Add Nano Banana Pro as first README example, remove old duplicate
New example uses fresh V2 research output showing JSON prompting dominance, @handle citations, and the full research-to-prompt flow. Removed the old iOS App Mockup example which used the same SwimMom prompt/image but with stale V1 data. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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@@ -62,6 +62,76 @@ Examples:
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---
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## Example: Nano Banana Pro Prompting (Image Generation)
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**Query:** `/last30days nano banana pro prompting`
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**Research Output:**
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> JSON prompting is the dominant technique — The X community overwhelmingly uses structured JSON prompts rather than plain text. Creators like @Xmira_belle, @Cicily_aura, @RubenSalvo_, and @mahivisuals all share prompts in JSON format with nested objects for metadata, subject descriptions, lighting, camera specs, and scene composition. @realdigitaldao made a static ad "in less than 5 min" using a simple JSON prompt.
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>
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> Prompt adherence is Nano Banana Pro's killer advantage — JSON prompts hit 92% precision for color accuracy, lighting ratios, and composition vs ~68% for natural language prompts, per fofr.ai. @artingent directly compared it to GPT Image 1.5 and noted Nano Banana Pro has higher prompt adherence — "GPT image 1.5 ignored the Top Down instruction."
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>
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> Stop writing "tag soup" — act like a Creative Director — The biggest shift is away from comma-separated keyword lists toward natural language descriptions with clear structure. The ICS Framework (Image type, Content, Style) and the 5-element formula (subject, composition, action, setting, style) are the two dominant approaches, per r/nanobanana2pro.
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**Key patterns discovered:**
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1. JSON > plain text — Structure prompts as JSON objects with keys for subject, composition, lighting, camera, style — per @Xmira_belle, @Cicily_aura
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2. The 5-element formula — Subject + Composition + Action + Setting + Style — per r/nanobanana2pro
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3. Separate subjects into distinct objects — Multi-character scenes need each person in their own JSON block to prevent "concept bleeding" — per fofr.ai
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4. Use camera/lens metadata — Aperture, focal length, ISO, film stock as JSON keys for hidden photorealism control
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5. 14 reference images max — Feed up to 14 reference images for brand/character consistency — per Google DeepMind
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**Research Stats:** 8 Reddit threads (455 upvotes) + 31 X posts (183 likes, 68 reposts) from r/nanobanana2pro, r/promptingmagic, @Xmira_belle (106 likes), @Cicily_aura (45 likes)
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**Then asked:** "make a mock-up of an app for moms who swim"
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**Generated Prompt:**
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```json
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{
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"image_type": "UI mockup",
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"device": {
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"frame": "iPhone 16 Pro",
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"display": "realistic screen with subtle reflection",
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"orientation": "portrait"
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},
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"app_concept": "SwimMom - fitness and community app for mothers who swim",
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"screen": "home dashboard",
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"design_system": {
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"style": "iOS 18 native",
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"corners": "rounded, 16px radius",
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"shadows": "soft drop shadows, subtle depth",
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"spacing": "8pt grid, generous whitespace"
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},
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"color_palette": {
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"primary": "calming aqua blue (#4ECDC4)",
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"secondary": "warm coral (#FF6B6B)",
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"background": "clean white with soft blue gradient header"
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},
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"layout": {
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"header": "greeting 'Good morning, Sarah' with wave icon, profile avatar top right",
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"hero_card": "today's swim stats - laps, calories, time - with circular progress ring",
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"section_2": "horizontal scroll of upcoming mom swim meetups with location pills",
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"section_3": "two cards - 'My Goals' with streak counter, 'Find a Pool' with map pin",
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"bottom_nav": "5 icons - Home (active), Workouts, Community, Schedule, Profile"
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},
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"visual_details": {
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"illustrations": "friendly, minimal line art of swimming figure",
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"typography": "SF Pro Display, clean hierarchy",
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"mood": "energizing yet calm, supportive community feel"
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}
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}
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```
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**The Result:**
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<p align="center">
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<img src="assets/swimmom-mockup.jpeg" width="400" alt="SwimMom iOS app mockup"/>
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</p>
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This example shows /last30days learning that **JSON prompts dominate** the Nano Banana Pro community (not plain text), then applying that format to generate an iOS mockup in one shot. The research came from real X creators and Reddit threads — techniques you wouldn't find in official docs.
