ab-aswini/asset-architect

Asset Architect V2.0 - Frame-Perfect Workflow Skill

Philosophy: True cinematic storytelling through motion, not disconnected slides. Core Principle: START[N] + MOTION[N] + END[N] = START[N+1]

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🎯 When to Use This Skill

Trigger when user requests:

• "Create complete asset workflow for [business type]"
• "Generate frame-perfect sequences for [website]"
• "Build cinematic scroll animation specifications for [vertical]"
• "I need image prompts and video sequences with exact continuity"
• "Design visual journey for [industry] website"
• Any mention of "canvas animation + scroll" + "seamless transitions"

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🔧 Workflow Overview

PHASE 1: Sequence Design (Frame Specifications)
   ↓
PHASE 2: Color Consistency Matrix
   ↓
PHASE 3: AI Video Tool Specifications
   ↓
PHASE 4: Technical Implementation Blueprint
   ↓
PHASE 5: Pre-Production Checklist
   ↓
PHASE 6: Client Pitch Materials

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PHASE 1: FRAME-PERFECT SEQUENCE DESIGN

Step 1: Define Visual Journey

Question Set for User:

1. What's the primary emotion/experience you want visitors to feel?
2. What's the logical spatial journey? (e.g., outside → inside → specific space)
3. How many key spaces/moments need to be shown? (3-5 recommended)
4. Any specific transitions that are important? (e.g., passing through door, ascending stairs)
5. Should sequences feel slow/luxurious or dynamic/energetic?

Output: Sequence Map

Sequence 1: [Start Point] → [End Point] (Duration: Xs)
Sequence 2: [Start Point] → [End Point] (Duration: Xs)
Sequence 3: [Start Point] → [End Point] (Duration: Xs)

Step 2: Design START Frame

### START FRAME (Frame 001)

SHOT TYPE: [Extreme Close-up / Close-up / Medium / Wide / Establishing]
Camera Position: [X meters distance, Y meters height, Z° angle]

Composition Breakdown:

- FOREGROUND (X% of frame):
  - Primary elements: [Specific objects, their appearance]
  - Colors: [Element]: #HEXCODE
  - Textures: [Describe materials, surfaces]
  - Focus state: [Sharp / Soft / Out of focus]
- MIDGROUND (Y% of frame):
  - Secondary elements: [Specific objects]
  - Focus state: [Sharp / Soft bokeh / Blurred]
  - Color palette: [Element]: #HEXCODE
- BACKGROUND (Z% of frame):
  - Context elements: [Environment, sky, walls]
  - Focus state: [Usually soft / out of focus]
  - Colors: [Element]: #HEXCODE

Technical Camera Settings:

- Focal Length: [Xmm equivalent]
- Aperture: f/X.X
- Focus Point: [Specific element at X distance]
- Depth of Field: [Xm before to Ym after]

Lighting Specification:

- Time of Day: [Morning / Midday / Golden Hour / Evening]
- Primary Light Source: [Sun / Window / Artificial]
- Light Direction: [Front-lit / Side-lit / Back-lit / Top-down]
- Light Quality: [Hard / Soft]
- Color Temperature: [X Kelvin]

Color Verification:
✓ Brand Primary (#HEXCODE) visible in [element]
✓ Brand Accent (#HEXCODE) visible in [element]
✓ Neutral Background (#HEXCODE) established

Step 3: Design Motion (Frame-by-Frame)

### MOTION DESCRIPTION (Frames 001-XXX)

Camera Movement Type:

- Primary: [Crane up/down, Dolly forward/back, Truck left/right, Orbit]
- Movement Quality: [Smooth linear / Ease-in / Ease-out / Ease-in-out]

Frame-by-Frame Transformation Logic:

**Frames 001-030 (0-1 second):**

- [Primary element] occupies [X%] of frame
- Camera at [position description]
- Focus on [element at distance X]
- [What's changing this second]

**Frames 031-060 (1-2 seconds):**

- [Continuation from previous]
- New elements entering: [description]
- Elements exiting: [description]
- Focus shift: [from where to where]

[Continue for complete sequence duration]

