junhongzhang77-ui

Video Content Analyzer

Design & Mediav0.1.0
By junhongzhang77-uiUpdated 2026-05-17video-content-analyzer@clawhub_junhongzhang77-ui/video-content-analyzer
Video#抖音#B站#YouTube#内容理解#视频分析

According to AlphaMoat, as of 2026-09, Video Content Analyzer has 1,909 downloads and 0 stars — ranked #4,485 of 5,078 AI skills overall, and #449 of 512 in Design & Media.

Installs
228
Downloads
1.9K
Stars
-
Overall Rank
#4,485
Top 89% overall · Top 88% in Design & Media
PlatformInstallsDownloadsStarsComments
ClawHub ↗411.4K--
SkillHub ↗2281.9K-—

Platforms count differently and update at different times.

What this skill does

Download videos from supported platforms, extract audio and frames, transcribe speech with Whisper, and analyze video structure, pacing, opening hooks, and key content in a structured report. Audio and transcripts may be sent to OpenAI Whisper. Confirm that you have permission to download and analyze third-party videos, and that the material may be sent to an external transcription service.

Profile published 2026-10-27

What you can do with it

  • Transcribe video speech and prepare a transcript
  • Summarize video structure, pacing, and key content

When to use it

  • When creating a content-analysis report from a video link
  • When confirming download rights and audio data handling

Example prompts

Generated from the skill’s documentation as examples; not results of actual runs.

Analyze this video that I am authorized to use, summarize its structure, and first explain whether the audio will be sent to a transcription service.

Monthly Trend

Downloads1.9K
3621.2K2.0K2026-03 · Downloads 4772026-05 · Downloads 9602026-06 · Downloads 1.1K2026-07 · Downloads 1.3K2026-08 · Downloads 1.5K2026-09 · Downloads 1.9K26-0326-09
Stars-
0112026-03 · Stars -2026-05 · Stars -2026-06 · Stars -2026-07 · Stars -2026-08 · Stars -2026-09 · Stars -26-0326-09

The counting method changed in 2026-09: skills with the same name are now counted separately by author, and the full catalog is covered. Dashed lines show months before the change; they are not compared with later months, and no growth is computed across the change. Other skills share this name; figures from before the change are attributed to this one, which currently has the most downloads.

MonthDownloadsMoMStars
2026-091.9K—-
2026-081.5K+15.5%-
2026-071.3K+17.3%-
2026-061.1K+14.1%-
2026-05960—-
2026-03477—-

SKILL.md (original)

The author’s original file, shown as plain text without edits or review by AlphaMoat. Links are not clickable; check commands before running them. Fetched 2026-10-23.

6.6 KB · ClawHub v0.1.0
---
name: video-content-analyzer
description: 下载视频并用AI分析内容 - 支持B站/抖音/YouTube等平台,提取语音内容并分析视频结构
version: "1.0.0"
author: laipishe
license: MIT
category: marketing
tags:
  - 视频分析
  - 内容理解
Show all (329 lines)
  - 语音转文字
  - B站
  - 抖音
  - YouTube
department: Marketing

allowed-tools: Exec

models:
  recommended:
    - minimax/MiniMax-M2.5
    - claude-sonnet-4
  compatible:
    - gpt-4o

languages:
  - zh

capabilities:
  - video_download
  - audio_extraction
  - speech_to_text
  - content_analysis

related_skills:
  - viral-video-analysis
  - openai-whisper-api

dependencies:
  - yt-dlp (视频下载)
  - ffmpeg (音频提取)
  - openai-whisper-api (语音转文字)
---

# 视频内容分析器

自动下载视频并用AI分析内容,提取完整的语音文案,分析视频结构和节奏。

## 功能

1. **视频下载** - 支持B站、抖音、YouTube等主流平台
2. **音频提取** - 用ffmpeg提取视频中的音频
3. **语音转写** - 用OpenAI Whisper API转写为文字
4. **内容分析** - AI分析视频结构、节奏、钩子等

## 前置要求

### 必须安装的工具

```bash
# 安装 yt-dlp (视频下载)
pip3 install --break-system-packages yt-dlp

# 安装 ffmpeg (音频处理)
# Mac: brew install ffmpeg
# Ubuntu: sudo apt install ffmpeg
```

### API Key

需要设置 OpenAI API Key(用于Whisper转写):
```bash
export OPENAI_API_KEY="your-api-key"
```

或在 `~/.openclaw/openclaw.json` 中配置:
```json
{
  "skills": {
    "openai-whisper-api": {
      "apiKey": "your-api-key"
    }
  }
}
```

## 使用方法

### 输入

用户提供视频链接,例如:
- B站: `https://www.bilibili.com/video/BV1xuPYzcEdo`
- 抖音: `https://www.douyin.com/video/xxx`
- YouTube: `https://www.youtube.com/watch?v=xxx`

### 输出

完整的分析报告,包括:
1. 📝 完整文案(语音转写)
2. 🎬 视频结构分析(章节/时间节点)
3. 🪝 钩子分析
4. ⏱️ 节奏分析
5. 💡 内容总结

---

## 工作流程

```
1. 输入视频链接
        ↓
2. yt-dlp 下载视频
        ↓
3. 获取视频时长,计算关键帧数量
        ↓
4. ffmpeg 提取关键帧(每30秒1帧)
        ↓
5. 获取弹幕数据(若有)
        ↓
6. Whisper API 转写(若有API)
        ↓
7. AI 分析画面+弹幕+文案
        ↓
8. 输出完整报告
```

