influencer-analyzer

影响者分析器

了解哪些内容有效，找到差异化切入点。 此技能跟踪心脏病学内容创作者，并为你的内容识别机会。

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功能

步骤	操作	输出
1	通过 Perplexity/DuckDuckGo 查找影响者内容	URL、文章、视频
2	抓取并提取内容模式	主题、形式、频率
3	分析互动信号	受众感兴趣的内容
4	生成差距分析	你可以实现差异化的领域

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触发条件

在你说出以下内容时使用此技能：

• “[Topol/Attia/竞争对手] 最近在发布什么内容？”
• “找出心脏病学内容中的空白”
• “分析我的竞争对手”
• “我应该涵盖哪些主题？”
• “跟踪心脏病学领域的影响者”

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目标影响者

国际（英语）

名称	平台	关注领域	跟踪原因
@EricTopol	Twitter, Substack	临床试验、数字健康	声音风格模型、Ground Truths 风格
Peter Attia	播客、YouTube	长寿、心血管疾病预防	深度探讨风格
York Cardiology	YouTube	患者教育	清晰易懂的讲解
Dr. Sanjay Gupta (York)	YouTube	ECG、临床病例	教育内容形式

印度（印地语/英语）

名称	平台	关注领域	跟踪原因
Dr Navin Agrawal	YouTube	患者教育	竞争情况
Cardiac Second Opinion	YouTube	第二诊疗意见	竞争情况
Dr. Devi Shetty	视频	平价医疗	权威性

反面模式（不要这样做）

名称	平台	跟踪原因
SAAOL	YouTube	需要纠正的错误信息
Dr Biswaroop Roy Chowdhury	YouTube	需要揭穿的危险说法

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用法

在 Claude Code 中（推荐）

"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 模式

# 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"

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输出格式

1. 影响者档案

## 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. 差距分析报告

## 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. 竞争对比表

| 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 |

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与你的系统集成

输出至：

• research-engine/data/target_channels.json - 频道跟踪
• youtube-script-master - 主题选择
• viral-content-predictor - 内容评分
• content-repurposer - 多平台改编

数据流：

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

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Claude 应如何使用此技能

当用户询问竞争对手或内容策略时：

步骤 1：确定目标

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

步骤 2：使用 Perplexity 进行研究

使用 Perplexity MCP 或网页搜索查找：

• 最近发布的内容／文章
• 互动指标
• 主题分布

步骤 3：分析模式

• 哪些主题反复出现？
• 哪些内容获得的互动最多？
• 发布频率如何？

步骤 4：生成差距分析

与用户现有内容进行比较：

• 哪些内容已涵盖，哪些尚未涵盖？
• 用户可以在哪些方面实现差异化？
• 有什么独特的切入角度？

步骤 5：提供可执行的建议

• 可涵盖的具体主题
• 可尝试的形式
• 发布时机建议

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示例工作流

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

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依赖项

# 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

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所需 API 密钥

密钥	用途	状态
PERPLEXITY_API_KEY	网页搜索	已有（通过 OpenRouter）
ANTHROPIC_API_KEY	分析	已有

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预配置的影响者档案

位于 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"
    }
  ]
}

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注意事项

• 隐私：仅分析公开内容
• 频率：每周运行一次以跟踪趋势
• 重点：进行差距分析，而非照搬
• 目标：找到你自己的独特切入角度，而不是模仿他人

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此技能可帮助你了解竞争格局，从而实现差异化，而非重复他人的内容。