nano-banana-pro

intellectronica/agent-skills · updated Apr 8, 2026

$npx skills add https://github.com/intellectronica/agent-skills --skill nano-banana-pro
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summary

Text-to-image generation and image-to-image editing via Google's Gemini 3 Pro Image API.

  • Supports both new image generation from text prompts and editing of existing images with instruction-based modifications
  • Configurable output resolution: 1K (default), 2K, or 4K for high-resolution results
  • Automatically detects API key from --api-key argument or GEMINI_API_KEY environment variable
  • Saves PNG output to the user's current working directory with timestamped filenames
skill.md

Nano Banana Pro Image Generation & Editing

Generate new images or edit existing ones using Google's Nano Banana Pro API (Gemini 3 Pro Image).

Usage

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

Generate new image:

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

Edit existing image:

uv run ~/.claude/skills/nano-banana-pro/scripts/generate_image.py --prompt "editing instructions" --filename "output-name.png" --input-image "path/to/input.png" [--resolution 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.

Resolution Options

The Gemini 3 Pro Image API supports three resolutions (uppercase K required):

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

Map user requests to API parameters:

  • 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.

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.

Output

  • Saves PNG to current directory (or specified path if filename includes directory)
  • Script outputs the full path to the generated image
  • Do not read the image back - just inform the user of the saved path

Examples

Generate new image:

uv run ~/.claude/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 ~/.claude/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

Discussion

Product Hunt–style comments (not star reviews)
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general reviews

Ratings

4.533 reviews
  • Charlotte Rao· Dec 24, 2024

    Useful defaults in nano-banana-pro — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Dhruvi Jain· Dec 12, 2024

    I recommend nano-banana-pro for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Emma Lopez· Dec 8, 2024

    nano-banana-pro is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Nia Brown· Dec 4, 2024

    Registry listing for nano-banana-pro matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Aisha Shah· Nov 27, 2024

    Keeps context tight: nano-banana-pro is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Oshnikdeep· Nov 3, 2024

    Solid pick for teams standardizing on skills: nano-banana-pro is focused, and the summary matches what you get after install.

  • Ganesh Mohane· Oct 22, 2024

    nano-banana-pro is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Aisha Gupta· Oct 18, 2024

    I recommend nano-banana-pro for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Harper Gill· Sep 25, 2024

    nano-banana-pro reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Henry Taylor· Sep 13, 2024

    nano-banana-pro is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

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