nano-banana-pro-prompts-recommend-skill
AI skill for OpenClaw & Claude Code — recommend from 10000+ Nano Banana Pro (Gemini) image prompts. Smart search by use case, content remix, sample images.
Generate landing page content from PRD — hero section, features, A/B headline variants, CTA, and SEO meta tags. Use when user says "create landing page", "write landing copy", "hero section", "A/B headlines", or "landing content". Can scaffold actual pages for astro-static. Do NOT use for SEO auditing (use /seo-audit).
Follow the repository instructions for this skill and your agent. Review the files and dependencies before adding it to your workflow.
SkillHub CLI
skillhub install fortunto2/solo-landing-genInspect the source and compatibility requirements, then follow its installation steps.
Give your agent the source link and ask it to inspect instructions and dependencies before explaining the installation steps.
Generate landing page content from a project's PRD. Produces hero section, features, social proof, CTA, SEO meta tags, and A/B headline variants. If astro-static stack detected, can scaffold actual page files.
kb_search(query) — find related methodology (conversion, copywriting)project_info(name) — get project stack and detailsweb_search(query) — competitor landing analysisIf MCP tools are not available, fall back to Glob + Grep + Read.
Parse project from $ARGUMENTS.
Detect stack:
astro.config.* → astro-static (can scaffold page)next.config.* → Next.js (can scaffold route)Extract landing inputs from PRD/README:
Competitor landing analysis (optional, if MCP/WebSearch available):
Forced reasoning — conversion strategy: Before generating, write out:
Generate landing content:
These signals come from indexed source analysis and may lag behind changes. Check the current source files.
# /landing-gen
Generate landing page content from a project's PRD. Produces hero section, features, social proof, CTA, SEO meta tags, and A/B headline variants. If astro-static stack detected, can scaffold actual page files.
## MCP Tools (use if available)
- `kb_search(query)` — find related methodology (conversion, copywriting)
- `project_info(name)` — get project stack and details
- `web_search(query)` — competitor landing analysis
If MCP tools are not available, fall back to Glob + Grep + Read.
## Steps
1. **Parse project** from `$ARGUMENTS`.
- Read PRD, README, or research.md for product info.
- If empty: ask via AskUserQuestion.
2. **Detect stack:**
- Check for `astro.config.*` → astro-static (can scaffold page)
- Check for `next.config.*` → Next.js (can scaffold route)
- Otherwise: generate content-only markdown
3. **Extract landing inputs** from PRD/README:
- **Problem:** 1 sentence pain statement
- **Solution:** 1 sentence product description
- **ICP:** Target user persona
- **Features:** Top 3-4 differentiating features with descriptions
- **Competitors:** From research.md (if exists) — for positioning
- **Pricing:** If available
4. **Competitor landing analysis** (optional, if MCP/WebSearch available):
- Search for top 3 competitor landing pages
- Note: headline patterns, CTA language, social proof types
- Identify positioning gaps
5. **Forced reasoning — conversion strategy:**
Before generating, write out:
- **Primary conversion:** What's the ONE action? (sign up / download / buy)
- **Objections:** Top 3 reasons someone wouldn't convert
- **Trust signals:** What overcomes each objection?
- **Above the fold:** Problem + Solution + CTA — nothing else
6. **Generate landing content:**
### 6a. Hero Section
- **Headline:** Problem-focused, benefit-driven (8-12 words)
- **Subheadline:** How the product solves it (15-25 words)
- **CTA button:** Action verb + outcome ("Start Free Tria...AI skill for OpenClaw & Claude Code — recommend from 10000+ Nano Banana Pro (Gemini) image prompts. Smart search by use case, content remix, sample images.
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