MCPInstall

nano-banana-pro

Nano Banana/Gemini image gen/edit: text/image input, 512-4K workflows.

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Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/steipete/agent-scripts --skill nano-banana-pro
  1. 01

    Install

    Run the command in your project. The CLI asks which agents to install for.

  2. 02

    Describe the task

    Ask your agent for something this skill covers. It loads nano-banana-pro automatically when relevant.

  3. 03

    Review the result

    The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

Nano Banana 2 Image Generation & Editing

Generate new images or edit existing ones using Google's Nano Banana 2 API (Gemini 3.1 Flash Image).

Usage

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

Generate new image:

uv run ~/.codex/skills/nano-banana-pro/scripts/generate_image.py --prompt "your image description" --filename "output-name.png" [--resolution 512|1K|2K|4K] [--api-key KEY]

Edit existing image:

uv run ~/.codex/skills/nano-banana-pro/scripts/generate_image.py --prompt "editing instructions" --filename "output-name.png" --input-image "path/to/input.png" [--resolution 512|1K|2K|4K] [--api-key KEY]

Important: Always run from the user's current working directory so images are saved where the user is working, not in the skill directory.

Default Workflow (draft → iterate → final)

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

  • Draft (1K): quick feedback loop
    • uv run ~/.codex/skills/nano-banana-pro/scripts/generate_image.py --prompt "<draft 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
    • uv run ~/.codex/skills/nano-banana-pro/scripts/generate_image.py --prompt "<final prompt>" --filename "yyyy-mm-dd-hh-mm-ss-final.png" --resolution 4K

Resolution Options

The Gemini 3.1 Flash Image API supports these output size values:

  • 512 - compact ~512px-class resolution
  • 1K (default) - ~1024px resolution
  • 2K - ~2048px resolution
  • 4K - ~4096px resolution

Map user requests to API parameters:

  • "512", "512px", "0.5K", "thumbnail", "tiny" → 512
  • 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

API Key

The script checks for API key in this order:

  1. --api-key argument (use if user provided key in chat)
  2. GEMINI_API_KEY environment variable

If neither is available, the script exits with an error message.

Preflight + Common Failures (fast fixes)

  • Preflight:

    • command -v uv (must exist)
    • test -n \"$GEMINI_API_KEY\" (or pass --api-key)
    • If editing: test -f \"path/to/input.png\"
  • Common failures:

    • Error: No API key provided. → set GEMINI_API_KEY or pass --api-key
    • Error loading input image: → wrong path / unreadable file; verify --input-image points to a real image
    • “quota/permission/403” style API errors → wrong key, no access, or quota exceeded; try a different key/account

Filename Generation

Generate filenames with the pattern: yyyy-mm-dd-hh-mm-ss-name.png

Format: {timestamp}-{descriptive-name}.png

  • Timestamp: Current date/time in format yyyy-mm-dd-hh-mm-ss (24-hour format)
  • Name: Descriptive lowercase text with hyphens
  • Keep the descriptive part concise (1-5 words typically)
  • Use context from user's prompt or conversation
  • If unclear, use random identifier (e.g., x9k2, a7b3)

Examples:

  • Prompt "A serene Japanese garden" → 2025-11-23-14-23-05-japanese-garden.png
  • Prompt "sunset over mountains" → 2025-11-23-15-30-12-sunset-mountains.png
  • Prompt "create an image of a robot" → 2025-11-23-16-45-33-robot.png
  • Unclear context → 2025-11-23-17-12-48-x9k2.png

Image Editing

When the user wants to modify an existing image:

  1. Check if they provide an image path or reference an image in the current directory
  2. Use --input-image parameter with the path to the image
  3. The prompt should contain editing instructions (e.g., "make the sky more dramatic", "remove the person", "change to cartoon style")
  4. Common editing tasks: add/remove elements, change style, adjust colors, blur background, etc.

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", "make it look like a watercolor painting")

Preserve user's creative intent in both cases.

Prompt Templates (high hit-rate)

Use templates when the user is vague or when edits must be precise.

  • Generation template:

    • “Create an image of: <subject>. Style: <style>. Composition: <camera/shot>. Lighting: <lighting>. Background: <background>. Color palette: <palette>. Avoid: <list>.”
  • Editing template (preserve everything else):

    • “Change ONLY: <single change>. Keep identical: subject, composition/crop, pose, lighting, color palette, background, text, and overall style. Do not add new objects. If text exists, keep it unchanged.”

Output

  • Saves PNG to current directory (or specified path if filename includes directory)
  • Requires a new filename: existing files, hard links, and symlinks are rejected. Parent directories are created as needed, but symlinked path components are rejected; use their real directory paths instead. Absolute paths and paths outside the current directory remain supported on macOS and Linux.
  • Script outputs the full path to the generated image
  • Do not read the image back - just inform the user of the saved path

Offline output-safety regression tests (Pillow required): python3 -m unittest discover -s skills/nano-banana-pro/scripts -p 'test_*.py' from the repository root.

Examples

Generate new image:

uv run ~/.codex/skills/nano-banana-pro/scripts/generate_image.py --prompt "A serene Japanese garden with cherry blossoms" --filename "2025-11-23-14-23-05-japanese-garden.png" --resolution 4K

Edit existing image:

uv run ~/.codex/skills/nano-banana-pro/scripts/generate_image.py --prompt "make the sky more dramatic with storm clouds" --filename "2025-11-23-14-25-30-dramatic-sky.png" --input-image "original-photo.jpg" --resolution 2K

FAQ

What does the nano-banana-pro skill do?

Nano Banana/Gemini image gen/edit: text/image input, 512-4K workflows.

How do I install nano-banana-pro?

Run npx skills add https://github.com/steipete/agent-scripts --skill nano-banana-pro in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/nano-banana-pro/ (personal) or .claude/skills/nano-banana-pro/ (project).

Which AI agents can use nano-banana-pro?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is nano-banana-pro safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains nano-banana-pro?

It is published by steipete in steipete/agent-scripts. It has 293 recorded installs.

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