Step 4: Design END Frame

Same detailed format as START frame, with continuity checks:

CRITICAL: Verify END frame can serve as START frame for next sequence.
- Camera position achievable from next starting position ✓
- Lighting consistent with next sequence ✓
- Composition provides logical continuation ✓
- Color palette maintained ✓

Step 5: Continuity Verification

END Frame Camera Position: [8m distance, 1.6m height, 0° angle]
NEXT Sequence START Position: [8m distance, 1.6m height, 0° angle] ✓ MATCH
Lighting Transition: [None / Gradual interior→exterior]
Color Consistency: [List hex codes present in both frames]

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PHASE 2: COLOR CONSISTENCY MATRIX

| Element | Hex Code | RGB | Where Used | Consistency Rule | Variation Allowed | | ------------- | -------- | ----- | ----------- | ------------------------- | ------------------ | | Brand Primary | #XXXXXX | R,G,B | [Locations] | Exact match required | Brightness ±5% max | | Brand Accent | #XXXXXX | R,G,B | [Locations] | Exact match required | None | | Background | #XXXXXX | R,G,B | [Locations] | Hue consistent | Brightness ±15% | | Text/Dark | #XXXXXX | R,G,B | [Locations] | High contrast (4.5:1 min) | None |

Lighting Temperature Map:

| Space Type | Color Temperature | Kelvin | Hex Approximation | | ----------------- | ----------------- | ---------- | ----------------- | | Exterior Daylight | Neutral/Cool | 5500K | #FFFFFA | | Interior Warm | Warm White | 3000-4000K | #FFF4E6 | | Interior Neutral | Neutral White | 4000-5000K | #FFFEF0 | | Golden Hour | Warm Golden | 3000-3500K | #FFE4B5 |

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PHASE 3: AI VIDEO TOOL SPECIFICATIONS

Tool Selection Matrix

| Tool | Best For | Max Duration | Motion Control | Cost | | ---------------------- | ------------------------------- | ------------ | -------------- | ----------------- | | Runway Gen-3 Alpha | Photorealistic, precise camera | 10s | Excellent | High ($12+/s) | | Pika Labs | Fast turnaround, decent quality | 4s | Good | Medium ($1/s) | | Stable Video Diffusion | Open source, batch processing | Flexible | Moderate | Free (compute) | | Leonardo Motion | Illustrated/stylized | 4s | Low | Low ($0.30/frame) |

Runway Gen-3 Prompt Format

Sequence [N]: [Title]

Camera Motion: [Detailed movement description]
Starting Frame: [Upload image_start_N.jpg]
Ending Frame: [Upload image_end_N.jpg]
Duration: [X] seconds
Style: Photorealistic, cinematic, [vertical-specific style]
Avoid: text, watermarks, people, morphing, warping, sudden jumps

Advanced Settings:
- Motion Consistency: Maximum
- Temporal Coherence: High
- Camera Motion: [Dolly / Crane / Orbit / Pan / Tilt]
- Motion Strength: [5-7 for architectural]

Pika Labs Prompt Format

[Comprehensive scene description]
Starting frame: [Detailed start composition, camera position, lighting]
Ending frame: [Detailed end composition, camera position, lighting]
Camera motion: [Movement type] [direction and path]
Style: photorealistic architectural photography
-neg: text, watermarks, logos, people, morphing

Stable Video Diffusion Config

model: stabilityai/stable-video-diffusion-img2vid-xt
inputs:
  image: sequence_N_start.jpg
  prompt: [Detailed scene description]
  negative_prompt: text, watermarks, morphing, distortion
parameters:
  num_frames: [75-180 based on duration]
  fps: 30
  motion_bucket_id: [75-100 for architectural]
  noise_aug_strength: 0.02
output:
  format: "frames"
  naming: "%04d.jpg"

Universal Export Settings

• Canvas Animation: JPEG sequence, 85-90% quality, 4-digit zero-padded
• HTML5 Video: MP4 H.264, 5-8 Mbps (1080p), WebM VP9 fallback
• Resolution: 1920x1080 minimum, 3840x2160 preferred
• Frame Rate: 30fps web standard, 60fps premium

