---

name: youtube-video-analyzer description: Deep analysis of YouTube videos using scene detection, subtitle alignment, and parallel frame analysis. Generates structured bilingual learning summaries with mind maps, flowcharts, timelines, and key visual captures. Use when user provides a YouTube link and wants comprehensive learning notes with visual content analysis.

YouTube Video Analyzer

A professional YouTube video analysis assistant using scene detection + subtitle alignment + parallel analysis architecture.

Prerequisites

Before starting, ensure these tools are installed:

# Check installations
which yt-dlp    # Video/subtitle download
which ffmpeg    # Scene detection and frame extraction

# Install if missing (macOS)
brew install yt-dlp ffmpeg

# Or via pip
pip install yt-dlp

Complete Workflow

Phase 1: Setup and Download

# Create working directory
VIDEO_ID="[extract from URL]"
WORK_DIR="youtube_analysis_$VIDEO_ID"
mkdir -p $WORK_DIR/{video,subtitles,frames,output}

# Download video + subtitles + metadata in one call (fewer requests)
yt-dlp -f "worst[ext=mp4]/best[ext=mp4]" \
       --write-info-json \
       --write-auto-sub --write-sub \
       --sub-lang zh-Hans,zh,en \
       --convert-subs srt \
       --no-playlist \
       -o "$WORK_DIR/video/source.%(ext)s" \
       "YOUTUBE_URL"

# Move subtitles to subtitles/ and keep metadata.json
mv "$WORK_DIR/video/"*.srt "$WORK_DIR/subtitles/" 2>/dev/null || true
cp "$WORK_DIR/video/source.info.json" "$WORK_DIR/metadata.json" 2>/dev/null || true

Phase 2: Scene Detection and Frame Extraction

# Extract keyframes + timestamps in a single decode
ffmpeg -i $WORK_DIR/video/source.mp4 \
       -vf "select='gt(scene,0.3)',showinfo" \
       -vsync vfr \
       $WORK_DIR/frames/scene_%04d.jpg \
       2> $WORK_DIR/ffmpeg_scene.log

# Parse timestamps from log (no second decode)
grep "pts_time" $WORK_DIR/ffmpeg_scene.log | \
  sed 's/.*pts_time:\([0-9.]*\).*/\1/' > $WORK_DIR/frame_timestamps.txt

Scene threshold guidelines:

| Video Type | Threshold | Description | |------------|-----------|-------------| | Lectures/PPT | 0.2-0.3 | Fewer changes, capture slides | | Technical tutorials | 0.25-0.35 | Code/UI changes | | Vlogs/interviews | 0.3-0.4 | Moderate changes | | Fast-paced/edited | 0.4-0.5 | Avoid too many frames |

Phase 3: Subtitle Parsing and Alignment

Parse the SRT subtitle file and align with extracted frames:

1. Read subtitle file from $WORK_DIR/subtitles/
2. Parse timestamp format: 00:01:23,456 --> 00:01:25,789
3. Match each frame timestamp to corresponding subtitle segment
4. Create frame-subtitle pairs for analysis

Phase 4: Parallel Segment Analysis

Divide frames into segments (10-15 frames each) and analyze:

For each segment, use this prompt:

分析以下视频片段：

时间范围：{start_time} - {end_time}
帧图片：[Read the frame images]
字幕内容：
{subtitle_text}

请分析：
1. 每帧的视觉内容（图表、代码、流程图、UI等）
2. 结合字幕理解讲解要点
3. 提取关键概念和术语
4. 标注重要的视觉元素
5. 给出关键细节的解释或小结
6. 如果有步骤/代码，提炼可复现的操作点

输出格式：结构化笔记，标注时间戳

Parallel execution tips:

• Cap concurrency (e.g., 3–5 segments at once) to avoid rate limits
• Retry failed segments and merge results incrementally
• Consider de-dup/contact-sheeting similar frames to reduce token use

Phase 5: Final Summary Generation

Merge all segment analyses and generate complete summary:

Use this prompt for final generation:

整合以下视频分析结果，生成完整的学习总结：

{all_segment_analyses}

**必须包含以下内容：**

1. 概览（中英双语）
2. 核心要点列表
3. 场景时间线表格
4. 关键视觉内容（引用帧图片）
5. 详细笔记（按章节组织）
6. 实践要点清单

**详细度要求：**
- 每个章节至少 3-5 条要点（包含解释、原因或影响）
- 对关键术语给出简短定义/释义
- 对关键步骤给出可复现的操作描述
- 重要结论尽量引用对应帧图（scene_XXXX.jpg）

**必须生成以下图表（Mermaid格式）：**

1. **思维导图**（必须）- 展示知识结构
2. **时间线**（必须）- 展示内容分布
3. **流程图**（如有步骤/流程）
4. **概念关系图**（如有概念关联）

