banana-cog

What This Skill Does

Banana Cog acts as the advanced orchestration layer for Nano Banana image generation, powered by CellCog. Unlike standard image generation tools that focus on single-shot outputs, Banana Cog is designed for complex, multi-image workflows. It bridges the gap between text prompts and visual project management by employing a structured reasoning pipeline: Scene Planning, Character Design, Image Generation, Consistency Verification, and Composition Review. This skill is ideal for users needing 10 to 30 coherent images within a single execution, ensuring character identity, style adherence, and logical scene progression across an entire series.

Installation

To integrate Banana Cog, you must first ensure the foundational CellCog SDK is active. Run the following command in your terminal:

clawhub install cellcog

Once the dependency is satisfied, install the skill via the OpenClaw repository:

clawhub install openclaw/skills/skills/nitishgargiitd/banana-cog

Ensure your API credentials for Nano Banana and the associated Gemini image models are correctly configured within your environment to facilitate the request handling.

Use Cases

Banana Cog is built for professionals and creatives who require high-volume, high-consistency visual output. Key use cases include:

• Storyboarding and Animation Sequences: Planning character arcs across multiple narrative beats while maintaining visual fidelity.
• Brand Asset Creation: Generating comprehensive brand kits, including mascots in various poses and product mockups in multiple lifestyle settings.
• Style Transfer and Batch Processing: Transforming large sets of base images into a specific art style (e.g., cinematic, anime, or minimalist) without manual intervention.
• Photorealistic Series: Creating high-quality consistent portrait or interior design series for marketing campaigns.

Example Prompts

1. "Generate a sequence of 10 images showing a futuristic cyberpunk scout navigating through a neon-lit rain-slicked city at night, maintaining character consistency in every frame."
2. "Design a mascot character called 'ClawBot' and produce 5 images of it interacting with various office tools, keeping the color scheme and design language identical."
3. "Take the provided reference photo of a kitchen and generate 6 variations of the same layout, switching the design theme between modern farmhouse, industrial, minimalist, scandinavian, dark academia, and luxury marble."

Tips & Limitations

To get the best results, provide descriptive context regarding the 'scene logic' rather than just visual descriptions. Since the agent performs reasoning before generation, clarity in your character or composition constraints is paramount. Note that very long queues (approaching 30+ images) may take significant time to process. Always ensure your source reference images are clear and high-resolution to assist the model in its consistency verification phase.