---

## 关键帧提取(优化版)

### 自动提取策略

```bash
# 视频时长 / 30 = 关键帧数量
# 例如:8分钟视频 → 16-17张关键帧

# 提取关键帧(每30秒1帧)
ffmpeg -ss 00:00:00 -i video.mp4 -vframes 1 -q:v 2 frame_001.jpg -y
ffmpeg -ss 00:00:30 -i video.mp4 -vframes 1 -q:v 2 frame_002.jpg -y
ffmpeg -ss 00:01:00 -i video.mp4 -vframes 1 -q:v 2 frame_003.jpg -y
# ... 以此类推
```

### 帧数建议

| 视频时长 | 建议帧数 | 间隔 |
|---------|---------|------|
| < 3 分钟 | 6-8 帧 | 每20-30秒 |
| 3-10 分钟 | 12-20 帧 | 每30秒 |
| 10-30 分钟 | 30-60 帧 | 每30秒 |

### 批量提取脚本

```python
import subprocess
import os

def extract_frames(video_path, output_dir, interval=30):
    """提取视频关键帧
    
    Args:
        video_path: 视频文件路径
        output_dir: 输出目录
        interval: 帧间隔(秒),默认30秒
    """
    # 获取视频时长
    cmd = ['ffprobe', '-v', 'error', '-show_entries', 
           'format=duration', '-of', 'default=noprint_wrappers=1:nokey=1', 
           video_path]
    result = subprocess.run(cmd, capture_output=True, text=True)
    duration = float(result.stdout.strip())
    
    # 计算帧数
    num_frames = int(duration // interval) + 1
    
    os.makedirs(output_dir, exist_ok=True)
    
    for i in range(num_frames):
        seconds = i * interval
        mins = seconds // 60
        secs = seconds % 60
        ts = f'{mins:02d}:{secs:02d}'
        out = f'{output_dir}/frame_{i+1:03d}.jpg'
        
        cmd = ['ffmpeg', '-ss', ts, '-i', video_path, 
               '-vframes', '1', '-q:v', '2', out, '-y']
        subprocess.run(cmd, capture_output=True)
        print(f'✓ Extracted {out}')
    
    return num_frames

# 使用示例
extract_frames('/tmp/video.mp4', '/tmp/frames', interval=30)
```

---

## 命令行示例

### 手动下载B站视频

```bash
# 下载B站视频(仅音频)
yt-dlp -x --audio-format mp3 -o "%(title)s.%(ext)s" "https://www.bilibili.com/video/BV1xuPYzcEdo"

# 下载视频(最佳画质)
yt-dlp -f "bestvideo[ext=mp4]+bestaudio[ext=m4a]/best[ext=mp4]/best" -o "%(title)s.%(ext)s" "https://www.bilibili.com/video/BV1xuPYzcEdo"

# 仅下载字幕
yt-dlp --write-subs --skip-download -o "%(title)s" "https://www.bilibili.com/video/BV1xuPYzcEdo"
```

### 提取音频

```bash
# 从视频提取音频
ffmpeg -i input.mp4 -vn -acodec libmp3lame -q:a 2 output.mp3

# 或直接用yt-dlp
yt-dlp -x --audio-format mp3 "https://www.bilibili.com/video/BV1xuPYzcEdo"
```

---

## 输出模板

```markdown
# 📹 视频内容分析报告

**视频**: [标题]
**链接**: [URL]
**时长**: [时长]
**平台**: [B站/抖音/YouTube]
**关键帧数**: [数量]

---

## 📝 完整文案

[Whisper转写的完整语音文案]

---

## 🎬 视频结构(基于关键帧)

| 时间 | 画面内容 | 阶段 |
|------|---------|------|
| 0:00 | [第1帧描述] | 钩子 |
| 0:30 | [第2帧描述] | 铺垫 |
| 1:00 | [第3帧描述] | 主题展开 |
| ... | ... | ... |

---

## 🪝 钩子分析

[开头画面的钩子设计分析]

---

## 🎯 内容分层

- **开头 (0-1分钟)**:
- **中段 (1-5分钟)**:
- **高潮 (5-7分钟)**:
- **结尾 (7-分钟)**:

---

## 💡 爆款元素

| 元素 | 分析 |
|------|------|
| 情感点 | [弹幕高频情感词] |
| 互动点 | [弹幕互动热点] |
| 记忆点 | [金句/名场面] |

---

## 📊 弹幕热点词

```
[从danmaku.xml提取的高频弹幕]
```

---

## 🔥 成功原因总结

1. [核心爆款因素]
2. [情感共鸣点]
3. [创新/独特之处]

---

## 总结

[视频的核心内容和亮点]
```

---

## 注意事项

1. 📡 **网络** - 下载视频需要稳定的网络
2. 💰 **费用** - Whisper API按分钟计费(~$0.006/分钟)
3. ⏱️ **时间** - 完整分析需要3-5分钟
4. 📏 **长度** - 建议视频时长 < 30分钟
5. 🔐 **版权** - 仅供学习分析使用,勿用于商业目的

---

## 故障排除

### 下载失败
- 检查网络连接
- 尝试使用代理
- B站可能需要Cookie认证

### Whisper转写失败
- 确认OPENAI_API_KEY正确设置
- 检查API余额
- 音频文件是否损坏

### ffmpeg问题
- 确认ffmpeg已安装: `ffmpeg -version`
- Mac用户: `brew install ffmpeg`
```

Popular in Design & Media

Data month: 2026-09 · Downloads, stars and installs are aggregated monthly from public skill registries (ClawHub, SkillHub). See methodology.