快速判断
使用 Nano Banana Pro (Gemini 3 Pro Image) 生成或编辑图像。支持文生图、图生图及 1K/2K/4K 分辨率,适用于图像创建、修改及编辑请求,使用 --input-image 指定输入图像。
适合任务
- 按 SkillHub 收录说明复用成熟任务流程。
- 通过下载包离线阅读完整 Skill 内容。
- 结合热度指标优先评估常用 Skill。
输入与输出
输入:任务目标、上下文材料、文件路径、约束条件或需要处理的内容。
输出:按 Skill 说明生成的文档、代码、检查结果、计划、建议或操作步骤。
示例任务
- 使用 Nano Banana Pro 帮我处理当前任务,并说明需要准备哪些输入。
- 根据 Nano Banana Pro 的说明,先列出使用前的安全检查项。
安装方式
- 下载本站提供的 Skill ZIP 并解压。
- 把解压后的 Skill 目录放入当前 AI 工具支持的
skills目录。 - 如需在线查看原始内容,可打开 GitHub 的
SKILL.md。
风险边界
SkillHub 提供了源站安全报告入口,但本站不替代人工审查。使用前仍需检查权限、外部依赖和敏感数据边界。
SKILL.md 文档介绍
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-imagefor 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:
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.→ setGEMINI_API_KEYor pass--api-keyError loading input image:→ wrong path / unreadable file; verify--input-imagepoints 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 ~/.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 4KEdit 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