Kalodata Storyboard Extract

Kalodata Storyboard Extract

Extract AI-generated storyboards from viral videos to understand what made them successful and generate content ideas for replication.

Overview

Enables extraction of AI-generated storyboards from viral TikTok Shop videos, including scene breakdowns, visual descriptions, camera work analysis, and auto-generating content ideas for replication.

When to Use

Trigger phrases:

• "kalodata storyboard extract"

• "Analyze Viral Videos: Understand what made a video successful"

• "Extract Scene Breakdowns: Get detailed scene-by-scene analysis"

• "Camera Work Analysis: Understand camera techniques used"

• Analyze Viral Videos: Understand what made a video successful

• Extract Scene Breakdowns: Get detailed scene-by-scene analysis

• Camera Work Analysis: Understand camera techniques used

• Content Ideation: Auto-generate 5 content ideas from any video

• Competitor Research: Study winning video structures for your category

• Creative Direction: Get visual descriptions for product showcases

The Process

1. Identify target video – Get video ID from Kalodata product research or competitor analysis
2. Extract storyboard – Run extraction with video ID and date range
3. Analyze results – Review key success factors, camera work, scene breakdown
4. Generate content ideas – Use auto-generated angles for your content
5. Replicate or adapt – Apply insights to your own video strategy

When NOT to Use

• Task is outside your authorization scope
• You need to implement controls (use implementing-* skills)
• Task is about analysis, not action (use analyzing-* skills)
• You don't have access to target systems
• Task requires compliance expertise (consult professionals)
• Task is about defense, not offense (use defensive skills)

Red Flags

• Trying to extract storyboards without API credentials (need valid Kalodata cookies)
• Using video IDs from unsupported platforms (this skill is TikTok Shop specific)
• Ignoring date ranges can lead to outdated or irrelevant data
• Expecting real-time extraction results (this runs asynchronously)

Verification

• Storyboard extraction completes without errors
• Key success factors are actionable and specific
• Camera work analysis identifies concrete techniques used
• Scene breakdown includes accurate timestamps and visual descriptions
• Generated content ideas are diverse and relevant to the video theme

Do Not Use This Skill When

• Need real-time video metrics (use Video Analysis skill)
• Need product data (use Product Research skill)
• Need creator/influencer analytics (use Kalodata creator endpoints)

Core Features

• Core operation execution with comprehensive error handling
• Input validation and output quality assurance
• Integration with existing workflows and toolchains
• Detailed logging for debugging and audit trails

1. Storyboard Extraction

Trigger AI analysis of any video and get complete scene breakdown:

const result = await extractor.extractStoryboard({
  videoId: '7600772739623914770',
  dateRange: { start: '2026-01-20', end: '2026-02-18' },
});

Returns:

• keyToSuccess: What made the video viral
• cameraWork: Camera techniques used
• scenes: Detailed scene breakdown
• contentIdeas: 5 auto-generated content angles

2. Key Success Factors

Extract what made the video viral:

// Returns array of success factors
result.keyToSuccess.forEach(factor => {
  console.log(factor);
});

// Example output:
// [
//   "Menampilkan setelan pakaian modis dan tertutup (modest fashion)...",
//   "Model secara aktif berpose dan berputar...",
//   "Branding 'FashionByDea' terlihat jelas...",
//   ...
// ]

3. Camera Work Analysis

Get camera techniques used in the video:

console.log(result.cameraWork);
// "Video ini menggunakan teknik pengambilan gambar statis..."

4. Scene Breakdown

Detailed per-scene analysis:

result.scenes.forEach(scene => {
  console.log(`${scene.name}: ${scene.shotScale}`);
  console.log(`  ${scene.visualDescription}`);
});

// Example output:
// Product Information: Full Shot
//   Seorang wanita berhijab mengenakan setelan tunik...
// Product Selling Points: Full Shot
//   Wanita itu berputar perlahan untuk menunjukkan...

5. Auto-Generated Content Ideas

Automatically generate 5 content angles for replication:

result.contentIdeas.forEach((idea, i) => {
  console.log(`${i + 1}. ${idea.title}`);
  console.log(`   Angle: ${idea.angle}`);
  console.log(`   ${idea.description}`);
});

API Reference

StoryboardExtractor Class

class StoryboardExtractor {
  constructor(options: ClientOptions);
  
  // Main extraction method
  extractStoryboard(options: ExtractStoryboardOptions): Promise<StoryboardResult>;
  
  // Analysis helpers
  analyzeStoryboard(storyboard: GetVideoScriptResponse): StoryboardAnalysis;
  generateContentIdeas(storyboard: GetVideoScriptResponse): ContentIdea[];
  
  // Credentials
  updateCredentials(session: string, cfClearance: string): void;
  getConfig(): Readonly<KalodataConfig>;
}

ExtractStoryboardOptions

interface ExtractStoryboardOptions {
  videoId: string;
  dateRange: { start: string; end: string };
  translate?: boolean;
  maxAttempts?: number;
  pollIntervalMs?: number;
}

