Nano Banana Image Generation & Editing

Multi-provider image generation and editing. Default provider: Tuzi (兔子API, api.tu-zi.com).

Script Directory

Agent Execution:

1. SKILL_DIR = this SKILL.md file's directory
2. Script path = ${SKILL_DIR}/scripts/main.ts

Usage

Run the script using absolute path (do NOT cd to skill directory first):

Generate new image:

npx -y bun ${SKILL_DIR}/scripts/main.ts --prompt "your image description" --filename "output.png" [--resolution 1K|2K|4K] [--provider tuzi|google|openai|dashscope|replicate] [--model MODEL_ID]

Edit existing image:

npx -y bun ${SKILL_DIR}/scripts/main.ts --prompt "editing instructions" --filename "output.png" --input-image "path/to/input.png" [--resolution 1K|2K|4K]

Important: Always run from the user's current working directory so images are saved where the user is working.

Default Workflow (draft → iterate → final)

Goal: fast iteration without burning time on 4K until the prompt is correct.

• Draft (1K): quick feedback loop
• npx -y bun ${SKILL_DIR}/scripts/main.ts --prompt "" --filename "yyyy-mm-dd-hh-mm-ss-draft.png" --resolution 1K
• Iterate: adjust prompt in small diffs; keep filename new per run
• If editing: keep the same --input-image for every iteration until you're happy.
• Final (4K): only when prompt is locked
• npx -y bun ${SKILL_DIR}/scripts/main.ts --prompt "" --filename "yyyy-mm-dd-hh-mm-ss-final.png" --resolution 4K

Options

| Option | Description |

|--------|-------------|

| --prompt , -p | Prompt text (required) |

| --filename , -f | Output filename (required) |

| --input-image , -i | Input image for editing |

| --resolution 1K\|2K\|4K, -r | Output resolution (default: 1K) |

| --provider tuzi\|google\|openai\|dashscope\|replicate | Force provider (default: auto-detect, Tuzi first) |

| --model , -m | Model ID |

| --api-key , -k | API key (overrides env var) |

Resolution Options

• 1K (default) - ~1024px resolution
• 2K - ~2048px resolution
• 4K - ~4096px resolution

Map user requests:

• No mention of resolution → 1K
• "low resolution", "1080", "1080p", "1K" → 1K
• "2K", "2048", "normal", "medium resolution" → 2K
• "high resolution", "high-res", "hi-res", "4K", "ultra" → 4K

Provider Selection

1. --provider specified → use it
2. --api-key provided (no --provider) → Google (direct Gemini API)
3. Only one API key available → use that provider
4. Multiple available → Tuzi first

Tuzi Models

| Model ID | Quality | Notes |

|----------|---------|-------|

| gemini-3-pro-image-preview | 1k/2k/4k | Default. High quality |

| gemini-3.1-flash-image-preview | 1k/2k/4k | Fast, extended aspect ratios |

| gemini-3-pro-image-preview-vip | 1k built-in | VIP |

| gemini-3-pro-image-preview-2k-vip | 2k built-in | VIP |

| gemini-3-pro-image-preview-4k-vip | 4k built-in | VIP |

Environment Variables

| Variable | Description |

|----------|-------------|

| TUZI_API_KEY | Tuzi API key (https://api.tu-zi.com) |

| TUZI_IMAGE_MODEL | Tuzi default model |

| TUZI_BASE_URL | Custom Tuzi endpoint |

| GEMINI_API_KEY | Google Gemini API key |

| GOOGLE_API_KEY | Google API key (alias) |

| OPENAI_API_KEY | OpenAI API key |

| DASHSCOPE_API_KEY | DashScope API key |

| REPLICATE_API_TOKEN | Replicate API token |

Load Priority: CLI --api-key > env vars > /.tuzi-skills/.env > ~/.tuzi-skills/.env

Image Editing

When the user wants to modify an existing image:

1. Use --input-image parameter with the path to the image
2. The prompt should contain editing instructions
3. Resolution auto-detects from input image size if not specified

Prompt Handling

For generation: Pass user's image description as-is to --prompt. Only rework if clearly insufficient.

For editing: Pass editing instructions in --prompt (e.g., "add a rainbow in the sky")

Prompt Templates

• Generation: "Create an image of: . Style: