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Viral Content Predictor

  • 47 installs
  • 5 repo stars
  • Updated June 18, 2026
  • drshailesh88/integrated_content_os

Scores content ideas for viral potential and predicts views, engagement, and retention, then outputs a research-backed content blueprint.

About

Analyzes content ideas from PDF/DOCX files and predicts viral potential (views, engagement, retention) for a medical-education channel. A creator uses it to prioritize which video ideas to produce and how to structure them.

  • Scores medical-education content ideas 0-100 for viral potential and predicts view ranges
  • Runs trend and YouTube-comment research to surface knowledge gaps and content blueprints

Viral Content Predictor by the numbers

  • 47 all-time installs (skills.sh)
  • Ranked #576 of 853 Sales & Marketing skills by installs in the Skillselion catalog
  • Data as of Jul 29, 2026 (Skillselion catalog sync)
npx skills add https://github.com/drshailesh88/integrated_content_os --skill viral-content-predictor

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Installs47
repo stars5
Last updatedJune 18, 2026
Repositorydrshailesh88/integrated_content_os

What it does

Scores content ideas for viral potential and predicts views, engagement, and retention, then outputs a research-backed content blueprint.

Files

SKILL.mdMarkdownGitHub ↗

Viral Content Predictor for Medical Education

This skill analyzes healthcare/medical education content ideas and predicts their viral potential using multi-factor analysis, trend research, and YouTube audience insights.

Core Capabilities

1. Content Idea Analysis: Extract and score content ideas from uploaded documents 2. Viral Potential Prediction: Estimate views, engagement, and AVD based on multiple factors 3. Trend Research: Identify hot topics and emerging trends in medical education 4. Audience Intelligence: Analyze YouTube comments to understand knowledge gaps and concerns 5. Content Optimization: Provide subtopics, myths to address, and structural recommendations

Workflow

Phase 1: Content Extraction & Initial Scoring

When the user provides PDF/DOCX files with content ideas:

1. Extract all content ideas from the document 2. Initial categorization by topic, complexity, and format 3. Preliminary viral score (0-100) based on:

  • Topic relevance and timeliness
  • Emotional appeal (fear, hope, relief, empowerment)
  • Searchability and SEO potential
  • Educational value vs entertainment balance
  • Novelty factor

Phase 2: Deep Research & Validation

For top-scoring ideas (score >70) or user-selected ideas:

1. Search current trends: Use web_search to find:

  • Recent high-performing videos on the topic
  • News articles and medical publications
  • Reddit/forum discussions
  • Trending searches related to the topic

2. Competitive analysis:

  • Identify top-performing videos in the niche
  • Analyze view counts, engagement ratios, and video length
  • Note common patterns and differentiators

3. Knowledge gap identification:

  • What questions are people asking?
  • What misconceptions exist?
  • What information is missing from existing content?

Phase 3: Predictive Analytics

For each analyzed idea, calculate:

1. Predicted View Range: Based on:

  • Search volume data (estimated from trends)
  • Similar video performance benchmarks
  • Topic saturation level
  • Seasonal/temporal relevance
  • Channel authority factor (assumed moderate for interventional cardiology niche)

2. Engagement Prediction:

  • Estimated likes, shares, comments
  • Expected like-to-view ratio
  • Share potential score

3. AVD (Average View Duration) Optimization Score:

  • Topic retention potential (inherent interest)
  • Complexity level (optimal: moderate complexity for patient education)
  • Hook strength assessment
  • Pacing recommendations

Phase 4: Content Blueprint

For prioritized ideas, provide:

1. Video Structure Recommendation:

  • Optimal video length
  • Hook suggestions (first 10 seconds)
  • Chapter breakdown with timestamps
  • Pacing guidance for high retention

2. Subtopics to Include (in priority order):

  • Core information (must-have)
  • High-interest tangents (AVD boosters)
  • Myth-busting segments (engagement drivers)
  • Practical takeaways (satisfaction & shareability)

3. Psychological Triggers to Address:

  • Common fears related to the topic
  • Misconceptions to debunk
  • Hope/empowerment angles
  • Trust-building elements

4. SEO & Discoverability:

  • Title suggestions (tested patterns)
  • Thumbnail concepts
  • Keyword recommendations
  • Description template

Scoring Methodology

Viral Potential Score (0-100)

Topic Factors (40 points):

  • Search demand: 15 pts (estimated from trend data)
  • Emotional resonance: 10 pts (fear, hope, curiosity)
  • Timeliness: 10 pts (recent news, seasonal relevance)
  • Novelty: 5 pts (unique angle or new information)

Engagement Factors (30 points):

  • Shareability: 10 pts (will people send to family/friends?)
  • Comment-worthiness: 10 pts (controversial or discussion-inducing?)
  • Practical value: 10 pts (actionable information)

Retention Factors (30 points):

  • Hook potential: 10 pts (compelling opening)
  • Information density: 10 pts (value per minute)
  • Narrative flow: 10 pts (story or logical progression)

View Prediction Formula

Estimated Views = Base_Audience × Topic_Multiplier × Quality_Factor × Trend_Factor

Where:
- Base_Audience: 5,000-15,000 (typical for established medical education channel)
- Topic_Multiplier: 0.5-10.0 (based on search volume and competition)
- Quality_Factor: 0.8-1.5 (based on production quality, assumed 1.0)
- Trend_Factor: 0.5-3.0 (based on current trending status)

