This skill should be used when the user asks to "generate an image", "create an image", "make a picture", "draw me a", "create artwork", "make an illustration", "edit an image", "modify a photo", "upload a file to Gemini", "check image stats", "change the aspect ratio", or mentions nanobanana, Gemini image generation, or AI art creation. Triggers include: "generate an image", "edit image", "create a picture", "4K image", "model tier", "aspect ratio", "negative prompt", "style transfer".
From image-gennpx claudepluginhub aaronbassett/agent-foundry --plugin image-genThis skill uses the workspace's default tool permissions.
references/parameters.mdGuides Next.js Cache Components and Partial Prerendering (PPR) with cacheComponents enabled. Implements 'use cache', cacheLife(), cacheTag(), revalidateTag(), static/dynamic optimization, and cache debugging.
Migrates code, prompts, and API calls from Claude Sonnet 4.0/4.5 or Opus 4.1 to Opus 4.5, updating model strings on Anthropic, AWS, GCP, Azure platforms.
Analyzes BMad project state from catalog CSV, configs, artifacts, and query to recommend next skills or answer questions. Useful for help requests, 'what next', or starting BMad.
Generate, edit, and manage AI images using the nanobanana MCP server powered by Google Gemini models.
A GEMINI_API_KEY environment variable must be set. Obtain a key from Google AI Studio.
| Tool | Purpose |
|---|---|
generate_image | Generate new images or edit existing ones |
edit_image | Conversational image editing on a base image |
upload_file | Upload files to Gemini Files API |
show_output_stats | Display output directory statistics |
Call generate_image with a descriptive prompt. Include subject, composition, action, location, and style for best results.
generate_image(
prompt="A golden retriever sitting in a sunlit meadow, watercolor style",
n=1
)
Always craft detailed, descriptive prompts. Vague prompts produce generic results.
Set n (1-4) to generate multiple variations from the same prompt.
generate_image(
prompt="Minimalist logo design for a coffee shop called 'Bean There'",
n=3
)
Specify aspect_ratio for different output formats. Supported values: 1:1, 2:3, 3:2, 3:4, 4:3, 4:5, 5:4, 9:16, 16:9, 21:9.
generate_image(
prompt="Cinematic landscape at sunset",
aspect_ratio="21:9"
)
Common use cases:
1:1 (Instagram), 9:16 (Stories/Reels)16:99:1621:93:4 or 2:3Three models available via model_tier:
| Tier | Model | Speed | Max Resolution | Best For |
|---|---|---|---|---|
auto (default) | Smart selection | Varies | Varies | Recommended — routes to NB2 or Pro based on prompt |
nb2 | Gemini 3.1 Flash Image | ~2-4s | 4K (3840px) | Most tasks, production assets |
pro | Gemini 3 Pro Image | ~5-8s | 4K (3840px) | Complex compositions, max quality |
flash | Gemini 2.5 Flash Image | ~2-3s | 1024px | Quick drafts, high-volume |
generate_image(
prompt="Intricate fantasy map with labeled regions",
model_tier="pro",
thinking_level="HIGH"
)
Use auto (the default) in most cases — it typically routes to nb2. Explicitly select pro for complex scenes requiring deep reasoning, or flash for rapid prototyping. For full model comparison, see references/parameters.md.
Use edit_image for conversational edits on a single image. Provide a base64-encoded image and a natural language instruction.
edit_image(
instruction="Add a knitted wizard hat to the cat",
base_image_b64="<base64 data>",
mime_type="image/png"
)
Alternatively, use generate_image with input_image_path_1 for file-based editing:
generate_image(
prompt="Remove the background and replace with a gradient",
input_image_path_1="/path/to/image.png",
mode="edit"
)
Combine up to 3 input images for composition, style transfer, or blending:
generate_image(
prompt="Combine the style of the first image with the subject of the second",
input_image_path_1="/path/to/style-reference.png",
input_image_path_2="/path/to/subject.png"
)
Upload images larger than 20MB or images reused across multiple prompts:
upload_file(
path="/path/to/large-image.png",
display_name="Product photo"
)
Then reference the returned file_id in subsequent generate_image calls:
generate_image(
prompt="Add a holiday theme to this product photo",
file_id="files/abc123",
mode="edit"
)
Specify where generated images are saved with output_path:
generate_image(
prompt="Company logo in blue and white",
output_path="/path/to/project/assets/logo.png"
)
If not specified, images save to the IMAGE_OUTPUT_DIR env var or ~/nanobanana-images.
Specify what to avoid in the output:
generate_image(
prompt="Professional headshot photo, studio lighting",
negative_prompt="blurry, distorted, cartoon, illustration"
)
For maximum quality output, combine Pro model with 4K resolution and grounding:
generate_image(
prompt="Product photography: leather wallet on marble surface, dramatic lighting",
model_tier="pro",
resolution="4k",
enable_grounding=true,
thinking_level="HIGH"
)
system_instruction for tone and include exact text to render in the promptFor complete parameter documentation, consult:
references/parameters.md - Full parameter reference for all tools with types and defaults