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Token-efficient tracking for AI orchestration. CLI-first for status updates (~50 tokens), agent fallback for complex ops (~1KB). Use when: updating task status, querying blockers, creating progress files, validating phases.
AshAi extension guidelines for integrating AI capabilities with Ash Framework. Use when implementing vectorization/embeddings, exposing Ash actions as LLM tools, creating prompt-backed actions, or setting up MCP servers. Covers semantic search, LangChain integration, and structured outputs.
This skill should be used when solving hard questions, complex architectural problems, or debugging issues that benefit from GPT-5 Pro or GPT-5.1 thinking models with large file context. Use when standard Claude analysis needs deeper reasoning or extended context windows.
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| name | video-analyzer |
| version | 1.0.10 |
| description | 鏅鸿兘鍒嗘瀽 Bilibili/YouTube/鏈湴瑙嗛锛岀敓鎴愯浆鍐欍€佽瘎浼板拰鎬荤粨銆傛敮鎸佸叧閿抚鎴浘鑷姩宓屽叆銆? |
| author | user |
| tags | ["video","transcription","analysis","bilibili","youtube","ai"] |
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?
褰撶敤鎴锋彁鍒颁互涓嬪唴瀹规椂婵€娲绘鎶€鑳斤細
姝ゆ妧鑳戒細锛?
python .claude/skills/video-analyzer/run.py --url "<VIDEO_URL>"
--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?
--analysis-types: 鍒嗘瀽绫诲瀷锛堥粯璁? evaluation,summary锛?
--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?# 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
棣栨浣跨敤闇€瑕侀厤缃?API key锛?
config.example.json 涓?config.json{
"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?
winget install ffmpegbrew install ffmpegsudo apt install ffmpeg棣栨杩愯浼氳嚜鍔ㄦ鏌ュ苟瀹夎锛?
requirements.txtQ: 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?
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:
video_title as Feishu doc title exactly.space_id + parent_node_token.doc_token/doc_url) in output field feishu_publish.Credential/target resolution priority:
feishu_space_id / feishu_parent_node_token parametersFEISHU_SPACE_ID / FEISHU_PARENT_NODE_TOKEN envconfig.json -> feishu.space_id / feishu.parent_node_tokenApp credentials are loaded from:
FEISHU_APP_ID / FEISHU_APP_SECRET env, oropenclaw.json -> channels.feishuIf publish fails, keep analysis result and return feishu_publish.success=false with error details.