Range Output: 
- Minimum (conservative): Lower quartile estimate
- Expected (median): Most likely scenario
- Maximum (optimistic): Upper quartile with viral potential

Research Tools & Techniques

Web Search Strategies

When researching topics, use these search patterns:

1. Trend identification:

  • "[topic] latest research 2024"
  • "most common questions about [topic]"
  • "[topic] myths debunked"

2. Audience analysis:

  • "reddit [topic] patient experience"
  • "[topic] what to expect forum"
  • "[topic] success stories"

3. Competition analysis:

  • "[topic] youtube popular"
  • "how to explain [topic] to patients"
  • "[topic] doctor explains"

YouTube Comment Analysis Strategy

When the user provides a topic or video URL:

1. Search for top 5-10 videos on the topic 2. Analyze comment patterns for:

  • Most frequently asked questions
  • Common confusions or misconceptions
  • Emotional reactions (fear, gratitude, skepticism)
  • Requests for specific information
  • Demographic clues (age, situation)

3. Categorize insights into:

  • Knowledge gaps: What people don't understand
  • Fears: What worries them
  • Desires: What they hope to learn
  • Trust signals: What builds credibility

Output Format

Content Idea Report

For each analyzed idea, provide:

## [Content Idea Title]

### 🎯 Viral Potential Score: [X/100]

**Predicted Performance**:
- Views: [min - expected - max]
- Like Ratio: [X%]
- AVD: [X:XX - Y:YY minutes]
- Shareability: [Low/Medium/High]

### 📊 Analysis

**Strengths**:
- [Key strength 1]
- [Key strength 2]

**Opportunities**:
- [Improvement area 1]
- [Improvement area 2]

**Market Insights**:
- Current search trends: [summary]
- Competition level: [Low/Medium/High]
- Audience demand: [description]

### 🎬 Content Blueprint

**Optimal Length**: [X-Y minutes]

**Video Structure**:
1. Hook (0:00-0:10): [specific suggestion]
2. Problem Setup (0:10-1:00): [what to cover]
3. Core Education (1:00-[X]:00): [main content]
4. Myth-Busting ([X]:00-[Y]:00): [misconceptions to address]
5. Practical Takeaways ([Y]:00-end): [actionable advice]

**Essential Subtopics** (in order of priority):
1. [Subtopic 1] - [why it matters for AVD]
2. [Subtopic 2] - [why it matters for AVD]
3. [Subtopic 3] - [why it matters for AVD]

**Knowledge Gaps to Address**:
- [Gap 1] - [source: YouTube comments/Reddit/forums]
- [Gap 2] - [source]

**Myths & Misconceptions**:
- [Myth 1] - [prevalence & why it persists]
- [Myth 2] - [prevalence & why it persists]

**Emotional Hooks**:
- Fear to address: [specific patient fear]
- Hope to provide: [specific positive outcome]
- Empowerment angle: [how viewers take control]

**SEO Recommendations**:
- Primary keyword: [keyword]
- Title suggestions:
  1. [Title option 1]
  2. [Title option 2]
  3. [Title option 3]
- Thumbnail concept: [description]

### 🔥 Hot Take / Unique Angle

[One compelling angle that differentiates this from existing content]

Trend Report

When analyzing current trends:

## 🚀 Trending Topics in [Niche]

### High Priority (Create ASAP)
1. **[Topic]** - Viral Score: [X/100]
   - Why now: [reason for timeliness]
   - Quick summary: [one-liner]
   
### Medium Priority (Plan for Next Month)
[Similar format]

### Emerging Trends (Watch Closely)
[Similar format]

### Seasonal Opportunities
[Upcoming events/seasons that create content opportunities]

Best Practices

For Medical Education Content

1. Balance authority with accessibility: Use simple language but demonstrate expertise 2. Lead with empathy: Acknowledge fears and concerns first 3. Provide hope: Always include positive outcomes or management strategies 4. Be specific: Concrete examples outperform abstractions 5. Use visual analogies: Help patients visualize complex concepts 6. Address "why": Explain mechanisms, not just recommendations 7. Anticipate objections: Address common pushback or skepticism 8. Include patient stories: Anonymized cases increase retention 9. End with empowerment: Clear next steps or takeaways

AVD Optimization Tactics

1. Pattern interrupt every 60-90 seconds: Change visual, topic, or energy 2. Open loops: Tease information that comes later 3. Progress indicators: "Three things you need to know..." 4. Highlight surprising facts: "Most people don't know..." 5. Use conversational pacing: Speak as if to one person 6. Strategic repetition: Reinforce key points without being boring 7. Maintain momentum: Cut dead air and unnecessary transitions

Reference Files

  • references/medical-content-patterns.md: Analysis of high-performing medical YouTube content patterns
  • references/cardiology-keywords.md: SEO-optimized keywords for cardiology topics
  • references/avd-tactics.md: Advanced retention strategies specific to educational content

When to Use Multiple Research Iterations

For content ideas scoring 85+: 1. Run initial analysis 2. Conduct deep competitive research 3. Search for recent medical publications 4. Analyze comment sections of top 5 competing videos 5. Check Reddit/forums for patient perspectives 6. Synthesize into comprehensive blueprint

This ensures the highest-potential ideas get the deepest analysis.

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