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tiktok-video-analyzer抖音视频分析器

Agent Skill

用于辅助视频生成、动画合成、脚本化剪辑或 Remotion 等视频项目开发。它适合让 Agent 组织镜头、生成素材说明、维护合成代码或排查渲染问题。使用时需要确认分辨率、时长、素材路径和导出格式;涉及外部素材、人物肖像或商业发布时,应先核对版权授权和内容审核要求。

总安装

38,220

周安装

1,625

GitHub Stars

5

下载量

13,390
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:tiktok-video-analyzer(抖音视频分析器)
来源仓库:https://github.com/holl4ndtv/tiktok-video-analyzer
安装命令:
openclaw skills install tiktok-video-analyzer
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install tiktok-video-analyzer

简介

通过 URL 分析来自 TikTok、YouTube、Instagram、Twitter 等的视频,在本地转录音频并回答有关内容的问题。

SKILL.md

Video Analyzer Skill

Analyze any video by dropping a URL. Works with TikTok, YouTube, Instagram, Twitter/X, and 1000+ other sites. Transcribes the audio locally and answers any question about the content.


When to Use This Skill

Activate when the user:

  • Shares a video URL (tiktok.com, youtube.com, instagram.com, twitter.com, x.com, etc.)
  • Asks "what is this video about", "summarize this", "what are they teaching", "what's the hook", etc.
  • Asks a question about a previously saved video

⚠️ CRITICAL RULES — READ BEFORE ANYTHING ELSE

Rule 1 — FIRST MESSAGE IS ALWAYS THIS, NO EXCEPTIONS:

Use the message tool to send this BEFORE running any exec command:

📡 Video received, analyzing...

This must be a message tool call, not your final reply text. Using the message tool sends it immediately to the user while you continue processing. If you put it in your reply text instead, the user won't see it until everything is done — which defeats the purpose entirely.

Do NOT reference conversation history, prior testing, or anything from the current session. Every URL is treated fresh.

Rule 2 — NEVER GO SILENT The user MUST receive a message every 30-60 seconds while processing. Silence = broken.

  • After download step: send "📥 Downloaded! Transcribing now..."
  • If anything takes more than 30 seconds: send "⏳ Still working..."

Rule 3 — NO PERSONAL COMMENTARY. EVER. Do NOT add ANY of the following:

  • "This appears to be the video we already tested"
  • "I recognize this URL" / "you've sent this before"
  • "Heads up — this is the same link"
  • Any footnote, parenthetical, or aside about the URL or prior usage

Just run the skill and give the answer. End with the save prompt. Nothing else. If the transcript is cached: say "📚 Found in your library!" then answer. That's it.

Rule 4 — First-run warning If the transcripts folder is empty (first ever run), warn upfront:

⚠️ First time running — downloading the AI model (~150MB). Takes 2-4 minutes once, never again.

Prerequisites Check

Before the first run, check if dependencies are installed:

which ffmpeg && python3 -c "import faster_whisper; print('ok')" && python3 -c "import yt_dlp; print('ok')"

If anything is missing, guide the user:

Mac/local:

brew install ffmpeg
pip3 install faster-whisper yt-dlp --break-system-packages

Linux/VPS:

apt install -y ffmpeg
pip install faster-whisper yt-dlp --break-system-packages

Flow

Step 1 — Acknowledge IMMEDIATELY (before anything else)

Send: 📡 Video received, analyzing...

Step 1b — First run warning

If this looks like the first time (no cached transcripts exist), warn the user:

⚠️ First time running — the AI transcription model needs to download (~150MB). This takes 2-4 minutes once and never again. Grab a coffee ☕

Step 2 — Download (step 1 of 2)

python3 ~/.openclaw/skills/tiktok-analyzer/transcribe.py --download-only "URL_HERE"

Returns JSON with status: "downloaded" and video_id. If from_cache: true + skip_transcribe: true → go straight to Step 3, skip Step 2b.

Step 2b — Send progress message (via message tool), then transcribe

Use the message tool to send: 📥 Downloaded! Transcribing now...

Then immediately run:

python3 ~/.openclaw/skills/tiktok-analyzer/transcribe.py --transcribe-only "VIDEO_ID"

Replace VIDEO_ID with the video_id from the previous step.

Returns JSON:

{
  "transcript": "full text here...",
  "language": "en",
  "video_id": "abc123",
  "from_cache": false
}

If from_cache: true (from Step 2) → say "📚 Found this in your library — instant answer!" and skip the wait messages.

If there's an "error" key → relay it cleanly (never show a Python stacktrace to the user).

Step 3 — Answer the question

Use the transcript to answer whatever they asked. If no specific question, provide:

  • What it's about (1-2 sentences)
  • Key points / what's being taught (bullet list)
  • Tone / style (educational, entertainment, story, etc.)

Step 4 — Offer to save (MANDATORY if from_cache: false)

After giving the answer, ALWAYS ask this — do not skip it:

💾 Want to save this transcript so you can ask follow-up questions later without re-downloading? (yes/no)

Only skip this if from_cache: true (already saved).

If yes:

python3 ~/.openclaw/skills/tiktok-analyzer/save_transcript.py "VIDEO_ID" 'JSON_DATA'

Confirm: ✅ Saved to your video library!


Searching Saved Transcripts

When the user asks about something they've analyzed before:

  1. List files in ~/.openclaw/skills/tiktok-analyzer/transcripts/
  2. Read the relevant .json file(s)
  3. Answer from the saved transcript

Error Handling

ErrorResponse
Private/removed video"This video is private or has been removed. Try a different URL."
No ffmpeg"You need ffmpeg. Run: brew install ffmpeg (Mac) or apt install ffmpeg (Linux)"
No faster-whisper"Run: pip install faster-whisper yt-dlp then try again."
Timeout / very long video"That one's taking a while — try a shorter clip or check your connection."

Demo Tips

  • For demos: Use a video you've already analyzed (cache hit = instant response, looks great)
  • First run: Always warn upfront about the 150MB model download
  • Works on any platform yt-dlp supports — TikTok, YouTube, Instagram, Twitter, Reddit, Vimeo, and 1000+ more

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

88.32%
按下载量换算11,826

安全审计

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通过

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通过

Static analysis

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权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

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