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---
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## Example: Legal Prompting (Hallucination Prevention)
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**Query:** `/last30days prompting techniques for chatgpt for legal questions`
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@@ -203,75 +273,6 @@ This example shows /last30days as a **setup guide aggregator** - pulling togethe
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---
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## Example: iOS App Mockup (Nano Banana Pro)
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**Query:** `/last30days prompting tips for nano banana pro for ios designs`
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**Research Output:**
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> The community has converged on JSON-structured prompts for UI work - multiple viral posts from @brindleyai, @bananababydoll, and @fofrAI use detailed JSON with nested objects for subject, scene, and style. The key workflow from @fofrAI: take an existing image, have Gemini generate a JSON prompt from it, then iterate. For iOS specifically, @paji_a and @chongdashu both documented using Nano Banana Pro for iOS app mockup designs in "vibe coding" workflows.
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>
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> The web guides emphasize thinking in layers: define the window frame first, then UI layout (sidebars, nav bars, cards), then text on buttons/headings. Google's official prompting guide says to drop the "4k masterpiece trending on artstation" spam - Nano Banana Pro understands natural language. For tight layouts, use an 8pt grid and limit screens to 6-8 elements.
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**Key patterns discovered:**
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1. JSON prompt format with nested sections (subject, scene, style, device)
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2. Layer-based structure - frame -> layout regions -> content -> text labels
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3. iOS 18 / Material Design 3 references - rounded corners, soft shadows, vibrant primary
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4. iPhone frame specification - "inside realistic iPhone 16 Pro frame"
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5. Wireframe-to-mockup workflow - upload sketch, request high-fidelity conversion
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6. 8pt grid + 6-8 elements max per screen for clean density
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7. Iterative editing - don't re-roll, ask for specific changes if 80% correct
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**Then asked:** "make a mock-up of an app for moms who swim"
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**Generated Prompt:**
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```json
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{
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"image_type": "UI mockup",
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"device": {
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"frame": "iPhone 16 Pro",
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"display": "realistic screen with subtle reflection",
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"orientation": "portrait"
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},
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"app_concept": "SwimMom - fitness and community app for mothers who swim",
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"screen": "home dashboard",
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"design_system": {
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"style": "iOS 18 native",
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"corners": "rounded, 16px radius",
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"shadows": "soft drop shadows, subtle depth",
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"spacing": "8pt grid, generous whitespace"
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},
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"color_palette": {
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"primary": "calming aqua blue (#4ECDC4)",
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"secondary": "warm coral (#FF6B6B)",
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"background": "clean white with soft blue gradient header",
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"accents": "pool water ripple patterns, subtle"
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},
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"layout": {
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"header": "greeting 'Good morning, Sarah' with small wave icon, profile avatar top right",
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"hero_card": "today's swim stats - laps completed, calories burned, time in pool - with circular progress ring",
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"section_2": "horizontal scroll of upcoming mom swim meetups with location pills and participant avatars",
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"section_3": "two cards side by side - 'My Goals' with streak counter, 'Find a Pool' with map pin icon",
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"bottom_nav": "5 icons - Home (active), Workouts, Community, Schedule, Profile"
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},
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"visual_details": {
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"illustrations": "friendly, minimal line art of swimming figure",
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"typography": "SF Pro Display, clean hierarchy",
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"mood": "energizing yet calm, supportive community feel"
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}
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}
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```
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**The Result:**
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<p align="center">
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<img src="assets/swimmom-mockup.jpeg" width="400" alt="SwimMom iOS app mockup"/>
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</p>
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This example shows /last30days learning **AI image generation prompting patterns** (JSON structure, layer-based thinking, iOS design system references) and applying them to create a production-quality app mockup in one shot.
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---
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## Example: Top Claude Code Skills (Recommendations)
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**Query:** `/last30days top claude code skills`
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