Influencer Analyzer

Know what's working, find where to differentiate. This skill tracks cardiology content creators and identifies opportunities for your content.

WHAT IT DOES

Step Action Output

1 Find influencer content via Perplexity/DuckDuckGo URLs, articles, videos

2 Scrape and extract content patterns Topics, formats, frequency

3 Analyze engagement signals What resonates with audience

4 Generate gap analysis Where you can differentiate

TRIGGERS

Use this skill when you say:

• "What is [Topol/Attia/competitor] posting about?"

• "Find gaps in cardiology content"

• "Analyze my competition"

• "What topics should I cover?"

• "Track cardiology influencers"

TARGET INFLUENCERS

International (English)

Name Platform Focus Why Track

@EricTopol Twitter, Substack Trials, digital health Voice model, Ground Truths style

Peter Attia Podcast, YouTube Longevity, CVD prevention Deep-dive style

York Cardiology YouTube Patient education Clear explanations

Dr. Sanjay Gupta (York) YouTube ECG, clinical cases Educational format

Indian (Hindi/English)

Name Platform Focus Why Track

Dr Navin Agrawal YouTube Patient education Competition

Cardiac Second Opinion YouTube Second opinions Competition

Dr. Devi Shetty Videos Affordable care Authority

Anti-Patterns (What NOT to do)

Name Platform Why Track

SAAOL YouTube Misinformation to counter

Dr Biswaroop Roy Chowdhury YouTube Dangerous claims to debunk

USAGE

In Claude Code (Recommended)

"Analyze what Eric Topol is posting about this week"

"Find gaps between Topol's content and Indian cardiology YouTube"

"What cardiology topics are trending that I haven't covered?"

"Compare my content strategy with Peter Attia"

CLI Mode

Analyze single influencer

python scripts/analyze_influencer.py --name "Eric Topol" --platform twitter

Compare multiple influencers

python scripts/analyze_influencer.py --compare "Topol,Attia,York Cardiology"

Find content gaps

python scripts/analyze_influencer.py --gaps --domain "Cardiology"

Track specific topic

python scripts/analyze_influencer.py --topic "GLP-1" --influencers "Topol,Attia"

OUTPUT FORMATS

1. Influencer Profile

Eric Topol (@EricTopol)

Recent Focus (Last 30 days):

• Clinical trials: 45%
• Digital health/AI: 30%
• COVID updates: 15%
• Book promotion: 10%

Top Performing Topics:

1. REDUCE-IT controversy (high engagement)
2. Apple Watch AFib detection (viral)
3. AI in diagnosis (consistent interest)

Posting Patterns:

• Frequency: 5-10 tweets/day
• Best times: 6AM, 12PM, 6PM PST
• Thread usage: Weekly deep-dives

Style Notes:

• Links to primary sources (PubMed, NEJM)
• Quotes key statistics
• Engages with critics
• Retweets junior researchers

2. Gap Analysis Report

CONTENT GAP ANALYSIS

What Topol Covers That You Don't:

• Weekly trial breakdowns
• Digital health intersection
• International guideline comparisons

What You Cover That Topol Doesn't:

• Hinglish explanations
• Indian patient context
• Cost-conscious alternatives
• Cultural nuances (vegetarian diets, family dynamics)

OPPORTUNITY ZONES:

1. Translate English trials for Indian context

   • Topol covers REDUCE-IT → You explain what it means for Indian patients

2. Bridge the gap

   • International guidelines → Indian applicability

3. Underserved topics in English space

   • Rheumatic heart disease (rare topic in US)
   • Tropical cardiology
   • Resource-limited settings

4. Competitive Comparison Table

INTEGRATION WITH YOUR SYSTEM

Feeds Into:

• research-engine/data/target_channels.json

• Channel tracking

• youtube-script-master

• Topic selection

• viral-content-predictor

• Content scoring

• content-repurposer

• Multi-platform adaptation

Data Flow:

influencer-analyzer ↓ [Gap Analysis Report] ↓ research-engine (topic prioritization) ↓ youtube-script-master (script creation) ↓ YOUR CONTENT (unique angle)

HOW CLAUDE SHOULD USE THIS SKILL

When the user asks about competitors or content strategy:

Step 1: Identify Target

User: "What is Topol posting about?" → Target: Eric Topol → Platforms: Twitter, Substack

Step 2: Research with Perplexity

Use Perplexity MCP or web search to find:

• Recent posts/articles

• Engagement metrics

• Topic distribution

Step 3: Analyze Patterns

• What topics repeat?

• What gets most engagement?

• What's the posting frequency?

Step 4: Generate Gap Analysis

Compare with user's existing content:

• What's covered vs. uncovered?

• Where can user differentiate?

• What's the unique angle?

Step 5: Actionable Recommendations

• Specific topics to cover

• Formats to try

• Timing suggestions

SAMPLE WORKFLOW

User: "Find content gaps in cardiology YouTube"

Claude:

1. Uses Perplexity to search:

   • "Eric Topol recent tweets cardiology 2025"
   • "Peter Attia podcast topics 2025"
   • "York Cardiology recent videos"
   • "Indian cardiology YouTube channels"

2. Analyzes results:

   • Topic frequency
   • Engagement patterns
   • Content gaps

3. Cross-references with user's content:

   • What has user covered?
   • What's missing?
   • What's unique to user?

4. Outputs:

   • Gap analysis report
   • Priority topics list
   • Differentiation strategy

DEPENDENCIES

Already have

anthropic>=0.18.0 python-dotenv>=1.0.0 rich>=13.0.0

For web scraping (optional)

requests>=2.31.0 beautifulsoup4>=4.12.0

API KEYS NEEDED

Key Purpose Status

PERPLEXITY_API_KEY Web search Already have (via OpenRouter)

ANTHROPIC_API_KEY Analysis Already have

PRE-CONFIGURED INFLUENCER PROFILES

Located in data/influencers.json :

{ "influencers": [ { "name": "Eric Topol", "handle": "@EricTopol", "platforms": ["twitter", "substack"], "focus": ["clinical_trials", "digital_health", "AI_medicine"], "style": "expert_commentary", "track_for": "voice_model" }, { "name": "Peter Attia", "handle": "peterattiamd", "platforms": ["podcast", "youtube", "newsletter"], "focus": ["longevity", "metabolic_health", "CVD_prevention"], "style": "deep_dive", "track_for": "format_inspiration" }, { "name": "York Cardiology", "handle": "@YorkCardiology", "platforms": ["youtube"], "focus": ["ECG", "patient_education", "clinical_cases"], "style": "educational", "track_for": "competitor" }, { "name": "Dr Navin Agrawal", "handle": null, "platforms": ["youtube"], "focus": ["patient_education", "hindi"], "style": "simple_explanations", "track_for": "competitor" } ] }

NOTES

• Privacy: Only analyze public content

• Frequency: Run weekly for trend tracking

• Focus: Gap analysis, not copying

• Goal: Find YOUR unique angle, not imitate others

This skill helps you understand the competitive landscape so you can differentiate, not duplicate.