Video Analyzer Skill

鏅鸿兘鍒嗘瀽 Bilibili銆乊ouTube 鎴栨湰鍦拌棰戯紝鐢熸垚杞啓銆佽瘎浼板拰鎬荤粨銆傛敮鎸佸叧閿抚鎴浘鑷姩宓屽叆銆?

When to Use This Skill

褰撶敤鎴锋彁鍒颁互涓嬪唴瀹规椂婵€娲绘鎶€鑳斤細

• "鍒嗘瀽瑙嗛"
• "杞啓瑙嗛"
• "鎬荤粨瑙嗛鍐呭"
• "璇勪及杩欎釜瑙嗛"
• "瑙嗛鍐呭鍒嗘瀽"
• "鎻愬彇瑙嗛鏂囧瓧"

How It Works

姝ゆ妧鑳戒細锛?

1. 涓嬭浇瑙嗛锛氭敮鎸?Bilibili銆乊ouTube 鎴栨湰鍦版枃浠?
2. 璇煶杞啓锛氫娇鐢?Whisper AI 妯″瀷杩涜楂樼簿搴﹁浆鍐?
3. **鍏抽敭甯ф彁鍙?*锛氭櫤鑳介€夋嫨鍏抽敭鑺傜偣骞舵彁鍙栨埅鍥撅紙榛樿鍚敤锛?
4. 鍐呭鍒嗘瀽锛氫娇鐢?LLM 杩涜鍐呭璇勪及銆佹€荤粨銆佹牸寮忓寲
5. 缁撴灉淇濆瓨锛氱敓鎴?Markdown 鏍煎紡鐨勫垎鏋愭姤鍛?

Usage

鍩虹鐢ㄦ硶

python .claude/skills/video-analyzer/run.py --url "<VIDEO_URL>"

甯哥敤鍙傛暟

• --url

  : 瑙嗛閾炬帴鎴栨湰鍦版枃浠惰矾寰勶紙蹇呭～锛?

• --whisper-model

  : Whisper 妯″瀷锛堥粯璁? large-v2锛?
  • 鍙€? tiny, base, small, medium, large-v2, large-v3, turbo

• --analysis-types

  : 鍒嗘瀽绫诲瀷锛堥粯璁? evaluation,summary锛?
  • 鍙€? evaluation, summary, format

• --output-dir

  : 杈撳嚭鐩綍锛堥粯璁? ./video-analysis锛?

• --summary-style

  : 鎬荤粨椋庢牸锛堝彲閫? concise, deep, social, study锛?

• --no-screenshots

  : 绂佺敤鍏抽敭甯ф埅鍥?

绀轰緥

# 鍩虹鍒嗘瀽
python run.py --url "https://www.bilibili.com/video/BV1xx411c7mD"

# 蹇€熻浆鍐欙紙灏忔ā鍨嬶級
python run.py --url "https://youtu.be/xxx" --whisper-model small

# 鍙仛鎬荤粨
python run.py --url "./video.mp4" --analysis-types summary

Configuration

棣栨浣跨敤闇€瑕侀厤缃?API key锛?

1. 澶嶅埗

   config.example.json

   涓?

   config.json

2. 濉叆浣犵殑 API key锛?

{
  "llm": {
    "provider": "openai",
    "api_key": "your-api-key",
    "base_url": "https://api.openai.com/v1",
    "model": "gpt-4o-mini"
  }
}

鏀寔鐨勬彁渚涘晢锛?

• OpenAI: gpt-4o-mini, gpt-4o
• Anthropic: claude-3-5-sonnet-20241022
• **鍏煎 OpenAI API 鐨勬湇鍔?*: 濡?Gemini銆丏eepSeek 绛?

Dependencies

绯荤粺渚濊禆

• FFmpeg锛堝繀闇€锛? 瑙嗛澶勭悊
  • Windows:

    winget install ffmpeg

  • macOS:

    brew install ffmpeg

  • Linux:

    sudo apt install ffmpeg

Python 渚濊禆

棣栨杩愯浼氳嚜鍔ㄦ鏌ュ苟瀹夎锛?

• yt-dlp - 瑙嗛涓嬭浇
• faster-whisper - 璇煶杞啓
• openai / anthropic - LLM API
• 鍏朵粬渚濊禆瑙?

  requirements.txt

Features

• 馃幀 澶氬钩鍙版敮鎸侊紙B绔欍€乊ouTube銆佹湰鍦版枃浠讹級
• 馃帳 楂樼簿搴﹁浆鍐欙紙Whisper AI锛?
• 馃 鏅鸿兘鍒嗘瀽锛堝唴瀹硅瘎浼般€佹€荤粨锛?
• 馃摳 鍏抽敭甯ф埅鍥撅紙鑷姩鎻愬彇骞跺祵鍏ワ級
• 馃寪 澶氳瑷€鏀寔锛堜腑鑻辨枃绛夛級

Troubleshooting

Q: 鎻愮ず缂哄皯 FFmpeg A: 瀹夎 FFmpeg锛堣涓婃柟绯荤粺渚濊禆锛?

Q: API 璋冪敤澶辫触 A: 妫€鏌?

config.json

涓殑 API key 鏄惁姝ｇ‘

Q: 瑙嗛涓嬭浇澶辫触 A: 妫€鏌ョ綉缁滆繛鎺ワ紝鎴栦娇鐢ㄦ湰鍦拌棰戞枃浠?

*Q: 鎴浘鍔熻兘涓嶅伐浣? A: 纭繚 FFmpeg 宸插畨瑁咃紝涓斾娇鐢ㄧ殑鏄棰?URL锛堜笉鏄函闊抽锛?

Notes

• 棣栨杩愯浼氫笅杞?Whisper 妯″瀷锛堢害 3GB锛屼娇鐢ㄥ浗鍐呴暅鍍忥級
• 瑙嗛涓存椂涓嬭浇鍒扮郴缁熶复鏃剁洰褰曪紝鍒嗘瀽瀹屾垚鍚庤嚜鍔ㄦ竻鐞?
• 澶фā鍨嬶紙large-v2锛夌簿搴﹂珮浣嗛€熷害鎱紝灏忔ā鍨嬶紙small锛夐€熷害蹇絾绮惧害杈冧綆
• 鍚敤鎴浘闇€瑕佷笅杞藉畬鏁磋棰戯紙鑰岄潪浠呴煶棰戯級

Code-level Feishu Publishing (Required)

Do not store Feishu app credentials in this skill config. Publishing is handled by built-in Python flow (

feishu_publisher.py

) after analysis.

After analysis succeeds:

1. Use

   video_title

   as Feishu doc title exactly.
2. Merge all generated content into one markdown body (summary + evaluation + transcript).
3. Create a wiki docx node under configured

   space_id

   +

   parent_node_token

   .
4. Write the full markdown body into the created doc token.
5. Return publish result (

   doc_token

   /

   doc_url

   ) in output field

   feishu_publish

   .

Credential/target resolution priority:

• feishu_space_id

  /

  feishu_parent_node_token

  parameters

• FEISHU_SPACE_ID

  /

  FEISHU_PARENT_NODE_TOKEN

  env

• config.json

  ->

  feishu.space_id

  /

  feishu.parent_node_token

App credentials are loaded from:

• FEISHU_APP_ID

  /

  FEISHU_APP_SECRET

  env, or
• OpenClaw

  openclaw.json

  ->

  channels.feishu

If publish fails, keep analysis result and return

feishu_publish.success=false

with error details.