Skills 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

install
source · Clone the upstream repo
git clone https://github.com/openclaw/skills
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/openclaw/skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/anil-matcha/muapi-nano-banana-skill" ~/.claude/skills/openclaw-skills-muapi-nano-banana && rm -rf "$T"
OpenClaw · Install into ~/.openclaw/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/openclaw/skills "$T" && mkdir -p ~/.openclaw/skills && cp -r "$T/skills/anil-matcha/muapi-nano-banana-skill" ~/.openclaw/skills/openclaw-skills-muapi-nano-banana && rm -rf "$T"
manifest: skills/anil-matcha/muapi-nano-banana-skill/SKILL.md
source content

🍌 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

ComponentDescriptionExample
SubjectDetailed entity description"A stoic robot barista with exposed copper wiring"
ActionDynamic interaction"Pouring a latte art leaf with mechanical precision"
ContextEnvironment & Atmosphere"Inside a neon-lit cyberpunk cafe at midnight"
CompositionCamera & Lens choice"Close-up, 85mm lens, f/1.8 aperture"
LightingMood & Direction"Volumetric blue rim light, warm cafe glow"
StyleAesthetic 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.