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PHASE 4: TECHNICAL IMPLEMENTATION BLUEPRINT

Canvas Sequence Manager Component

// components/animations/SequenceManager.tsx
import { useEffect, useState, useRef, useCallback } from 'react';

interface Sequence {
  id: string;
  path: string;
  frameCount: number;
}

export default function SequenceManager({ sequences, containerHeight }) {
  const canvasRef = useRef<HTMLCanvasElement>(null);
  const containerRef = useRef<HTMLDivElement>(null);
  const [allFrames, setAllFrames] = useState(new Map());
  const [loading, setLoading] = useState(true);
  const [progress, setProgress] = useState(0);

  const totalFrames = sequences.reduce((sum, seq) => sum + seq.frameCount, 0);

  // Preload all sequences
  useEffect(() => {
    const loadAllSequences = async () => {
      const frameMap = new Map();
      let loadedTotal = 0;

      for (const sequence of sequences) {
        const frames = [];
        for (let i = 1; i <= sequence.frameCount; i++) {
          const img = new Image();
          img.src = `${sequence.path}/${String(i).padStart(4, '0')}.jpg`;
          await img.decode();
          frames.push(img);
          loadedTotal++;
          setProgress(Math.round((loadedTotal / totalFrames) * 100));
        }
        frameMap.set(sequence.id, frames);
      }
      setAllFrames(frameMap);
      setLoading(false);
    };
    loadAllSequences();
  }, [sequences, totalFrames]);

  // Scroll-driven frame rendering
  const renderCurrentFrame = useCallback((scrollProgress) => {
    const canvas = canvasRef.current;
    if (!canvas || allFrames.size === 0) return;
    const context = canvas.getContext('2d');
    if (!context) return;

    const dpr = window.devicePixelRatio || 1;
    const rect = canvas.getBoundingClientRect();
    canvas.width = rect.width * dpr;
    canvas.height = rect.height * dpr;
    context.scale(dpr, dpr);

    const currentFrame = Math.floor(scrollProgress * totalFrames);
    let frameCount = 0;
    for (const sequence of sequences) {
      const sequenceStart = frameCount;
      if (currentFrame >= sequenceStart && currentFrame < sequenceStart + sequence.frameCount) {
        const sequenceFrames = allFrames.get(sequence.id);
        if (sequenceFrames) {
          const frame = sequenceFrames[currentFrame - sequenceStart];
          if (frame?.complete) {
            context.clearRect(0, 0, canvas.width, canvas.height);
            context.drawImage(frame, 0, 0, rect.width, rect.height);
          }
        }
        break;
      }
      frameCount += sequence.frameCount;
    }
  }, [allFrames, sequences, totalFrames]);

  useEffect(() => {
    if (loading) return;
    const handleScroll = () => {
      const container = containerRef.current;
      if (!container) return;
      const rect = container.getBoundingClientRect();
      const scrollProgress = Math.max(0, Math.min(1, -rect.top / (rect.height - window.innerHeight)));
      renderCurrentFrame(scrollProgress);
    };
    window.addEventListener('scroll', handleScroll);
    handleScroll();
    return () => window.removeEventListener('scroll', handleScroll);
  }, [loading, renderCurrentFrame]);

  if (loading) {
    return (
      <div className="loading-container">
        <div>Loading Sequences... {progress}%</div>
        <div className="progress-bar" style={{ width: `${progress}%` }} />
      </div>
    );
  }

  return (
    <div ref={containerRef} style={{ height: containerHeight, position: 'relative' }}>
      <div style={{ position: 'sticky', top: 0, height: '100vh' }}>
        <canvas ref={canvasRef} style={{ width: '100%', height: '100%', objectFit: 'cover' }} />
      </div>
    </div>
  );
}

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PHASE 5: PRE-PRODUCTION CHECKLIST

Sequence Design

• [ ] All sequences have START frames fully specified
• [ ] All sequences have END frames fully specified
• [ ] Frame-by-frame motion breakdown completed
• [ ] START[N+1] matches END[N] for all adjacent sequences
• [ ] Camera positions physically achievable
• [ ] Total duration appropriate for web (15-25s recommended)

