Content Dna

Content DNA

Reverse-engineer what made a video work. Seven dimensions, structured output, portable bricks you can adapt.

Usage

Single video

/content-dna https://www.tiktok.com/@creator/video/123

With adaptation for your niche

/content-dna https://www.tiktok.com/@creator/video/123 --adapt --niche "AI marketing"

With explicit voice choice

/content-dna https://www.tiktok.com/@creator/video/123 --adapt --niche "pet brand" --voice-mode analysis
/content-dna https://www.tiktok.com/@creator/video/123 --adapt --niche "pet brand" --voice-mode personal
/content-dna https://www.tiktok.com/@creator/video/123 --adapt --niche "pet brand" --brand /path/to/client-voice.md --voice-mode brand

Shell

bash ~/clawd/skills/content-dna/scripts/content-dna.sh \
  --url "VIDEO_URL" \
  --adapt \
  --niche "AI marketing"

What You Get

7 Dimensions:

1. Topic — what the video is about at a high level
2. Angle — the specific take that makes it unique
3. Hook Structure — visual hook + text on screen + spoken opening line
4. Story Structure — beat-by-beat narrative
5. Visual Format — talking head / split-screen / green screen / etc
6. Key Visuals — the specific shots that carry the idea
7. Audio — VO style, pacing, music, sound design

Performance Layer:

• Primary driver + secondary driver
• Engagement type: debate / utility / inspiration / entertainment / FOMO
• Why comments were high

Strategic Readouts:

• Brick name
• Brick definition
• One-paragraph explanation of why it worked
• Plain-English takeaway: Use this when...

Portable Bricks:

• The reusable mechanical elements (rated high/medium/low portability)
• Why each transfers to other niches

Adapted Concepts (with --adapt):

• 3 ready-to-brief concepts for your niche
• Each uses a different portable brick
• Written in the selected output voice
• Keep source niche and output voice separate when needed

How It Works

1. ScrapeCreators fetches video metadata + transcript (if available)
2. Cover image + metadata sent to Gemini Flash 3 via OpenRouter
3. Gemini returns structured JSON with the 7-dimension breakdown + performance layer + brick analysis + adapted concepts
4. The script prints a human-readable markdown-style breakdown for chat use and saves the enriched JSON to ~/clawd/workspace/content-dna/outputs/

Source Niche vs Output Voice

Treat these as separate choices:

• Source niche: where the outlier came from
• Output voice: who the adapted concept is for

Use this decision rule:

• If you want brand-native output, pass an explicit brand voice file.
• If you want to borrow mechanics from another niche for your own content, use personal voice intentionally.
• If you just want analysis, use --voice-mode analysis and avoid forcing a brand voice onto the adaptation.

If the niche and active voice look mismatched, ask:

Do you want this adapted for the niche's brand voice, your own voice, or just as raw pattern analysis?

Integration with Larger Pipelines

Content DNA should sit in the middle of the pipeline:

1. Discovery / signal pull
2. Content DNA analysis
3. Pattern aggregation
4. Final generation in the selected voice

If a user asks for the actual / full / real pipeline, do not skip the analysis stage and do not fill gaps with made-up output.