nano-banana-pro-openrouter

Generate/edit images with Nano Banana Pro (Gemini 3 Pro Image) via OpenRouter. Use for image create/modify requests incl. edits. Supports text-to-image + ima...

Security Scan

The skill's code and instructions match its stated purpose (image generation/editing via OpenRouter) with no evident attempts to access unrelated secrets or endpoints, but there are small metadata and dependency omissions you should note before installing.

Purpose & Capability

The name/description (Nano Banana Pro via OpenRouter) aligns with the scripts: they call OpenRouter's API and use the Gemini image model. Minor mismatch: SKILL.md expects the 'uv' CLI and an OPENROUTER_KEY, but the skill registry metadata lists no required binaries or env vars.

Instruction Scope

Runtime instructions and scripts only read the input image(s) you explicitly provide, convert that image to a data URL, and POST to https://openrouter.ai. The scripts do not attempt to read arbitrary system files or unrelated environment variables.

Install Mechanism

This is instruction + script only (no install spec). The scripts list dependencies (requests, pillow) in comments but do not install them; SKILL.md and scripts assume the 'uv' runner and Python deps are present. That is a usability/integration omission, not malicious, but you must ensure those binaries/packages are installed securely.

Credentials

The only secret the code uses is an OpenRouter API key (OPENROUTER_KEY or --api-key), which is proportional to the task. However, registry metadata did not declare this required env var; the SKILL.md and scripts do require it — verify and provide only an appropriate API key.

Persistence & Privilege

The skill is not always-enabled, does not request elevated privileges, and does not attempt to modify other skills or system-wide configs.

Assessment

This skill appears to be what it says: it uploads images you explicitly provide (or generates images) to OpenRouter using the provided API key. Before installing, check/consider: 1) Provide only an OpenRouter API key (use a dedicated or limited key if possible). 2) Don’t pass sensitive images you wouldn’t want uploaded — any file you point at --input-image will be read and sent as a base64 data URL to openrouter.ai. 3) Ensure the 'uv' CLI and Python packages (requests, pillow) are available in your environment; the registry metadata omits these requirements. 4) If you want extra caution, run the scripts locally in a controlled environment first (with non-sensitive images) to confirm behavior. If you need me to, I can point out exactly where the key is read and where the upload happens in the code.

Nano Banana Pro Image Generation & Editing

Generate new images or edit existing ones using OpenRouter (model: google/gemini-3-pro-image-preview).

Usage

Run the script using absolute path:

Generate new image:

uv run /path/to/this/skill/scripts/generate_image.py --prompt "your image description" --filename "output-name.png" [--resolution 1K|2K|4K] [--api-key KEY]

Edit existing image:

uv run /path/to/this/skill/scripts/generate_image.py --prompt "editing instructions" --filename "output-name.png" --input-image "path/to/input.png" [--resolution 1K|2K|4K] [--api-key KEY]

Custom output directory:

uv run /path/to/this/skill/scripts/generate_image.py --prompt "your image description" --filename "output-name.png" --output-dir "/custom/path"

Output Location:

• Default: Images are saved to ./output_images/ (relative to this skill's root directory)
• Custom: Use --output-dir to specify a different directory
• The script will create the output directory if it doesn't exist

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 /path/to/this/skill/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 /path/to/this/skill/scripts/generate_image.py --prompt "<final prompt>" --filename "yyyy-mm-dd-hh-mm-ss-final.png" --resolution 4K

Resolution Options

The OpenRouter 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. OPENROUTER_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 \"$OPENROUTER_KEY\" (or pass --api-key)
  • If editing: test -f \"path/to/input.png\"

• Common failures:

  • Error: No API key provided. → set OPENROUTER_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)
• 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 /path/to/this/skill/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 /path/to/this/skill/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