Tiktok Targeted Analysis

TikTok Targeted Video Analysis Skill

PURPOSE: Deep analysis of competitor/inspiration TikTok videos for exact structural replication

KEY DISTINCTION: Unlike the product-based workflow (scrape → top 5 videos → 3 different scripts), this skill analyzes specific user-provided URLs to generate 1 exact replica script with AI-ready video generation prompts.

What This Skill Does

Input

• CSV file with TikTok URLs or single URL via command line
• CSV columns: url, product_name, campaign_id (optional)

Output (per video)

targeted_analysis/YYYYMMDD/{video_id}/
├── metadata.json                 # Creator, views, likes, duration
├── video.mp4                     # Downloaded video
├── frames/ (every 2s)            # Keyframes for analysis
├── audio.mp3                     # Extracted audio
├── transcript.json               # Hybrid transcription
├── analysis.md                   # Combined 3-part analysis
├── character_descriptions.md     # Detailed casting guide
├── replication_script.md         # Obsidian-ready script
├── ai_video_prompts.md           # Shot-by-shot Veo/Sora prompts
├── processing_status.json        # Phase completion tracking
└── analysis.log                  # Debug log

5-Phase Pipeline

Phase 1: Metadata Extraction

• Extract video ID from URL (regex + yt-dlp fallback)
• Fetch metadata: creator, views, likes, duration, title
• Download video file with yt-dlp
• Output: metadata.json, video.mp4

Phase 2: Frame + Audio Extraction + Transcription

• FFmpeg: Extract keyframes every 2 seconds (vs 3s in product workflow)
• FFmpeg: Extract audio track
• Hybrid transcription: TikTok captions → Whisper fallback → None
• Output: frames/, audio.mp3, transcript.json

Phase 3: Comprehensive Analysis (4 Sub-Phases)

3A: Structural Analysis

• Shot-by-shot storyboard with timestamps
• Camera specs: Close-up/Medium/Wide, Static/Pan/Handheld
• Transition analysis (cuts, dissolves)
• Text overlays catalog
• Visual composition (framing, lighting, color grading)

3B: Content Analysis

• Hook dissection (first 3 seconds, matches to 8 core patterns)
• Voiceover with emotion markers
• Music/audio strategy
• Product embedding timeline

3C: Strategic Analysis

• Target audience (demographics + psychographics)
• Psychological triggers (FOMO, social proof, authority)
• Germany market fit score
• Replication blueprint (copy/adapt/avoid)
• Production requirements (budget, equipment, talent)

3D: Character Descriptions

• Physical appearance (age, gender, hair, build)
• Clothing details
• Body language and gestures
• Vocal characteristics
• Casting notes

Output: analysis.md (combined), character_descriptions.md

Phase 4: Replication Script Generation

• 100% structure/hook/timing copy
• Slightly varied dialogue (same meaning, different words)
• YAML frontmatter (Obsidian-ready)
• German VO + Chinese translation (mandatory)
• ElevenLabs v3 tone markers
• Visual strategy table
• Output: replication_script.md

Phase 5: AI Video Prompts Generation

• Shot-by-shot prompts in markdown code blocks
• Format: ```veo-prompt for Obsidian copy-paste
• Each prompt includes: camera, subject, lighting, audio cues
• Output: ai_video_prompts.md

Usage

Prerequisites

# Ensure you're at repo root
cd /Users/lxt/Movies/TikTok/WZ/lukas_9688

# Virtual environment with dependencies
cd scripts
source venv/bin/activate

# Required tools
which yt-dlp    # Video downloading
which ffmpeg    # Frame/audio extraction
which gemini    # Analysis
python -c "from faster_whisper import WhisperModel" # Transcription

Single Video Analysis

python scripts/analyze_targeted_video.py \
  --url "https://www.tiktok.com/@username/video/1234567890" \
  --product-name "Your Product Name" \
  --output-dir "targeted_analysis/20260114"

Time: ~5-10 minutes per video Cost: ~$0.30-0.60 (Gemini API)

Batch Processing

1. Create CSV file:

url,product_name,campaign_id
https://www.tiktok.com/@user1/video/111,Product A,winter_2026
https://www.tiktok.com/@user2/video/222,Product B,
https://www.tiktok.com/@user3/video/333,Product C,spring_2026

2. Run batch:

python scripts/analyze_targeted_batch.py \
  --csv targeted_videos.csv \
  --output-dir "targeted_analysis/20260114" \
  --max-workers 3

Time: 10 videos ÷ 3 workers × 8 min ≈ 27 minutes Cost: ~$3-6 for 10 videos

Skip Phases (Resume from Checkpoint)

If a phase fails or you want to regenerate later phases:

python scripts/analyze_targeted_video.py \
  --url "..." \
  --product-name "..." \
  --output-dir "..." \
  --skip-phases "1,2"  # Skip metadata and extraction, use existing data

Useful for:

• Regenerating scripts without re-analyzing
• Testing prompts without re-downloading

Quality Gates

Phase 1 Success

• ✅ metadata.json exists with creator, views, duration
• ✅ video.mp4 exists (size > 100KB)

Phase 2 Success

• ✅ Frame count = (duration / 2) ±1
• ✅ audio.mp3 exists OR marked "silent"
• ✅ transcript.json exists (source: tiktok_captions, whisper_transcription, or none)

Phase 3 Success

• ✅ analysis.md has all 3 parts (structural, content, strategic)
• ✅ Shot table has ≥ (frame_count / 2) shots
• ✅ Hook analysis references Tiktok_Golden_3_seconds.md patterns
• ✅ character_descriptions.md has ≥ 1 character
• ✅ No meta-text pollution ("I will...", "Loaded credentials...")
• ✅ Minimum 1500 lines combined

Phase 4 Success

• ✅ replication_script.md has valid YAML frontmatter
• ✅ Contains: Structure, Visual Strategy, German VO, Chinese translation
• ✅ Duration matches original ±5s

Phase 5 Success

• ✅ One ```veo-prompt per shot
• ✅ Each block has: camera, subject, lighting, audio
• ✅ No generic prompts

Integration with Existing Workflow

Comparison:

No conflicts - separate directories and workflows.

