draft-landing — Landing Page Information Architecture

SkillMedia

Use when asked to structure a landing page, design page layout for conversion, or plan landing page information architecture. Examples: "landing page structure for SaaS", "conversion-optimized layout"

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the draft-landing — Landing Page Information Architecture skill

What this skill tells your AI

The instructions your AI receives, as published by tonone-ai/tonone in skills/draft-landing/SKILL.md and read by ahel’s review.

Follow the output format defined in docs/output-kit.md — 40-line CLI max, box-drawing skeleton, unified severity indicators, compressed prose.

When to use

User needs a landing page structure, section order, or conversion-optimized layout. Product type is known or discoverable.

Workflow

  1. Identify product type from user request or project context
  2. Search landing page patterns:
    python3 -m draft_agent.uiux search --domain landing --query "{product_type}" --limit 3
    
  3. Search product reasoning for audience + conversion context:
    python3 -m draft_agent.uiux search --domain product --query "{product_type}" --limit 3
    
  4. Validate each section against the "so what?" test — every section must earn its place
  5. Output section order with CTA placement markers

Output format

┌─ Landing Page IA — {product_type} ──────────────────────────────────┐
│ #  │ Section            │ Purpose                    │ CTA?          │
├────┼────────────────────┼────────────────────────────┼───────────────┤
│  1 │ {section_name}     │ {purpose}                  │ Primary CTA   │
│  2 │ {section_name}     │ {purpose}                  │ —             │
│  3 │ {section_name}     │ {purpose}                  │ Secondary CTA │
│  … │ …                  │ …                          │ …             │
└────┴────────────────────┴────────────────────────────┴───────────────┘

Conversion strategy: {strategy}
CTA copy guidance:   {cta_guidance}

Anti-patterns

  • Never skip the "so what?" test per section — if a section can't answer it, cut it
  • Never add sections without a clear conversion purpose
  • Never place the primary CTA below the fold on the first screen
  • Never structure the page without knowing the primary audience and their job-to-be-done

Delivery

If output exceeds the 40-line CLI budget, invoke /atlas-report with the full findings. The HTML report is the output. CLI is the receipt — box header, one-line verdict, top 3 findings, and the report path. Never dump analysis to CLI.

Signals

GitHub stars
71
Forks
9
Last commit
Aug 2026
Advanced
Catalog kind
skill
Gateway key
draft-landing
Source
github.com/tonone-ai/tonone