How do I install the Video Analyzer skill?

Run npx skillmds@latest add modbender/video-analyzer-2 in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Video Analyzer safe to use?

This skill has not completed SkillMD's automated safety review yet. Independent scanners report: SkillSpector: PASS, Skill Scanner: PASS. Capability flags: executes scripts. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Video Analyzer?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Video Analyzer free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Video Analyzer?

modbender (@modbender) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Video Analyzer by modbender — Agent Skill

Name: Video Analyzer
Rating: 4.666666666666667 (3 reviews)
Author: modbender

File contents

Video Analyzer 🎥

A tool to download, transcribe, and analyze videos from any platform using a smart two-tier system (yt-dlp for fast subtitles, local whisper-cpp for robust fallback).

How to Use

When the user asks you to summarize, transcribe, or download a video/audio from a URL, use the bundled python script:

uv run {baseDir}/scripts/analyze_video.py --action <ACTION> --url "<URL>" [--quality <normal|max>] [--lang <en|it|etc>]

Supported Actions:

transcript: Extracts the text with timestamps. Use this when the user asks for a summary or transcript.
download-video: Downloads the video as MP4 to the Desktop.
download-audio: Downloads the audio as M4A/MP3 to the Desktop.

Analyzing a Video (IMPORTANT)

If the user asks for a summary, analysis, or key moments:

Run the script with --action transcript.
The script will output the path to a .txt file containing the timestamped transcript.
Read that file.
Output your response EXACTLY in this Markdown format:

## 📝 TL;DR
[A punchy 3-sentence summary of the video's core message]

## ⏱️ Key Moments
- [MM:SS] [Brief description of what is discussed]
- [MM:SS] [Brief description of what is discussed]
- [MM:SS] [Brief description of what is discussed]
*(Extract 3 to 7 key moments depending on video length)*

## 💡 Actionable Insights
1. [Practical takeaway 1]
2. [Practical takeaway 2]
3. [Practical takeaway 3]

---

Local Whisper Quality

If the script needs to fall back to Whisper (e.g., for X/Twitter videos), it uses normal by default:

normal: Fast (~1 min for 30 min video) — Default
max: Best quality (~5 min for 30 min video) — use --quality max when accuracy is critical

Multilingual Support

All Whisper models are multilingual by default. The skill can transcribe videos in any language (Italian, Spanish, Japanese, etc.).

IMPORTANT: Always respond to the user in THEIR language, not the video's language. If the user speaks Italian but sends an English video, give them the summary in Italian.

Finding specific moments

The transcript includes precise timestamps like [05:53] text.... If the user asks "When do they talk about X?", grep the transcript and return the exact timestamp from the file.

---name: video-analyzer-2description: Download, transcribe, and analyze videos from YouTube, X/Twitter, and TikTok with local Whisper processing. Perfect for extracting TL;DRs, timestamps, and actionable insights.---# Video Analyzer 🎥A tool to download, transcribe, and analyze videos from any platform using a smart two-tier system (yt-dlp for fast subtitles, local whisper-cpp for robust fallback).## How to UseWhen the user asks you to summarize, transcribe, or download a video/audio from a URL, use the bundled python script:```bashuv run {baseDir}/scripts/analyze_video.py --action <ACTION> --url "<URL>" [--quality <normal|max>] [--lang <en|it|etc>]```### Supported Actions:- `transcript`: Extracts the text with timestamps. **Use this when the user asks for a summary or transcript.**- `download-video`: Downloads the video as MP4 to the Desktop.- `download-audio`: Downloads the audio as M4A/MP3 to the Desktop.### Analyzing a Video (IMPORTANT)If the user asks for a **summary, analysis, or key moments**:1. Run the script with `--action transcript`.2. The script will output the path to a `.txt` file containing the timestamped transcript.3. Read that file.4. Output your response **EXACTLY** in this Markdown format:```markdown## 📝 TL;DR[A punchy 3-sentence summary of the video's core message]## ⏱️ Key Moments- [MM:SS] [Brief description of what is discussed]- [MM:SS] [Brief description of what is discussed]- [MM:SS] [Brief description of what is discussed]*(Extract 3 to 7 key moments depending on video length)*## 💡 Actionable Insights1. [Practical takeaway 1]2. [Practical takeaway 2]3. [Practical takeaway 3]---```### Local Whisper QualityIf the script needs to fall back to Whisper (e.g., for X/Twitter videos), it uses `normal` by default:- `normal`: Fast (~1 min for 30 min video) — **Default**- `max`: Best quality (~5 min for 30 min video) — use `--quality max` when accuracy is critical### Multilingual SupportAll Whisper models are **multilingual by default**. The skill can transcribe videos in any language (Italian, Spanish, Japanese, etc.).**IMPORTANT:** Always respond to the user in THEIR language, not the video's language. If the user speaks Italian but sends an English video, give them the summary in Italian. ### Finding specific momentsThe transcript includes **precise timestamps** like `[05:53] text...`. If the user asks "When do they talk about X?", grep the transcript and return the exact timestamp from the file.

Frequently asked questions

Video Analyzer