# 1. 准备分镜拆解数据和钩子分析数据（JSON 文件）
# 2. 生成报告
python scripts/generate_report.py breakdown.json hook_analysis.json

# 3. 保存到文件
python scripts/generate_report.py breakdown.json hook_analysis.json > report.md

python scripts/generate_report.py breakdown.json

# 视频分析报告

## 基本信息
- 视频时长、分镜数量、分辨率

## 前三秒钩子分析（核心）
- 综合评分
- 5维度评分表格
- 钩子类型
- 优势/不足/优化建议
- 留存预测

## 分镜概览
- 前10个分镜的概览表格

## BGM 分析
- 音乐风格、情绪基调、节拍

## 场景分析
- 主要场景、视频风格、目标受众
- 平台推荐

报告生成时间

{
  "duration": 30.5,
  "segment_count": 12,
  "resolution": "1920x1080",
  "segments": [...],
  "bgm_analysis": {
    "music_style": {"primary": "流行"},
    "emotion": {"primary": "欢快"},
    "tempo": {"bpm_estimate": 120, "pace": "中速"}
  },
  "scene_analysis": {
    "primary_scene": "室内",
    "video_style": {"overall": "生活方式", "target_audience": ["年轻人"]},
    "platform_recommendations": [...]
  }
}

{
  "overall_score": 7.5,
  "visual_impact": 8.0,
  "visual_comment": "评价...",
  "language_hook": 7.0,
  "language_comment": "评价...",
  "emotion_trigger": 7.5,
  "emotion_comment": "评价...",
  "information_density": 7.0,
  "info_comment": "评价...",
  "rhythm_control": 8.0,
  "rhythm_comment": "评价...",
  "hook_type": "好奇型",
  "strengths": ["优点1", "优点2"],
  "weaknesses": ["不足1"],
  "suggestions": ["建议1", "建议2"],
  "retention_prediction": "中：50-70%，因为..."
}

# 完整流程
python ../video-breakdown-skill/scripts/process_video.py "https://example.com/video.mp4" > breakdown.json
cat breakdown.json | python ../hook-analyzer-skill/scripts/analyze_hook_segments.py - > hooks.json
# (hooks.json 需经 LLM 评分后得到 hook_analysis.json)
python scripts/generate_report.py breakdown.json hook_analysis.json > report.md