opencode Skill

muapi-nano-banana

Reasoning-driven image generation using structured creative briefs (Gemini 3 style) — generates high-fidelity images via muapi.ai with logic-based prompting

LLM Mart · 0 points · 11 views 0 listing impressions 0 install-command copies
Virus-scanned Reviewed automatically before listing.

Full trust report

Download samuraigpt-generative-media-skills-.opencode_skills_muapi-nano-banana-74df8cb.zip · 2 KB
Part of samuraigpt/generative-media-skills — 72 skills

Install

skills CLI npx skills add https://github.com/SamurAIGPT/Generative-Media-Skills/tree/main/.opencode/skills/muapi-nano-banana
Claude Code claude plugin marketplace add https://llmmart.ai/marketplace.json && claude plugin install samuraigpt-generative-media-skills@llmmart
Git git clone https://github.com/SamurAIGPT/Generative-Media-Skills.git

The skills CLI installs just this skill, for any of its supported agents. Claude Code installs the whole samuraigpt/generative-media-skills collection as a plugin from our marketplace. Git is the plain clone.

Skill manifest

🍌 Nano-Banana Expert Skill (Gemini 3 Style)

A specialized skill for AI Agents to leverage "Reasoning-Driven" image generation. Based on the advanced prompting architecture of Google's Gemini 3 (Nano Banana Pro), this skill moves beyond keyword stuffing to structured, logic-based creative briefs.

Core Competencies

  1. Reasoning-Driven Prompting: Using natural language logic to define physics, lighting, and spatial relationships.
  2. Structured Creative Briefs: Implementing the "Perfect Prompt" formula: Subject + Action + Context + Composition + Lighting.
  3. Text Rendering Precision: Explicitly defining typography and signifiers for legible text integration.
  4. Contextual Grounding: Using "Search Grounding" logic (simulated) to anchor generations in real-world accuracy.

🏗️ Technical Specification

1. The "Perfect Prompt" Formula

Component Description Example
Subject Detailed entity description "A stoic robot barista with exposed copper wiring"
Action Dynamic interaction "Pouring a latte art leaf with mechanical precision"
Context Environment & Atmosphere "Inside a neon-lit cyberpunk cafe at midnight"
Composition Camera & Lens choice "Close-up, 85mm lens, f/1.8 aperture"
Lighting Mood & Direction "Volumetric blue rim light, warm cafe glow"
Style Aesthetic anchor "Cinematic, photorealistic, 4K production value"

2. Advanced Features

  • Negative Constraint Logic: Instead of "no blurry," use "Ensure sharp focus on the subject's eyes."
  • Identity Consistency: (Simulated) "Maintain consistent facial structure across variations."
  • Text Integration: Use double quotes for specific text: The sign reads "OPEN 24/7".

🧠 Prompt Optimization Protocol (Agent Instruction)

Before calling the script, the Agent MUST rewrite the user's prompt into a logic-driven Reasoning Brief:

  1. NO KEYWORD SOUP: Remove "8k, masterpiece, ultra-detailed." Use full, descriptive sentences.
  2. PHYSICAL CONSISTENCY: Describe how elements interact (e.g., "The light from the crystal shards casts caustic patterns across the obsidian floor").
  3. TEXT PRECISION: If the user wants text, define it precisely: featuring a sign that says "STORE NAME" in a weathered serif font.
  4. OPTICAL DIRECTIVES: Specify lens behavior: Shallow Depth of Field (f/1.8), Macro Lens, Anamorphic Flare.

🚀 Protocol: Using Nano-Banana

Step 1: Define the Creative Logic

Provide the agent with a subject and a specific scenario.

Step 2: Invoke the Script

The generate-nano-art.sh script translates the logic into a structured Gemini 3-style prompt.

# Generating a reasoning-driven image
bash scripts/generate-nano-art.sh \
  --subject "a glass chess piece" \
  --action "shattering into liquid shards" \
  --context "on a obsidian table" \
  --style "macro photography"

⚠️ Constraints & Guardrails

  • No Keyword Soup: MANDATORY - Do not use "trending on artstation, masterpiece, 8k". Use natural language descriptions.
  • Physics Logic: Ensure the prompt describes physically possible lighting and reflection interactions.
  • Full Sentences: The model parses relationships; use "light reflecting off the water" instead of "water, reflection".

⚙️ Implementation Details

This skill applies a "Logic Wrapper" around the core/media/generate-image.sh primitive, converting fragmented inputs into a coherent, reasoning-ready narrative prompt.

