Creative Review

Creative Review — Style Adherence & Feedback Loop

Validate generated creative assets against a reference style brief. Score adherence, produce actionable feedback, and feed improvements back into the generation pipeline.

Compounding Skills

Review Pipeline

REFERENCE → EXTRACT BRIEF → GENERATE ASSET → REVIEW → SCORE → FEEDBACK → ITERATE

Phase 1: Reference Extraction

When given a reference video or image:

1. Download the reference (yt-dlp for URLs, direct path for local files) 2. Extract frames at 1fps: ffmpeg -i ref.mp4 -vf "fps=1" frames/frame_%03d.png 3. Analyze each frame for:

• Color palette (dominant colors, background, accent)
• Typography (font style, size, placement, weight)
• Composition (layout, perspective, depth)
• Motion style (cuts, transitions, pacing)
• Material treatment (glass, shadow, glow, reflection)

4. Produce a style brief — structured document capturing all visual attributes

Style Brief Format

## Style Brief: {Reference Name}

### Palette
- Background: {hex}
- Panel fill: {rgba}
- Text primary: {hex}
- Accent: {hex}

### Typography
- Font: {family}
- Weight: {bold/regular}
- Placement: {center/left/overlay}
- Max words per card: {N}

### Composition
- Panel perspective: {degrees}
- Panel material: {glass/solid/wireframe}
- Depth technique: {shadow/glow/parallax}
- Background treatment: {void/gradient/particles}

### Motion
- Entrance style: {spring/fade/slide}
- Scene duration: {N-N seconds}
- Transition type: {cut/crossfade/spring}
- Pacing: {fast/confident/slow}

### Audio
- Style: {ambient/narration/music}
- Sync points: {beat drops/scene changes}

Phase 2: Asset Review

When given a generated asset to review:

Video Review Process

1. Extract frames at 1fps from the generated video 2. Compare frame-by-frame against the style brief criteria 3. Score each dimension (0-10):

4. Overall score: Weighted average (0-100)

Scoring Bands

Phase 3: Feedback Generation

For each dimension scoring below 8/10, generate specific, actionable feedback:

Feedback Format

## Creative Review: {Asset Name}

**Overall Score**: {N}/100 ({Rating})
**Reference**: {Brief Name}

### Scores
| Dimension | Score | Notes |
|-----------|-------|-------|
| Color adherence | {N}/10 | {specific note} |
| Typography | {N}/10 | {specific note} |
| ... | ... | ... |

### Must Fix (score < 6)
1. {Specific issue} → {Specific fix with code/prompt change}
2. ...

### Should Fix (score 6-7)
1. {Issue} → {Fix}

### Nice to Have (score 8-9)
1. {Polish suggestion}

### What Worked Well
- {Positive observation}
- {Pattern to keep}

Phase 4: Self-Evolution

After Each Review Cycle

1. If the fix worked → Add the technique to the style brief as a confirmed pattern 2. If the fix didn't work → Document why and what was tried, update guidance 3. If a new technique emerged → Capture it and add to the relevant skill's references

Style Brief Evolution

The style brief is a living document. After each review cycle:

Initial brief (from reference extraction)
  → Review #1 feedback applied
    → Review #2: new patterns discovered
      → Brief updated with confirmed patterns
        → Next generation starts from improved brief

Cross-Skill Feedback

When review findings affect other skills, propagate:

Agent Behavior

On Review Invocation

1. Identify the asset — video file path, URL, or generated content package 2. Identify the reference — style brief, reference URL, or skill defaults (e.g., /launch-video checklist) 3. Extract frames from both (if video) 4. Score each dimension against the brief 5. Generate feedback with specific fixes 6. Report — overall score, must-fix items, what worked

Using /agent-browser for Video Review

When the asset is a deployed video (hosted URL):

# Install if needed
npm install -g @anthropic-ai/agent-browser

# Open and screenshot for review
agent-browser open "https://broomva.tech/images/writing/slug/reel.mp4"
agent-browser screenshot --output review-frame.png

For local files, use ffmpeg frame extraction instead.

Quick Review Command

/creative-review /path/to/video.mp4 --against launch-video

This automatically: 1. Extracts frames from the video 2. Loads the /launch-video quality checklist 3. Scores each dimension 4. Reports findings with specific fixes

Quality Gate Integration

The creative review can be wired as a gate in the /blog-post pipeline:

Phase 6 (Media) → Generate video
  → /creative-review scores the output
    → Score ≥ 75? → Proceed to Phase 7
    → Score < 75? → Iterate with feedback → Re-generate → Re-review

This creates an automatic quality loop — no substandard creative ships.