videocut_剪口播（videocut 搜索） Skills下载安装命令和教程

name: videocut:剪口播 description: 口播视频转录和口误识别。生成审查稿和删除任务清单。触发词：剪口播、处理视频、识别口误

剪口播 v2

火山引擎转录 + AI 口误识别 + 网页审核

快速使用

用户: 帮我剪这个口播视频
用户: 处理一下这个视频

输出目录结构

output/
└── YYYY-MM-DD_视频名/
    ├── 剪口播/
    │   ├── 1_转录/
    │   │   ├── audio.mp3
    │   │   ├── volcengine_result.json
    │   │   └── subtitles_words.json
    │   ├── 2_分析/
    │   │   ├── readable.txt
    │   │   ├── auto_selected.json
    │   │   └── 口误分析.md
    │   └── 3_审核/
    │       ├── review.html
    │       └── video.mp4 → 源视频(符号链接)
    └── 字幕/
        └── ...

规则：已有文件夹则复用，否则新建。

流程

0. 创建输出目录
    ↓
1. 提取音频 (ffmpeg)
    ↓
2. 上传获取公网 URL (uguu.se)
    ↓
3. 火山引擎 API 转录
    ↓
4. 生成字级别字幕 (subtitles_words.json)
    ↓
5. AI 分析口误/静音，生成预选列表 (auto_selected.json)
    ↓
6. 生成审核网页 (review.html)
    ↓
7. 启动审核服务器，用户网页确认
    ↓
【等待用户确认】→ 网页点击「执行剪辑」或手动 /剪辑

执行步骤

步骤 0: 创建输出目录

# 变量设置（根据实际视频调整）
VIDEO_PATH="/path/to/视频.mp4"
VIDEO_NAME=$(basename "$VIDEO_PATH" .mp4)
DATE=$(date +%Y-%m-%d)
BASE_DIR="output/${DATE}_${VIDEO_NAME}/剪口播"

# 创建子目录
mkdir -p "$BASE_DIR/1_转录" "$BASE_DIR/2_分析" "$BASE_DIR/3_审核"
cd "$BASE_DIR"

步骤 1-3: 转录

cd 1_转录

# 1. 提取音频（文件名有冒号需加 file: 前缀）
ffmpeg -i "file:$VIDEO_PATH" -vn -acodec libmp3lame -y audio.mp3

# 2. 上传获取公网 URL
curl -s -F "files[]=@audio.mp3" https://uguu.se/upload
# 返回: {"success":true,"files":[{"url":"https://h.uguu.se/xxx.mp3"}]}

# 3. 调用火山引擎 API
SKILL_DIR="/Users/chengfeng/Desktop/AIos/剪辑Agent/.claude/skills/剪口播"
"$SKILL_DIR/scripts/volcengine_transcribe.sh" "https://h.uguu.se/xxx.mp3"
# 输出: volcengine_result.json

步骤 4: 生成字幕

node "$SKILL_DIR/scripts/generate_subtitles.js" volcengine_result.json
# 输出: subtitles_words.json

cd ..

步骤 5: 分析口误（脚本+AI）

5.1 生成易读格式

cd 2_分析

node -e "
const data = require('../1_转录/subtitles_words.json');
let output = [];
data.forEach((w, i) => {
  if (w.isGap) {
    const dur = (w.end - w.start).toFixed(2);
    if (dur >= 0.2) output.push(i + '|[静' + dur + 's]|' + w.start.toFixed(2) + '-' + w.end.toFixed(2));
  } else {
    output.push(i + '|' + w.text + '|' + w.start.toFixed(2) + '-' + w.end.toFixed(2));
  }
});
require('fs').writeFileSync('readable.txt', output.join('\\n'));
"

5.2 读取用户习惯

先读 用户习惯/ 目录下所有规则文件。

5.3 生成句子列表（关键步骤）

必须先分句，再分析。按静音切分成句子列表：

node -e "
const data = require('../1_转录/subtitles_words.json');
let sentences = [];
let curr = { text: '', startIdx: -1, endIdx: -1 };

data.forEach((w, i) => {
  const isLongGap = w.isGap && (w.end - w.start) >= 0.5;
  if (isLongGap) {
    if (curr.text.length > 0) sentences.push({...curr});
    curr = { text: '', startIdx: -1, endIdx: -1 };
  } else if (!w.isGap) {
    if (curr.startIdx === -1) curr.startIdx = i;
    curr.text += w.text;
    curr.endIdx = i;
  }
});
if (curr.text.length > 0) sentences.push(curr);

sentences.forEach((s, i) => {
  console.log(i + '|' + s.startIdx + '-' + s.endIdx + '|' + s.text);
});
" > sentences.txt