Files (generative-media-skills)
  • SKILL.md 3.7 KB
    ---
    name: muapi-nano-banana
    version: 0.1.0
    description: Reasoning-driven image generation using structured creative briefs (Gemini 3 style) — generates high-fidelity images via muapi.ai with logic-based prompting
    ---
    
    # 🍌 Nano-Banana Expert Skill (Gemini 3 Style)
    
    **A specialized skill for AI Agents to leverage "Reasoning-Driven" image generation.**
    Based on the advanced prompting architecture of Google's Gemini 3 (Nano Banana Pro), this skill moves beyond keyword stuffing to structured, logic-based creative briefs.
    
    ## Core Competencies
    
    1. **Reasoning-Driven Prompting**: Using natural language logic to define physics, lighting, and spatial relationships.
    2. **Structured Creative Briefs**: Implementing the "Perfect Prompt" formula: `Subject + Action + Context + Composition + Lighting`.
    3. **Text Rendering Precision**: Explicitly defining typography and signifiers for legible text integration.
    4. **Contextual Grounding**: Using "Search Grounding" logic (simulated) to anchor generations in real-world accuracy.
    
    ---
    
    ## 🏗️ Technical Specification
    
    ### 1. The "Perfect Prompt" Formula
    
    | Component | Description | Example |
    | :--- | :--- | :--- |
    | **Subject** | Detailed entity description | "A stoic robot barista with exposed copper wiring" |
    | **Action** | Dynamic interaction | "Pouring a latte art leaf with mechanical precision" |
    | **Context** | Environment & Atmosphere | "Inside a neon-lit cyberpunk cafe at midnight" |
    | **Composition** | Camera & Lens choice | "Close-up, 85mm lens, f/1.8 aperture" |
    | **Lighting** | Mood & Direction | "Volumetric blue rim light, warm cafe glow" |
    | **Style** | Aesthetic anchor | "Cinematic, photorealistic, 4K production value" |
    
    ### 2. Advanced Features
    - **Negative Constraint Logic**: Instead of "no blurry," use "Ensure sharp focus on the subject's eyes."
    - **Identity Consistency**: (Simulated) "Maintain consistent facial structure across variations."
    - **Text Integration**: Use double quotes for specific text: `The sign reads "OPEN 24/7"`.
    
    ---
    
    ## 🧠 Prompt Optimization Protocol (Agent Instruction)
    
    **Before calling the script, the Agent MUST rewrite the user's prompt into a logic-driven Reasoning Brief:**
    
    1. **NO KEYWORD SOUP**: Remove "8k, masterpiece, ultra-detailed." Use full, descriptive sentences.
    2. **PHYSICAL CONSISTENCY**: Describe how elements interact (e.g., "The light from the crystal shards casts caustic patterns across the obsidian floor").
    3. **TEXT PRECISION**: If the user wants text, define it precisely: `featuring a sign that says "STORE NAME" in a weathered serif font`.
    4. **OPTICAL DIRECTIVES**: Specify lens behavior: *Shallow Depth of Field (f/1.8)*, *Macro Lens*, *Anamorphic Flare*.
    
    ---
    
    ## 🚀 Protocol: Using Nano-Banana
    
    ### Step 1: Define the Creative Logic
    Provide the agent with a subject and a specific scenario.
    
    ### Step 2: Invoke the Script
    The `generate-nano-art.sh` script translates the logic into a structured Gemini 3-style prompt.
    
    ```bash
    # Generating a reasoning-driven image
    bash scripts/generate-nano-art.sh \
      --subject "a glass chess piece" \
      --action "shattering into liquid shards" \
      --context "on a obsidian table" \
      --style "macro photography"
    ```
    
    ---
    
    ## ⚠️ Constraints & Guardrails
    
    - **No Keyword Soup**: **MANDATORY** - Do not use "trending on artstation, masterpiece, 8k". Use natural language descriptions.
    - **Physics Logic**: Ensure the prompt describes *physically possible* lighting and reflection interactions.
    - **Full Sentences**: The model parses relationships; use "light reflecting off the water" instead of "water, reflection".
    
    ---
    
    ## ⚙️ Implementation Details
    This skill applies a "Logic Wrapper" around the `core/media/generate-image.sh` primitive, converting fragmented inputs into a coherent, reasoning-ready narrative prompt.
    

Comments (0)

Sign in to join the conversation.

No comments yet.

Reviews (0)

No reviews yet.

Related