datasets, analyze pixels, manage ROIs/annotations, batch processing, for high-content screening and microscopy workflows.

Python library for working with DICOM (Digital Imaging and Communications in Medicine) files. Use this skill when reading, writing, or modifying medical imaging data in DICOM format, extracting pixel data from medical images (CT, MRI, X-ray, ultrasound), anonymizing DICOM files, working with DICOM metadata and tags, converting DICOM images to other formats, handling compressed DICOM data, or processing medical imaging datasets. Applies to tasks involving medical image analysis, PACS systems, radiology workflows, and healthcare imaging applications.

This skill should be used when working with pre-trained transformer models for natural language processing, computer vision, audio, or multimodal tasks. Use for text generation, classification, question answering, translation, summarization, image classification, object detection, speech recognition, and fine-tuning models on custom datasets.

13k tokens

How to use it

Copy the folder

Take chubbyguan/bilibili-transcribe from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.

Install what it needs

The instructions reference pip, brew. Without those the skill loads but fails at the first command.