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Video Content Analyzer (Batch)

核心功能含单视频分析(提取关键帧、搜索关联信息、存Supabase、发飞书Wiki报告)及批量目录处理(自动分类、生成分类索引页、进度追踪),支持多种主流视频格式。需配置Supabase、谷歌搜索、飞书等环境变量,通过CLI调用,适合媒体归档、教程整理等场景,输出结构化Wiki文档与云端数据。

terrycarter1985
terrycarter1985
热度 29.67
最近更新 2026-05-18 11:51:20
分类:数据依赖:代码执行 / 读写文件 / 第三方 API应用场景:数据处理 / 报告撰写 / 自动化脚本 / 研究

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add video-content-analyzer-batch
Metadata
name
video-content-analyzer
version
2.0.0
description
Analyze video content, extract keyframes, search web for references, generate Feishu Wiki reports. Supports batch directory processing with category-based publishing.
author
ClawHub Team
license
MIT
tags
["video","analysis","wiki","search","supabase","batch"]

Video Content Analyzer

An integrated workflow for processing video content — extract keyframes, search for related information, store results in Supabase, and publish documentation to Feishu Wiki.

Skills

process_video — Single video analysis

Process a single video file: extract keyframes, search the web for related info, store in Supabase, publish analysis report to Feishu Wiki.

Parameters:

  • video_path (string, required): Path to the input video file
  • user_id (string, required): UUID of the user running the analysis
  • space_id (string, required): Feishu Wiki space ID for publishing

batch_process — Batch directory processing

Process all videos in a directory, auto-classify by filename keywords, store results in Supabase batch_jobs table, and publish categorized analysis reports to Feishu Wiki.

Parameters:

  • directory (string, required): Path to directory containing video files
  • user_id (string, required): UUID of the user running the analysis
  • space_id (string, required): Feishu Wiki space ID for publishing
  • categories (object, optional): Mapping of category names to keyword lists for auto-classification
    • Example: {"demo": ["demo", "presentation"], "tutorial": ["tut", "howto"]}
  • interval_seconds (integer, optional): Keyframe extraction interval in seconds (default: 10)

Supported video formats: .mp4, .avi, .mov, .mkv, .webm, .flv, .wmv

Batch workflow:

  1. Discover all video files in the specified directory
  2. Process each video (keyframe extraction → web search → Supabase storage)
  3. Auto-classify videos by filename keywords using the categories mapping
  4. Publish individual analysis pages to Feishu Wiki
  5. Create a category index page per category linking to all its video analyses
  6. Track progress in batch_jobs table in Supabase

Environment Variables

Variable Required Description
SUPABASE_URL Yes Supabase project URL
SUPABASE_SERVICE_ROLE_KEY Yes Supabase service role key
GOOGLE_API_KEY Yes Google Custom Search API key
GOOGLE_SEARCH_ENGINE_ID Yes Google Custom Search engine ID
FEISHU_APP_ID Yes Feishu app ID
FEISHU_APP_SECRET Yes Feishu app secret
FRAMES_OUTPUT_DIR No Directory for extracted frames (default: ./extracted_frames)

CLI Usage

# Single video
python src/main.py single path/to/video.mp4 --user-id <uuid> --space-id <space-id>

# Batch processing
python src/main.py batch /path/to/videos/ --user-id <uuid> --space-id <space-id>

# Batch with categories
python src/main.py batch /path/to/videos/ \
  --user-id <uuid> \
  --space-id <space-id> \
  --categories '{"demo":["demo","presentation"],"tutorial":["tut","howto"]}'