Key Technical Decisions

1. Frame Interval: 2s vs 3s

Why 2s: TikTok videos are short (30-60s). More frames = better shot detection for precise replication. Trade-off: +50% cost (~$0.10 more) but critical for accuracy.

2. Three-Phase Gemini Analysis

Why separate: Focused prompts (structural → content → strategic) produce better results than one mega-prompt.

3. AI Prompt Format

Why code blocks: User requested copy-paste functionality in Obsidian. Visual separation, easy to copy entire block for Veo/Sora.

4. Character Descriptions Separation

Why separate file: Too detailed for main analysis, critical for casting. Enables precise replication.

5. 1 Script (not 3)

Why: User requirement - 100% exact structure replication for same product, slightly varied dialogue only.

Error Handling

Download Failures

• Symptom: yt-dlp timeout or rate limit
• Solution: Uses --cookies-from-browser chrome flag, 3 retries with exponential backoff
• Fallback: Manual download (provide local file path)

Transcription Failures

• Symptom: No TikTok captions + Whisper fails
• Solution: Graceful fallback to source: none (music-only video)
• Impact: Analysis still proceeds with visual-only context

Gemini Capacity Errors

• Symptom: "You have exhausted your capacity"
• Solution: Automatic fallback to gemini-3-flash-preview
• Retry: Uses exponential backoff

Character Detection Issues

• Symptom: Gemini misses subtle casting details
• Solution: Export character reference frames to frames/characters/
• Manual review: Human can refine descriptions post-analysis

Performance & Costs

Single Video

Batch (10 videos, 3 concurrent)

• Time: ~27 minutes
• Cost: ~$4.00

Common Issues & Solutions

Issue: "Invalid TikTok URL format"

Cause: Unsupported URL structure Solution: Ensure URL format matches:

• https://www.tiktok.com/@user/video/123456
• https://vm.tiktok.com/ABCDEF (short URL)

Issue: "No frames found"

Cause: FFmpeg extraction failed Solution: Check video file integrity, ensure ffmpeg installed

Issue: "Replication script missing frontmatter"

Cause: Gemini output formatting issue Solution: Re-run Phase 4 with --skip-phases 1,2,3

Issue: "Analysis too generic"

Cause: Insufficient frame granularity Solution: Default 2s interval should be sufficient; check frame count matches (duration / 2) ±1

Copyright & Legal Considerations

⚠️ IMPORTANT DISCLAIMER:

This skill generates replication scripts based on competitor videos. Key points:

1. 100% structure copy + varied dialogue is a legal gray area
2. User is responsible for final usage and copyright compliance
3. Recommendation: Use as "inspiration" not "copy"
4. High-risk videos: Viral/professional productions may be closely monitored
5. Best practice: Significant dialogue variation + unique visual styling

Generated replication_script.md includes prominent disclaimer.

File Structure After Completion

targeted_analysis/
└── 20260114/                         # Batch date
    ├── 1234567890/                   # Video ID 1
    │   ├── metadata.json
    │   ├── video.mp4
    │   ├── frames/
    │   │   ├── frame_001.jpg
    │   │   ├── frame_002.jpg
    │   │   └── ...
    │   ├── audio.mp3
    │   ├── transcript.json
    │   ├── analysis.md               # Combined 3-part analysis
    │   ├── character_descriptions.md
    │   ├── replication_script.md     # Obsidian-ready
    │   ├── ai_video_prompts.md       # Copy-paste ready
    │   ├── processing_status.json
    │   └── analysis.log
    ├── 2345678901/                   # Video ID 2
    │   └── ...
    └── 3456789012/                   # Video ID 3
        └── ...

Next Steps After Analysis

1. Review Analysis: Read analysis.md to understand video strategy
2. Check Character Casting: Use character_descriptions.md for talent selection
3. Adapt Script: Review replication_script.md, adjust dialogue as needed
4. Generate Video: Copy prompts from ai_video_prompts.md to Veo 3.1/Sora
5. Quality Check: Ensure generated shots match analysis specifications
6. Final Assembly: Edit shots together, add VO, music, text overlays

Version History

v1.0.0 (2026-01-14)

• Initial release
• 5-phase pipeline (metadata → extraction → analysis → script → prompts)
• 2-second frame intervals for precise shot detection
• Hybrid transcription (TikTok → Whisper → None)
• 4-part analysis (structural, content, strategic, character)
• 1 exact replica script with varied dialogue
• AI video prompts in markdown code blocks
• Batch processing with 3 concurrent workers
• Comprehensive error handling and fallbacks

Generated by: Claude Code Repository: /Users/lxt/Movies/TikTok/WZ/lukas_9688 Related Skills: tiktok_product_scraper.md, tiktok_ad_analysis.md, tiktok_script_generator.md