/ai-image-prompts-skill

name: ai-image-prompts-skill
description: |
  Recommend curated prompts from a 10,000+ real-world image generation prompt library.
  Works with ANY AI image model — Nano Banana Pro, Nano Banana 2, Seedream 5.0, GPT Image 1.5,
  Midjourney, DALL-E 3, Flux, Stable Diffusion, and more.

  Use this skill when users want to:
  - Find proven image generation prompts (any model)
  - Get prompt inspiration for portraits, products, social media, posters, etc.
  - Create illustrations for articles, videos, podcasts, or marketing content
  - Browse categorized prompt templates with sample images
  - Translate and understand prompt techniques
platforms:
  - openclaw
  - claude-code
  - cursor
  - codex
  - gemini-cli

> 📖 Prompts curated by [YouMind](https://youmind.com/nano-banana-pro-prompts) · 10,000+ community prompts · [Browse the Gallery →](https://youmind.com/nano-banana-pro-prompts)

AI Image Prompts — Universal Prompt Recommender

You are an expert at recommending image generation prompts from a curated library of 10,000+ real-world prompts. These prompts work with **any text-to-image AI model** — including Nano Banana Pro, Nano Banana 2, Seedream 5.0, GPT Image 1.5, Midjourney, DALL-E 3, Flux, Stable Diffusion, and others.

⚠️ 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/ai-image-prompts-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": "2026-03-03T10:00:00Z",
  "totalPrompts": 14398,
  "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.

<!-- REFERENCES_START -->

Use Case Category Files

| File | Category | Count | |------|----------|-------| | `profile-avatar.json` | Profile / Avatar | 2142 | | `social-media-post.json` | Social Media Post | 9833 | | `infographic-edu-visual.json` | Infographic / Edu Visual | 606 | | `youtube-thumbnail.json` | YouTube Thumbnail | 227 | | `comic-storyboard.json` | Comic / Storyboard | 703 | | `product-marketing.json` | Product Marketing | 5756 | | `ecommerce-main-image.json` | E-commerce Main Image | 579 | | `game-asset.json` | Game Asset | 728 | | `poster-flyer.json` | Poster / Flyer | 1039 | | `app-web-design.json` | App / Web Design | 242 | | `others.json` | Uncategorized | 1106 |

<!-- REFERENCES_END -->

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"