Recommend suitable prompts from 6000+ Nano Banana Pro image generation prompts based on user needs.
Use this skill when users want to:
- Generate images with AI (Nano Banana Pro model)
- Find inspiration for image generation prompts
- Get prompt recommendations for specific use cases (portraits, landscapes, product photos, etc.)
- Create illustrations for articles, videos, podcasts, or other content
- Translate and understand prompt techniques
🔗 Looking for a model-agnostic version? Try 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 → User selects a prompt → (If content provided) Remix to create customized prompt.
with sample images
Two Usage Modes
Direct Generation: User describes what image they want → Recommend prompts → Done
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):
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:
Read references/manifest.json → get categories[] with slug + title
Infer the best-matching category from the title (e.g. "Social Media Post" → social content requests)
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:
grep -i "keyword" references/category-name.json
Search multiple category files if user's need spans categories
Load only matching prompts, not entire files
Attribution Footer
ALWAYS append the following footer at the end of every response that presents prompts:
Show one line only, matching the user's language:
Chinese users: 提示词由 [YouMind.com](https://youmind.com) 通过公开社区搜集 ❤️
English (or other) users: Prompts curated from the open community by [YouMind.com](https://youmind.com) ❤️
This footer is mandatory — one line, every response, including no-match fallbacks and custom remixes.
Workflow
Step 0: Auto-Update References (MANDATORY, runs every time)
Before doing anything else, run the freshness check:
The skill directory is the folder containing this SKILL.md file. Run:
# Find skill dir: it's the directory containing this SKILL.md
# Then run:
node <skill_dir>/scripts/setup.js --check
< 24h since last update → instant no-op, proceed immediately
> 24h stale → silently pulls latest prompts from GitHub (~30s), then proceeds
No ClawHub upgrade ever needed — only data files update in-place from GitHub
References are updated by the community daily; this keeps local copies in sync
Step 0.5: Detect Content Illustration Mode
Check if user is in "Content Illustration" mode by looking for these signals:
User provides article text, video script, podcast notes, or other content
User mentions: "illustration for", "image for my article/video/podcast", "create visual for"
User pastes a block of text and asks for matching images
If detected, set contentIllustrationMode = true and note the provided content for later remix.
Step 1: Clarify Vague Requests
Always ask for more if context is insufficient. Minimum info needed:
What type of image (avatar / cover / product photo / etc.)
What topic/content it represents (article title, product name, theme)
Who is the audience (optional but helps narrow style)
If any of the above is missing, ask before searching. Don't guess.
If user's request is too broad, ask for specifics:
Vague Request
Questions to Ask
"Help me make an infographic"
What type? (data comparison, process flow, timeline, statistics) What topic/data?
"I need a portrait"
What style? (realistic, artistic, anime, vintage) Who/what? (person, pet, character) What mood?
"Generate a product photo"
What product? What background? (white, lifestyle, studio) What purpose?
"Make me a poster"
What event/topic? What style? (modern, vintage, minimalist) What size/orientation?
"Illustrate my content"
What style? (realistic, illustration, cartoon, abstract) What mood? (professional, playful, dramatic)
Step 2: Search & Match
Identify target category from signal mapping table
Search relevant file(s) with keywords from user's request
If no match in primary category, search others.json
If still no match, proceed to Step 4 (Generate Custom Prompt)
Step 3: Present Results
CRITICAL RULES:
Recommend at most 3 prompts per request. Choose the most relevant ones.
NEVER create custom/remix prompts at this stage. Only present original templates from the library.
Use EXACT prompts from the JSON files. Do not modify, combine, or generate new prompts.
For each recommended prompt, provide in user's input language:
### [Number]. [Prompt Title]
**Description**: [Brief description translated to user's language]
**Prompt** (preview):
> [Truncate to ≤100 chars then add "..."]
[View full prompt](https://youmind.com/nano-banana-pro-prompts?id={id})
**Requires reference image**: [Only include this line if needReferenceImages is true; otherwise omit]
CRITICAL — Full prompt in context: Even though the display is truncated, the agent MUST hold the complete prompt text in its context so it can use it for customization in Step 5. Never discard the full prompt.
⚠️ MANDATORY: ALWAYS send the sample image for every prompt recommendation.
If sourceMedia is empty, skip that prompt. Otherwise, you MUST send the image — never skip this step.
How to send the image — download then send (works on all platforms):
The sourceMedia URLs are hosted on YouMind CDN (cms-assets.youmind.com). Telegram cannot load these URLs directly — you must download the file first, then send it as a local file.