Color Consistency

• [ ] Color consistency matrix generated with hex codes
• [ ] Brand colors used consistently across all sequences
• [ ] Lighting temperature mapped for each space
• [ ] Contrast ratios verified for text overlays (4.5:1 min)

Frame & Video Generation

• [ ] START/END frame images generated and verified
• [ ] AI tool prompts prepared (tool-specific format)
• [ ] Color picker verification completed
• [ ] JPEG sequences exported (0001.jpg format, no gaps)

Technical Implementation

• [ ] Canvas component built with scroll-driven rendering
• [ ] DPR-aware sizing (Retina display support)
• [ ] Performance tested (60fps maintained)
• [ ] Mobile frame counts reduced (60-90 instead of 120-180)
• [ ] Loading states designed and implemented

Deployment

• [ ] Cross-browser tested (Chrome, Safari, Firefox, Edge)
• [ ] Core Web Vitals checked (LCP<2.5s, CLS<0.1, INP<200ms)
• [ ] Production deployment completed
• [ ] Analytics configured

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Vertical-Specific Examples

Luxury Hotel

• Flow: Texture → Exterior → Entrance → Suite → View
• Palette: #F5F5F5 (warm white), #C9A977 (gold), #2C2C2C (charcoal)
• Tempo: 1.2-1.5s (slow, elegant)
• Durations: 5-6s per sequence, 150-180 frames each

Business Hotel

• Flow: Glass Detail → Building → Reception → Room → Amenities
• Palette: #1E88E5 (blue), #00ACC1 (cyan), #F5F5F5 (gray), #212121 (dark)
• Tempo: 0.6-0.8s (efficient)
• Durations: 4-5s per sequence, 120-150 frames each

Fine Dining Restaurant

• Flow: Ingredients → Facade → Dining Room → Kitchen → Plated Dish
• Palette: #1A1A1A (black), #FFD700 (gold), #FFFFFF (white)
• Tempo: 0.8-1s (sophisticated)
• Durations: 3-4s per sequence, 90-120 frames each

Real Estate

• Flow: Aerial → Exterior → Entry → Living Spaces → View
• Palette: #FAF9F6 (warm white), #708090 (blue-gray), wood tones
• Tempo: 0.6-0.8s (comfortable)
• Durations: 4-5s per sequence, 120-150 frames each

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Anti-Patterns to Avoid

❌ Disconnected Shots

Wrong: Hotel exterior → Random room → Pool → Restaurant (no continuity) Right: Exterior → Entrance → Lobby → Room (logical journey)

❌ Vague Motion

Wrong: "Camera moves smoothly from outside to inside" Right: "Camera dollies forward from 8m to 3m, subject grows from 20% to 70% of frame over frames 1-90"

❌ Color Inconsistency

Wrong: Blue #1E88E5 → #2196F3 → #1976D2 across sequences Right: Brand Blue #1E88E5 exactly in all sequences

❌ Impossible Camera Moves

Wrong: Ground level → suddenly aerial → back inside Right: Ground → eye level crane up → logical entrance

❌ Lighting Jumps

Wrong: Bright exterior → suddenly dark interior Right: Gradual dimming over frames 120-150 as entering

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Client Pitch Template

ROI Calculation

Current: OTA bookings at 20-30% commission
Monthly OTA fees: ₹[X] × [Y bookings] × 25% = ₹[Z]
Annual savings with website: ₹[Z] × 12 = ₹[Total]
Website Investment: ₹[Cost]
Payback Period: ₹[Cost] / ₹[Z per month] = [N] months

Pricing Tiers

• Basic (₹35-40K): 1-2 sequences, single page, WhatsApp booking
• Standard (₹50-60K): 3-4 sequences, multi-page, booking form, 6mo support
• Premium (₹75-100K): 5+ sequences, CMS, payments, 1yr maintenance

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Remember: Frame-perfect continuity is NON-NEGOTIABLE. Every sequence is a link in a cinematic chain — break one link and the entire experience falls apart.