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Samueladewole/claude-skills

Analyze a short-form video (TikTok, Instagram Reel, YouTube Short, or any MP4) to extract its full transcript, understand why it performed, and generate concrete repurposing ideas. Use this skill whenever the user asks to: analyze a video, understand why something went viral, reverse-engineer a creator's content, extract a transcript from a video, figure out what makes a video perform, or get repurposing ideas from a video. Also trigger when the user says things like "why did this perform", "what's the hook here", "can I repurpose this", "analyze this TikTok/Reel", or drops a video file path or URL.

claude-skills とは?

claude-skills is a Claude Code agent skill that analyze a short-form video (TikTok, Instagram Reel, YouTube Short, or any MP4) to extract its full transcript, understand why it performed, and generate concrete repurposing ideas. Use this skill whenever the user asks to: analyze a video, understand why something went viral, reverse-engineer a creator's content, extract a transcript from a video, figure out what makes a video perform, or get repurposing ideas from a video. Also trigger when the user says things like "why did this perform", "what's the hook here", "can I repurpose this", "analyze this TikTok/Reel", or drops a video file path or URL.

対応✓Claude Code~Codex CLI~Cursor✓Gemini CLI
npx skills add https://github.com/Samueladewole/claude-skills/tree/HEAD/video-performance-analyzer

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ドキュメント

Video Performance Analyzer

What This Skill Does

Takes a short-form video (MP4 file or YouTube URL) and returns:

  1. Full transcript — every spoken word, on-screen text, audio cues, with timestamps
  2. Performance analysis — why it works, mapped against proven growth frameworks
  3. Repurposing playbook — concrete content ideas derived from the video

Setup

API Key: Set GEMINI_API_KEY as environment variable (in .zshrc or .env)

Install dependency (one-time):

pip install google-genai

Script location: <skill-directory>/scripts/analyze_video.py


Input Formats

FormatHow to pass itNotes
Local MP4 fileFile path as argumentAny size up to 2GB (free) / 20GB (paid)
YouTube URLURL as argumentPublic videos only
TikTok / InstagramDownload first with yt-dlp, then pass MP4 pathyt-dlp -o video.mp4 <URL>

Running the Analysis

Quick run

python <skill-directory>/scripts/analyze_video.py /path/to/video.mp4

YouTube URL

python <skill-directory>/scripts/analyze_video.py "https://www.youtube.com/watch?v=VIDEO_ID"

With output saved to file

python <skill-directory>/scripts/analyze_video.py /path/to/video.mp4 --output /path/to/output.md

Download + analyze Instagram Reel / TikTok (two-step)

yt-dlp -o /tmp/reel.mp4 "https://www.instagram.com/reel/XXXX/"
python <skill-directory>/scripts/analyze_video.py /tmp/reel.mp4 --output ~/Desktop/analysis.md

Analysis Workflow

Step 1: Run the script

The script will:

  • Upload the video to Gemini Files API (or pass YouTube URL directly)
  • Wait for processing (usually 10-30 seconds)
  • Send the analysis prompt to Gemini
  • Return structured Markdown output

Step 2: Map against growth frameworks

After the script returns, interpret output through these dimensions:

Hook — "The Hook Is a Contract"

  • Did the hook make the viewer feel implicated, called out, or urgently curious?
  • 5 hook techniques: Contradiction, Specific number + unexpected context, Direct accusation, Stolen thought, Absurd reframe
  • Framing trick: deliberate word choice that raises perceived stakes

Structure — Progressive Intrigue

  • Map each timestamp beat and score whether stakes escalate beat-to-beat
  • "therefore/but" chain — does each beat cause the next, or just follow it?
  • Identify where information gaps open and close

Credibility — Specificity Signal

  • Count concrete numbers, named people, specific dates, dollar amounts
  • "Documentary proof" moments (showing receipts/sources visually)
  • Generic claims = weak. Named + numbered claims = strong.

Framing — Reader-First

  • Is the video about the creator's achievement, or the viewer's situation?
  • Personal milestone framing = performs with existing audience, dies everywhere else

Retention — Visual Pattern Interrupts

  • Visual change frequency: every 5-10s is the target
  • Transitions, overlays, text cards, B-roll cuts that reset attention

CTA — Loop-Closing vs. Loop-Opening

  • Best CTAs create a condition where following is the obvious next move
  • Weak: "like and follow" / Strong: "we'll see what happens" (forward momentum)

Step 3: Generate repurposing ideas

For each idea:

  • Format (short-form video, LinkedIn post, X thread, newsletter)
  • Hook/banner
  • Content pillar mapping
  • Funnel stage (TOFU / MOFU / BOFU)

Sources to mine:

  • Strongest single claim → standalone hot take
  • "Before/after" or "X vs. Y" implicit in narrative → comparison format
  • Step-by-step workflow → listicle or tools video
  • Emotional core (fear, surprise, outrage, relief) → personal angle script
  • Stats/numbers → data-driven short-form
  • Contrarian framing → X thread or newsletter hook

Output Format

1. Full Transcript

Timestamped, verbatim. On-screen text overlays noted inline.

2. Visual & Audio Breakdown

  • Format, background/set quality, music/audio tone, visual change frequency

3. Performance Scorecard

DimensionScoreNotes
Hook strength
Progressive intrigue
Specificity / credibility
Reader-first framing
Visual pattern interrupts
CTA quality

4. Repurposing Playbook (4-8 ideas, at least 2 immediately scriptable)

5. What to Steal (3-5 specific, actionable techniques)


Model Selection

  • Default: gemini-2.5-flash — best balance of speed + video understanding
  • Premium: gemini-2.5-pro — use for longer videos or deeper analysis (pass --model gemini-2.5-pro)
  • Free tier limits: 8 hours of YouTube video/day. Short-form videos are well within limits.

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