Tencent SkillHub · AI

Nano Banana Pro

Generate/edit images with Nano Banana Pro (Gemini 3 Pro Image). Use for image create/modify requests incl. edits. Supports text-to-image + image-to-image; 1K/2K/4K; use --input-image.

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Generate/edit images with Nano Banana Pro (Gemini 3 Pro Image). Use for image create/modify requests incl. edits. Supports text-to-image + image-to-image; 1K/2K/4K; use --input-image.

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Install for OpenClaw

Quick setup

Download the package from Yavira.
Extract the archive and review SKILL.md first.
Import or place the package into your OpenClaw setup.

Requirements

Target platform: OpenClaw
Install method: Manual import
Extraction: Extract archive
Prerequisites: OpenClaw
Primary doc: SKILL.md

Package facts

Download mode: Yavira redirect
Package format: ZIP package
Source platform: Tencent SkillHub
What's included: SKILL.md, scripts/generate_image.py

Validation

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Trust & source

Release facts

Source: Tencent SkillHub
Verification: Indexed source record
Version: 1.0.1

Provenance

Publisher: steipete
Source page: View original listing
Canonical URL: Open canonical page

Documentation

ClawHub primary doc Primary doc: SKILL.md 12 sections Open source page

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 "<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 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: --api-key argument (use if user provided key in chat) 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: Check if they provide an image path or reference an image in the current directory Use --input-image parameter with the path to the image The prompt should contain editing instructions (e.g., "make the sky more dramatic", "remove the person", "change to cartoon style") 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 ~/.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

Category context

Agent frameworks, memory systems, reasoning layers, and model-native orchestration.

Source: Tencent SkillHub

Largest current source with strong distribution and engagement signals.

Package contents

Included in package

1 Docs1 Scripts

SKILL.md Primary doc
scripts/generate_image.py Scripts