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Muapi Nano Banana

skill-samuraigpt-generative-media-skills-muapi-nano-banana · by SamurAIGPT

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

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Install

$ agentstack add skill-samuraigpt-generative-media-skills-muapi-nano-banana

✓ scanned · ✓ verified — works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

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About

🍌 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.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.