influencer-analyzer

Q: How do I install influencer-analyzer?

Run npx skills add https://github.com/drshailesh88/integrated_content_os --skill influencer-analyzer in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/influencer-analyzer/ (personal) or .claude/skills/influencer-analyzer/ (project).

by drshailesh88Marketing & SEO

Track and analyze cardiology content creators (Topol, Attia, York Cardiology, Indian channels). Discovers content patterns, topics, engagement, and gap opportunities for your Hinglish content strategy.

Installs: 49
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Security: Not audited

Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/drshailesh88/integrated_content_os --skill influencer-analyzer

01
Install
Run the command in your project. The CLI asks which agents to install for.
02
Describe the task
Ask your agent for something this skill covers. It loads influencer-analyzer automatically when relevant.
03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

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:**
- [x] Hinglish explanations
- [x] Indian patient context
- [x] Cost-conscious alternatives
- [x] 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

3. Competitive Comparison Table

| Aspect | Eric Topol | Peter Attia | York Cardiology | You |
|--------|------------|-------------|-----------------|-----|
| Platform | Twitter/Substack | Podcast/YouTube | YouTube | YouTube |
| Language | English | English | English | Hinglish |
| Depth | Expert-level | Deep-dive | Patient-friendly | Expert→Patient |
| Frequency | Daily | Weekly | 2-3x/week | ? |
| Unique Angle | Trials/Digital | Longevity | ECG teaching | Indian context |

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.

FAQ

What does the influencer-analyzer skill do?

How do I install influencer-analyzer?

Run npx skills add https://github.com/drshailesh88/integrated_content_os --skill influencer-analyzer in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/influencer-analyzer/ (personal) or .claude/skills/influencer-analyzer/ (project).

Which AI agents can use influencer-analyzer?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is influencer-analyzer safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains influencer-analyzer?

It is published by drshailesh88 in drshailesh88/integrated_content_os. It has 49 recorded installs.