Phase 6: Final Deliverables (cleanup)

Keep only final artifacts:

• Video file
• Chinese/English subtitles (SRT)
• Summary document
• Frames referenced by the summary

Run:

./scripts/finalize.sh "$WORK_DIR" /path/to/summary.md

Use --keep-work to preserve intermediate files for debugging. When using this skill, always run finalize.sh after the summary is generated to remove intermediate artifacts.

Output Format Template

# [视频标题] 学习总结 / Learning Summary

## 概览 / Overview
[中英双语简介]

## 核心要点 / Key Takeaways
- 要点 1 / Point 1
- 要点 2 / Point 2
- 要点 3 / Point 3

## 知识结构图 / Knowledge Mind Map

```mermaid
mindmap
  root((视频主题))
    核心概念1
      子概念A
      子概念B
    核心概念2
      子概念C
    实践要点
      步骤1
      步骤2

视频时间线 / Video Timeline

gantt
    title 视频内容时间线
    dateFormat mm:ss
    section 引言
    主题介绍 :00:00, 02:00
    section 核心内容
    概念讲解 :02:00, 15:00
    section 总结
    回顾要点 :15:00, 20:00

内容流程图 / Content Flowchart (如适用)

flowchart TD
    A[开始] --> B[步骤1]
    B --> C{判断条件}
    C -->|是| D[步骤2]
    C -->|否| E[步骤3]
    D --> F[结束]
    E --> F

概念关系图 / Concept Relationships (如适用)

graph LR
    A[概念A] --> B[概念B]
    A --> C[概念C]
    B --> D[概念D]
    C --> D

场景时间线 / Scene Timeline

| 时间 | 场景描述 | 关键内容 | |------|---------|---------| | 00:15 | 标题页 | 主题介绍 | | 02:30 | 代码演示 | 核心实现 | | 05:45 | 架构图 | 系统设计 |

关键视觉内容 / Key Visuals

[00:02:30] - 架构图

分析 / Analysis: [图片内容说明及重要性]

[00:05:45] - 代码示例

分析 / Analysis: [代码说明及要点]

详细笔记 / Detailed Notes

第一章：引言 [00:00 - 02:00]

[详细内容...]

第二章：核心概念 [02:00 - 10:00]

[详细内容...]

第三章：实践演示 [10:00 - 18:00]

[详细内容...]

第四章：总结 [18:00 - 20:00]

[详细内容...]

关键概念释义 / Key Terms

• 术语 1：解释
• 术语 2：解释

复现步骤 / Reproduction Steps

1. 步骤 1
2. 步骤 2
3. 步骤 3

常见误区 / Common Pitfalls

• 误区 1：说明
• 误区 2：说明

实践要点 / Action Items

• [ ] 实践项 1 / Action 1
• [ ] 实践项 2 / Action 2
• [ ] 实践项 3 / Action 3

相关资源 / Related Resources

• 链接1 - 描述
• 链接2 - 描述

## Execution Tips

1. **Long videos (>30min)**: Increase scene threshold to 0.4-0.5 to reduce frame count
2. **No subtitles available**: Use audio transcription or analyze frames only
3. **Too many frames**: Manually select key frames or increase threshold
4. **Token limits**: Process in smaller segments, summarize progressively
5. **Faster downloads**: Use parallel fragments with yt-dlp (e.g., `--concurrent-fragments 4`)

## Quick Start Script

Run the preprocessing script:

```bash
./scripts/preprocess.sh "YOUTUBE_URL"

Optional faster download (parallel fragments) and extra yt-dlp args:

YTDLP_CONCURRENT_FRAGMENTS=4 \
YTDLP_EXTRA_ARGS="--cookies-from-browser chrome" \
./scripts/preprocess.sh "YOUTUBE_URL"

Then analyze the extracted frames and subtitles using the prompts above, generate summary.md, and run finalize.sh to keep only deliverables.

Optional auto-finalize (if summary exists):

./scripts/preprocess.sh "YOUTUBE_URL" 0.3 /path/to/summary.md