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cs995279497-byte

Chen Nano Banana Pro

by cs995279497-byte · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
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Install in OpenClaw
/install chen-nano-banana-pro
Description
Generate/edit images with Nano Banana Pro (Gemini 3 Pro Image). Supports text-to-image, edits, and 1K/2K/4K resolution.
README (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 ~/.codex/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 ~/.codex/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.

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 "\x3Cdraft 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 "\x3Cfinal prompt>" --filename "yyyy-mm-dd-hh-mm-ss-final.png" --resolution 4K

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.

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: \x3Csubject>. Style: \x3Cstyle>. Composition: \x3Ccamera/shot>. Lighting: \x3Clighting>. Background: \x3Cbackground>. Color palette: \x3Cpalette>. Avoid: \x3Clist>.”
  • Editing template (preserve everything else):

    • “Change ONLY: \x3Csingle 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)
  • 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 ~/.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
Usage Guidance
This skill appears to do what it claims (generate/edit images via Gemini), but packaging inconsistencies suggest it wasn't curated carefully. Before installing or running: 1) Verify you have/are willing to provide a Gemini API key (GEMINI_API_KEY or pass via --api-key). 2) Ensure the 'uv' runner and Python deps (google-genai, pillow) are installed — they are referenced but not declared in registry metadata. 3) Note hard-coded example paths in SKILL.md; run the script from the directory where you want output saved, and confirm the script's behavior on a test image. 4) Check the owner/metadata differences (ownerId/version/slug mismatches) — if you need provenance, ask the publisher for clarification or prefer a skill from a known source. 5) If you are uneasy, run the script in an isolated environment (container or VM) and inspect network calls (to ensure requests go to expected Google endpoints) before supplying any API key. If you want, I can point out the exact lines to review or help craft a safer invocation command.
Capability Analysis
Type: OpenClaw Skill Name: chen-nano-banana-pro Version: 1.0.0 The skill is a functional wrapper for image generation and editing using the Google GenAI library. While it references a likely fictitious or placeholder model name ('gemini-3-pro-image-preview') and contains hardcoded absolute paths in SKILL.md (e.g., /Users/apple/...), the underlying Python script (scripts/generate_image.py) contains no malicious logic, data exfiltration, or unauthorized execution. It correctly handles API keys via environment variables or arguments and uses standard libraries (PIL, google-genai) for its stated purpose.
Capability Assessment
Purpose & Capability
The Python script implements Gemini-based image generation and editing as described, using google-genai and Pillow — that capability is consistent with the name/description. However, the skill metadata declares no required env vars or binaries while the SKILL.md and script require an API key (GEMINI_API_KEY or --api-key) and the SKILL.md expects the 'uv' runner to be present. This mismatch between declared requirements and actual runtime needs is concerning.
Instruction Scope
SKILL.md gives a focused runtime workflow (pass prompt, optional input image, save PNG to CWD). The instructions do not request unrelated files or credentials beyond the Gemini API key. Minor issues: examples and the skill header contain hard-coded absolute paths (e.g., /Users/apple/... and ~/.codex/...), and the SKILL.md instructs running from the user's CWD for save location — both are packaging/usage quirks to be aware of but not inherently malicious.
Install Mechanism
No install spec is present (instruction-only with a script file). There are no remote downloads or extract steps. The script lists dependencies (google-genai, pillow) but they are not installed automatically; this is low install risk but means users must install dependencies themselves.
Credentials
The script legitimately requires a Gemini API key (GEMINI_API_KEY or --api-key), which is proportionate to image generation. But the registry metadata claims no required env vars while SKILL.md and the script require GEMINI_API_KEY, creating an inconsistency. No other unrelated credentials are requested. Also note the skill will need permission to write image files to the chosen working directory.
Persistence & Privilege
The skill is not marked always:true and does not request persistent agent-wide privileges. It only writes generated images (and creates parent directories) in the current working directory; it does not modify other skills or global configs.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install chen-nano-banana-pro
  3. After installation, invoke the skill by name or use /chen-nano-banana-pro
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
- Initial release of chen-nano-banana-pro skill. - Generate or edit images using Nano Banana Pro (Gemini 3 Pro Image) API. - Supports text-to-image and image editing with customizable 1K, 2K, or 4K resolution. - API key detection: accepts --api-key argument or GEMINI_API_KEY environment variable. - Flexible prompt handling for both generation and editing modes, with recommended templates for clarity. - Output images saved in the user's current directory; filenames include timestamp and descriptive context.
Metadata
Slug chen-nano-banana-pro
Version 1.0.0
License MIT-0
All-time Installs 1
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is Chen Nano Banana Pro?

Generate/edit images with Nano Banana Pro (Gemini 3 Pro Image). Supports text-to-image, edits, and 1K/2K/4K resolution. It is an AI Agent Skill for Claude Code / OpenClaw, with 112 downloads so far.

How do I install Chen Nano Banana Pro?

Run "/install chen-nano-banana-pro" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Chen Nano Banana Pro free?

Yes, Chen Nano Banana Pro is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Chen Nano Banana Pro support?

Chen Nano Banana Pro is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Chen Nano Banana Pro?

It is built and maintained by cs995279497-byte (@cs995279497-byte); the current version is v1.0.0.

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