StoryboardResult

interface StoryboardResult {
  videoId: string;
  language: string;
  gender: string;
  keyToSuccess: string[];
  cameraWork: string;
  scenes: Scene[];
  contentIdeas: ContentIdea[];
  metadata: {
    extractedAt: string;
    totalDuration: number;
    sceneCount: number;
  };
}

Scene

interface Scene {
  name: string;
  startTime: number;
  endTime: number;
  duration: number;
  shotScale: string;
  visualDescription: string;
}

ContentIdea

interface ContentIdea {
  title: string;
  description: string;
  angle: 'demonstration' | 'transformation' | 'lifestyle' | 'problem-solution' | 'emotional';
  keyScene: string;
  hook: string;
}

Content Idea Angles

Example Workflow

1. Receive input and validate format
2. Route to appropriate handler based on input type
3. Execute core operation with monitoring
4. Transform output to expected format
5. Return results or trigger follow-up actions

Full Analysis Example

import { StoryboardExtractor } from '../../src/kalodata/storyboard-extract.js';

async function analyzeViralVideo(videoId: string) {
  const extractor = new StoryboardExtractor({
    session: process.env.KALODATA_SESSION!,
    cfClearance: process.env.KALODATA_CF_CLEARANCE!,
  });

  const result = await extractor.extractStoryboard({
    videoId,
    dateRange: { start: '2026-01-20', end: '2026-02-18' },
  });

  // Print key success factors
  console.log('=== KEY SUCCESS FACTORS ===');
  result.keyToSuccess.forEach((factor, i) => {
    console.log(`${i + 1}. ${factor}\n`);
  });

  // Print camera work analysis
  console.log('=== CAMERA WORK ===');
  console.log(result.cameraWork + '\n');

  // Print scene breakdown
  console.log('=== SCENE BREAKDOWN ===');
  result.scenes.forEach(scene => {
    console.log(`[${scene.startTime}s - ${scene.endTime}s] ${scene.shotScale}: ${scene.name}`);
    console.log(`  ${scene.visualDescription}\n`);
  });

  // Print content ideas
  console.log('=== CONTENT IDEAS ===');
  result.contentIdeas.forEach((idea, i) => {
    console.log(`${i + 1}. ${idea.title} (${idea.angle})`);
    console.log(`   Hook: ${idea.hook}`);
    console.log(`   ${idea.description}\n`);
  });

  return result;
}

// Usage
analyzeViralVideo('7600772739623914770');

Integration with Product Research

import { ProductResearcher } from '../../src/kalodata/product-research.js';
import { StoryboardExtractor } from '../../src/kalodata/storyboard-extract.js';

async function researchTopProductVideos() {
  const productResearcher = new ProductResearcher({
    session: process.env.KALODATA_SESSION!,
    cfClearance: process.env.KALODATA_CF_CLEARANCE!,
  });

  const storyboardExtractor = new StoryboardExtractor({
    session: process.env.KALODATA_SESSION!,
    cfClearance: process.env.KALODATA_CF_CLEARANCE!,
  });

  // Find top products
  const products = await productResearcher.queryByGoal({
    goal: 'find stable winners',
    categoryId: '600138989',
    dateRange: { start: '2026-01-20', end: '2026-02-18' },
  });

  // Get videos for top product
  const topProduct = products[0];
  console.log(`Analyzing: ${topProduct.title}`);

  // Extract storyboard from top video
  const storyboard = await storyboardExtractor.extractStoryboard({
    videoId: topProduct.videos?.[0]?.id || '',
    dateRange: { start: '2026-01-20', end: '2026-02-18' },
  });

  return storyboard;
}

Error Handling

try {
  const result = await extractor.extractStoryboard(options);
} catch (error) {
  if (error instanceof AuthenticationError) {
    console.log('Invalid credentials - update session/cf_clearance');
  } else if (error instanceof TaskNotCompleteError) {
    console.log('Video analysis taking too long - try increasing maxAttempts');
  } else if (error.message.includes('timed out')) {
    console.log('Request timed out - video may not exist');
  }
}

Environment Variables

KALODATA_SESSION=your_session_cookie
KALODATA_CF_CFLEARANCE=your_cf_clearance_token

Best Practices

1. Date Range: Use 30-day range for accurate analysis
2. Timeout: Increase maxAttempts for complex videos (default: 30)
3. Polling Interval: Decrease for faster videos, increase for slower (default: 2000ms)
4. Content Ideas: Use as starting points - customize for your product
5. Scene Timing: Use startTime and endTime to replicate exact structure

Anti-Rationalization Table

Related Skills

• Kalodata Product Research - Product intelligence
• Kalodata Video Analysis - Video metrics
• Kalodata API Client - Core client

Process

1. Analyze the task requirements
2. Apply domain expertise
3. Verify output quality