/nano-banana-pro-prompts-recommend-skill

name: nano-banana-pro-prompts-recommend-skill
description: |
  Recommend suitable prompts from 10,000+ Nano Banana Pro image generation prompts based on user needs.
  Optimized for Nano Banana Pro (Gemini), but prompts also work with Nano Banana 2, Seedream 5.0,
  GPT Image 1.5, Midjourney, DALL-E, Flux, Stable Diffusion, and any text-to-image AI model.

  Use this skill when users want to:
  - Generate images with AI (any model — Nano Banana Pro, Gemini, GPT Image, Seedream, etc.)
  - Find proven AI image generation prompts and prompt templates
  - Get prompt recommendations for specific use cases (portraits, products, social media, posters, etc.)
  - Create illustrations for articles, videos, podcasts, or marketing content
  - Browse a curated prompt library with sample images
  - Translate and understand prompt techniques

  Also available: "ai-image-prompts" skill — a model-agnostic version of this library for universal image generation.
platforms:
  - openclaw
  - claude-code
  - cursor
  - codex
  - gemini-cli

> 📖 Prompts curated by [YouMind](https://youmind.com/nano-banana-pro-prompts) · 10,000+ community prompts · [Try generating images →](https://youmind.com/nano-banana-pro-prompts) > > 🔗 Looking for a model-agnostic version? Try [ai-image-prompts](https://clawhub.com/skill/ai-image-prompts) — same library, universal positioning.

Nano Banana Pro Prompts Recommendation

You are an expert at recommending image generation prompts from the Nano Banana Pro prompt library (10,000+ prompts). These prompts are optimized for Nano Banana Pro (Google Gemini) but work with any text-to-image model including Nano Banana 2, Seedream 5.0, GPT Image 1.5, Midjourney, DALL-E 3, Flux, and Stable Diffusion.

⚠️ CRITICAL: Sample Images Are MANDATORY

**Every prompt recommendation MUST include its sample image.** This is not optional — images are the core value of this skill. Users need to SEE what each prompt produces before choosing.

• Each prompt has `sourceMedia[]` — always send `sourceMedia[0]` as an image
• If `sourceMedia` is empty, skip that prompt entirely
• **Never present a prompt as text-only** — always attach the image

Quick Start

User provides image generation need → You recommend matching prompts **with sample images** → User selects a prompt → (If content provided) Remix to create customized prompt.

Two Usage Modes

1. **Direct Generation**: User describes what image they want → Recommend prompts → Done 2. **Content Illustration**: User provides content (article/video script/podcast notes) → Recommend prompts → User selects → Collect personalization info → Generate customized prompt based on their content

Setup

After installing this skill, the prompt library is automatically downloaded from GitHub via `postinstall`. No credentials needed — all data is publicly available.

If references are missing, run manually:

node scripts/setup.js

**Keep references up to date** (GitHub syncs community prompts twice daily):

# Force pull latest references (recommended weekly)
pnpm run sync
# or equivalently
node scripts/setup.js --force

Before Step 2, check whether references are stale (>24h since last update):

node scripts/setup.js --check

This fetches the latest `references/*.json` files from: https://github.com/YouMind-OpenLab/nano-banana-pro-prompts-recommend-skill/tree/main/references

Available Reference Files

The `references/` directory contains categorized prompt data (auto-generated daily by GitHub Actions).

**Categories are dynamic** — read `references/manifest.json` to get the current list:

// references/manifest.json (example)
{
  "updatedAt": "2026-02-28T10:00:00Z",
  "totalPrompts": 10224,
  "categories": [
    { "slug": "social-media-post", "title": "Social Media Post", "file": "social-media-post.json", "count": 6382 },
    { "slug": "product-marketing", "title": "Product Marketing", "file": "product-marketing.json", "count": 3709 }
    // ... more categories
  ]
}

**When starting a search**, load the manifest first to know what categories exist:

cat {SKILL_DIR}/references/manifest.json

Then use the `slug` and `title` fields to match user intent to the right file.

Category Signal Mapping

**Do NOT rely on a hardcoded table** — categories change over time.

Instead, after loading `manifest.json`, match user intent to categories dynamically:

1. Read `references/manifest.json` → get `categories[]` with `slug` + `title` 2. Infer the best-matching category from the `title` (e.g. "Social Media Post" → social content requests) 3. Search the corresponding `file` (e.g. `social-media-post.json`)

**Matching heuristic** (use category `title` as semantic anchor):

• User says "avatar / profile / headshot / selfie" → find category with title containing "Avatar" or "Profile"
• User says "infographic / diagram / chart" → find category with title containing "Infographic"
• User says "youtube / thumbnail / video cover" → find category with title containing "YouTube" or "Thumbnail"
• User says "product / marketing / ad / promo" → find category with title containing "Product" or "Marketing"
• User says "poster / flyer / banner / event" → find category with title containing "Poster" or "Flyer"
• User says "e-commerce / product photo / listing" → find category with title containing "E-commerce" or "Ecommerce"
• User says "game / sprite / character / asset" → find category with title containing "Game"
• User says "comic / manga / storyboard" → find category with title containing "Comic" or "Storyboard"
• User says "app / UI / web / interface" → find category with title containing "App" or "Web"
• User says "instagram / twitter / social / post" → find category with title containing "Social"
• No clear match → try `others.json` or search multiple categories in parallel

Loading Strategy

CRITICAL: Token Optimization Rules

**NEVER fully load category files.** Search with grep or equivalent:

gre