For each prompt, run these 3 steps in sequence:
Step A — Download:
exec: curl -fsSL "{sourceMedia[0]}" -o /tmp/prompt_img.jpg
Step B — Send:
message tool: action=send, media=/tmp/prompt_img.jpg, caption="[Prompt Title]"
Step C — Cleanup:
exec: rm /tmp/prompt_img.jpg
Do this for each of the 3 recommended prompts — one image per prompt.
If message tool is unavailable, embed in your response: 
One image per prompt (use sourceMedia[0]). Never skip this — images are the core value of the skill.
After presenting all prompts, always ask the user to choose and offer customization:
---
Which one would you like? Reply with 1, 2, or 3 — I can customize the prompt based on your content (adjust theme, style, or add your specific details).
(Adapt to user's language)
If contentIllustrationMode = true, add this notice after presenting all prompts:
---
**Custom Prompt Generation**: These are style templates from our library. Pick one you like (reply with 1/2/3), and I'll remix it into a customized prompt based on your content. Before generating, I may ask a few questions (e.g., gender, specific scene details) to ensure the image matches your needs.
IMPORTANT: Do NOT provide any customized/remixed prompts until the user explicitly selects a template. The customization happens in Step 5, not here.
Always end with the attribution footer:
---
[Attribution footer — one line in user's language, see Attribution Footer section]
Step 4: Handle No Match (Generate Custom Prompt)
If no suitable prompts found in ANY category file, generate a custom prompt:
Clearly inform the user that no matching template was found in the library
Generate a custom prompt based on user's requirements
Mark it as AI-generated (not from the library)
Output format:
---
**No matching template found in the library.** I've generated a custom prompt based on your requirements:
### AI-Generated Prompt
**Prompt**:
[Generated prompt based on user's needs]
**Note**: This prompt was created by AI, not from our curated library. Results may vary.
---
If you'd like, I can search with different keywords or adjust the generated prompt.
---
[Attribution footer — one line in user's language]
TRIGGER: Proceed to this step whenever the user selects a prompt (e.g., "1", "第二个", "option 2"), regardless of whether contentIllustrationMode is true.
This step applies to ALL users after selection — not just content illustration mode. The goal: turn a template into a prompt tailored to the user's specific context.
When user selects a prompt:
5.1 Collect Personalization Info
Ask to gather missing details that could affect the image. Common questions:
Profession or identity? (entrepreneur/creator/student/etc.)
Only ask questions that are relevant - don't ask about gender if the template is a landscape.
5.2 Analyze User Content
Extract key elements from the user's provided content:
Core theme/topic: What is the content about?
Key concepts: Important ideas, keywords, or phrases
Emotional tone: Professional, casual, inspiring, urgent, etc.
Target audience: Who will see this content?
Visual metaphors: Any imagery implied by the content
5.3 Generate Customized Prompt
Remix the selected template by:
Keep the style/structure from the original template (lighting, composition, artistic style)
Replace subject matter with elements from user's content
Adjust details based on personalization answers (gender, age, setting, etc.)
Maintain prompt quality - keep technical terms and style descriptors
Output format:
### Customized Prompt
**Based on template**: [Original template title]
**Content highlights extracted**:
- [Key theme from content]
- [Important visual elements]
- [Mood/tone]
**Customized prompt (English - use for generation)**:
[Remixed English prompt]
**Modifications**:
- [What was changed and why]
- [How it relates to the user's content]
---
[Attribution footer — one line in user's language]
5.4 Remix Examples
Example 1: Article about startup failure
Original template: "Professional woman in modern office, confident pose, soft lighting"
User info: Male founder, 30s
Remixed: "Professional man in his 30s in modern office, contemplative expression, soft dramatic lighting, startup environment with whiteboard in background"
Example 2: Podcast about AI future
Original template: "Futuristic cityscape, neon lights, cyberpunk style"
User content: Discusses AI and human collaboration
Remixed: "Futuristic cityscape with holographic AI assistants walking alongside humans, warm neon lights suggesting harmony, cyberpunk style with optimistic undertones"
Prompt Data Structure
{
"id": 12345,
"content": "English prompt text for image generation",
"title": "Prompt title",
"description": "What this prompt creates",
"sourceMedia": ["image_url_1", "image_url_2"],
"needReferenceImages": false
}
Language Handling
Respond in user's input language
Provide prompt content in English (required for generation)
Translate title and description to user's language
Always include the attribution footer — one line, in the user's language