5.4 脚本自动标记静音（必须先执行）

node -e "
const words = require('../1_转录/subtitles_words.json');
const selected = [];
words.forEach((w, i) => {
  if (w.isGap && (w.end - w.start) >= 0.2) selected.push(i);
});
require('fs').writeFileSync('auto_selected.json', JSON.stringify(selected, null, 2));
console.log('≥0.2s静音数量:', selected.length);
"

→ 输出 auto_selected.json（只含静音 idx）

5.5 AI 分析口误（追加到 auto_selected.json）

检测规则（按优先级）：

#	类型	判断方法	删除范围
1	重复句	相邻句子开头≥5字相同	较短的整句
2	隔一句重复	中间是残句时，比对前后句	前句+残句
3	残句	话说一半+静音	整个残句
4	句内重复	A+中间+A 模式	前面部分
5	卡顿词	那个那个、就是就是	前面部分
6	重说纠正	部分重复/否定纠正	前面部分
7	语气词	嗯、啊、那个	标记但不自动删

核心原则：

先分句，再比对：用 sentences.txt 比对相邻句子
整句删除：残句、重复句都要删整句，不只是删异常的几个字
范围整段删除：标记口误时，从 startIdx 到 endIdx 之间的所有元素（含中间的 gap，不管多短）全部加入 auto_selected。不要逐个挑选文字 idx 而跳过 gap

分段分析（循环执行）：

1. Read readable.txt offset=N limit=300
2. 结合 sentences.txt 分析这300行
3. 追加口误 idx 到 auto_selected.json
4. 记录到 口误分析.md
5. N += 300，回到步骤1

🚨 关键警告：行号 ≠ idx

readable.txt 格式: idx|内容|时间
                   ↑ 用这个值

行号1500 → "1568|[静1.02s]|..."  ← idx是1568，不是1500！

口误分析.md 格式：

## 第N段 (行号范围)

| idx | 时间 | 类型 | 内容 | 处理 |
|-----|------|------|------|------|
| 65-75 | 15.80-17.66 | 重复句 | "这是我剪出来的一个案例" | 删 |

步骤 6-7: 审核

cd ../3_审核

# 6. 生成审核网页（传入视频文件，自动创建符号链接）
node "$SKILL_DIR/scripts/generate_review.js" ../1_转录/subtitles_words.json ../2_分析/auto_selected.json "$VIDEO_PATH"
# 输出: review.html, video.mp4(符号链接)

# 7. 启动审核服务器
node "$SKILL_DIR/scripts/review_server.js" 8899 "$VIDEO_PATH"
# 打开 http://localhost:8899

⚠️ 必须用 review_server.js，不能用 python3 -m http.server 替代。原因：视频播放依赖 HTTP Range 请求（206），python 简易服务器不支持，会导致视频无法播放/无声音。启动时不要在命令末尾加 &（shell 后台），用 run_in_background 参数即可。

用户在网页中：

播放视频画面确认
勾选/取消删除项
点击「执行剪辑」

数据格式

subtitles_words.json

[
  {"text": "大", "start": 0.12, "end": 0.2, "isGap": false},
  {"text": "", "start": 6.78, "end": 7.48, "isGap": true}
]

auto_selected.json

[72, 85, 120]  // Claude 分析生成的预选索引

剪辑编码（硬性规则）

⚠️ 匹配原片参数重编码，帧级精确切割。

cut_video.sh 的工作方式：

自动检测原片编码参数（codec/profile/pix_fmt/bitrate）
用 filter_complex trim+concat 帧级精确切割
以相同参数重编码：-profile:v high -b:v {原片码率} -pix_fmt yuv420p

关键：重编码画质取决于是否匹配原片参数，不是 CRF 值。

✅ -b:v {原片码率} -profile:v high -pix_fmt yuv420p → 肉眼无区别
❌ 只指定 -crf N 不指定 profile/pix_fmt → 可能有偏差

配置

火山引擎 API Key

cd /Users/chengfeng/Desktop/AIos/剪辑Agent/.claude/skills
cp .env.example .env
# 编辑 .env 填入 VOLCENGINE_API_KEY=xxx

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Agent SkillsThe universal skill manager for 42+ AI coding agents. Install 175,000+ skills with one command.ProductMercado Documentación Preguntas frecuentesResourcesGitHub npm Package Changelog Report IssueSupported AgentsCursor Claude Code GitHub Copilot Gemini CLI Windsurf & Cline +37 more agents© 2026 Agent Skills. Código abierto.Made with ♥ for the AI developer 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videocut_剪口播（videocut 搜索）

安装方式

简介

SKILL.md