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Landing Page Doctor

A Claude Code skill that diagnoses Landing Page first-screen (above the fold) conversion problems and provides actionable rewrite suggestions.

Give it any URL, get a structured 10-point diagnostic report with scores and specific improvements.

What It Does

  1. Captures desktop + mobile screenshots and extracts page data (headlines, CTAs, trust signals, etc.)
  2. Classifies page type (Indie SaaS / B2B / E-commerce / Content) and brand maturity
  3. Diagnoses against 10 objective checkpoints across 4 categories
  4. Interprets scores in context — the same score means different things for a known brand vs a new indie project
  5. Outputs a structured report with specific rewrite suggestions

The 10 Checkpoints

Category # Checkpoint Max
A. Value Communication 1 Headline Value Proposition 10
2 5-Second Clarity 10
3 First-Screen Information Density 10
B. Action Guidance 4 CTA Visibility 10
5 CTA Copy Quality 10
6 Commitment Reduction 10
C. Trust Building 7 Trust Anchor Presence 10
8 Trust Authenticity 10
D. Technical Performance 9 Mobile Responsiveness 10
10 Copy Readability 10
Total 100

Each checkpoint uses objective feature detection (Y/N checks) rather than subjective judgment, ensuring consistent results across different AI models.

Install

npx skills add JackChen-me/landing-page-doctor

Or manually:

git clone https://github.com/JackChen-me/landing-page-doctor.git ~/.claude/skills/landing-page-doctor

Prerequisites

The capture script requires Playwright. It will auto-install on first run, or you can install manually:

pip install playwright
playwright install chromium

Usage

In Claude Code, run:

/landing-page-doctor https://your-landing-page.com

Or simply paste a URL and ask Claude to diagnose it:

Help me analyze this landing page: https://example.com

Example Output

See examples/linear-app.md for a full diagnostic report of linear.app.

Report structure:

# Landing Page 首屏诊断报告

URL: https://example.com
页面类型: A. Indie tool / SaaS
品牌成熟度: 🔴 Unknown
总分: 42/100
等级: D

## 逐项诊断
### 1. 标题价值主张 [4/10]
当前: "AI-Powered Project Management Platform"
问题: 标题在说"我是什么",没有告诉用户"你能得到什么"
建议改为:
- 方案A: "Stop drowning in tasks — manage your team's work in 2 minutes"
- 方案B: "Your 3-person team can finally track everything without Excel"

[...10 items with scores and rewrite suggestions...]

## 诊断解读
### 分数背后的真实含义
### 如果你是独立开发者
### 最值得学习的地方

## Top 3 优先行动
1. ...
2. ...
3. ...

Key Design Decisions

Why brand maturity matters: A 0/10 trust score means completely different things for Linear (a well-known brand where visitors arrive via word-of-mouth) vs an indie developer's new tool (where cold traffic has zero context). The report always includes a "what this means for indie developers" section.

Why feature detection over subjective judgment: Instead of asking the AI "is this headline good?", we break it down into 5 checkable features (contains second person? has specific numbers? includes action verb?). This makes scoring consistent regardless of which AI model runs the skill.

Why capture before analyze: The Python script extracts structured data (CTA button colors, sizes, positions, nav item count, trust signal patterns) so the AI works with facts, not just visual impressions.

File Structure

landing-page-doctor/
├── SKILL.md                    # Main skill definition + workflow + report template
├── scripts/
│   └── capture.py              # Playwright-based page capture + data extraction
├── references/
│   └── diagnosis-rules.md      # 10 checkpoints with scoring criteria + interpretation matrix
├── examples/
│   └── linear-app.md           # Example report
├── README.md
├── README.zh-CN.md
└── LICENSE

Methodology

Based on conversion optimization principles from:

  • Nielsen Norman Group research on above-the-fold attention (57% of viewing time)
  • Google PageSpeed data on load time impact (53% bounce at 3s+)
  • Unbounce research on single vs multiple CTAs
  • Practical experience reviewing indie developer landing pages

License

MIT

About

A Claude Code skill that diagnoses Landing Page first-screen conversion problems with a 10-point scoring framework and actionable rewrite suggestions.

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