據 AlphaMoat 統計,截至 2026-09,Nano Banana Pro (Morfeo) 累計下載 2,528 次、獲 3 個星標,在全部 5,078 個 AI 技能中排名第 4,078 位,在「設計創意」分類(512 個)中排名第 395 位。
| 平台 | 累計安裝 | 累計下載 | 星標 | 評論 |
|---|---|---|---|---|
| ClawHub ↗ | 70 | 2204 | 3 | - |
| SkillHub ↗ | 175 | 2528 | 3 | — |
各平台的計數口徑不同,統計時間不一致。
主文描述從文字提示生成圖片,以及基於輸入或參考圖片進行編輯,並說明可配置輸出解析度。提示詞和選定圖片會傳送給 Google 處理;提交前檢查圖片授權、隱私和目標輸出,不把來源指令當作執行要求。
資料釋出於 2026-10-27
以下是根據技能文件生成的示例,不代表實際執行結果。
2026-09 起統計方法調整:同名技能按作者分別統計,並覆蓋全部技能。圖中虛線為調整前的月份,與之後的資料不直接比較,也不計算跨越調整的增長。
| 月份 | 累計下載 | 環比 | 星標 |
|---|---|---|---|
| 2026-09 | 2528 | — | 3 |
| 2026-08 | 2234 | +6.7% | 3 |
| 2026-07 | 2094 | +12.0% | 3 |
| 2026-06 | 1870 | +7.8% | 3 |
| 2026-05 | 1734 | — | 3 |
| 2026-03 | 1477 | — | 3 |
以下是作者釋出的原始檔案,按純文字顯示,本站未做修改或稽核;其中的連結不可點選,命令請核實後再執行。抓取於 2026-10-23。
--- name: nano-banana-pro description: Generate and edit images using Google's Nano Banana Pro (Gemini 3 Pro Image) API. Use when the user asks to generate, create, edit, modify, change, alter, or update images. Also use when user references an existing image file and asks to modify it in any way (e.g., "modify this image", "change the background", "replace X with Y"). Supports both text-to-image generation and image-to-image editing with configurable resolution (1K default, 2K, or 4K for high resolution). DO NOT read the image file first - use this skill directly with the --input-image parameter. --- # Nano Banana Pro Image Generation & Editing Generate new images or edit existing ones using Google's Nano Banana Pro API (Gemini 3 Pro Image). ## API Technical Specification
### Endpoints & Authentication
**Google AI Studio (Public Preview):**
```
POST https://generativelanguage.googleapis.com/v1beta/models/gemini-3-pro-image-preview:generateContent?key=${API_KEY}
```
**Vertex AI (Enterprise):**
```
POST https://${REGION}-aiplatform.googleapis.com/v1/projects/${PROJECT_ID}/locations/${REGION}/publishers/google/models/gemini-3-pro-image-preview:predict
```
### Model IDs
- API: `gemini-3-pro-image-preview`
- SDK interno: `nanobanana-pro-001`
### Parameters
| Parameter | Values | Description |
|-----------|--------|-------------|
| `aspect_ratio` | `1:1`, `4:3`, `3:4`, `16:9`, `9:16` | Output aspect ratio |
| `output_mime_type` | `image/png`, `image/jpeg` | Output format |
| `reference_images` | Array (max 14) | Reference images for consistency |
| `reference_type` | `CHARACTER`, `STYLE`, `SUBJECT` | How to use reference |
| `person_generation` | `ALLOW_ADULT`, `DONT_ALLOW`, `FILTER_SENSITIVE` | Person generation policy |
| `image_size` | `1K`, `2K`, `4K` | Output resolution |
### Reference Types
- **STYLE**: Transfer visual style, color palette, mood from reference
- **CHARACTER**: Maintain facial features, traits consistency across images
- **SUBJECT**: Keep the subject/product consistent (use for product photography!)
### Advanced Capabilities
- **Text Rendering**: Native text rendering without spelling errors
- **In-context Editing**: Send existing image + modification prompt (automatic in-painting)
- **High Resolution**: Native upscale to 4K via `upscale: true`
## Usage
Run the script using absolute path (do NOT cd to skill directory first):
**Generate new image:**
```bash
uv run ~/.clawdbot/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:**
```bash
uv run ~/.clawdbot/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]
```
**With reference image (product/style/character consistency):**
```bash
uv run ~/.clawdbot/skills/nano-banana-pro/scripts/generate_image.py \
--prompt "your description" \
--filename "output-name.png" \
--reference-image "path/to/reference.jpg" \
--reference-type SUBJECT|STYLE|CHARACTER \
[--resolution 1K|2K|4K]
```
**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
- **1K** (default) - ~1024px resolution
- **2K** - ~2048px resolution (recommended for most uses)
- **4K** - ~4096px resolution (high quality)
Map user requests:
- No mention → `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
2. `GEMINI_API_KEY` environment variable
## Filename Generation
Format: `{timestamp}-{descriptive-name}.png`
- Timestamp: `yyyy-mm-dd-hh-mm-ss` (24-hour format)
- Name: Descriptive lowercase with hyphens
Examples:
- `2025-11-23-14-23-05-japanese-garden.png`
- `2025-11-23-15-30-12-sunset-mountains.png`
---
# Prompt Engineering Framework
You are an expert Prompt Engineer specializing in Nano Banana Pro. Transform basic user ideas and reference images into high-fidelity, descriptive prompts.
## 1. Input Analysis
When provided with a user idea and reference images, evaluate:
- **Subject Matter**: Identify primary actors, objects, or focal points
- **Reference Utility**: Determine if image provides composition (layout), style (aesthetic/texture), or character (specific features)
- **Text Requirements**: Note any specific text to render within the image
## 2. Prompt Construction Framework
Structure optimized prompts using this hierarchy:
### Core Subject & Action
Clear description of "who" or "what" is doing "what."
### Style & Medium
Specify artistic medium:
- Hyper-realistic photography
- Oil painting
- 3D render
- Minimalist vector
- Commercial food photography
- Editorial style
### Reference Integration
Explicitly instruct on how to use uploaded images:
> "Retain the product packaging from the reference image as the hero element"
> "Apply the warm lighting aesthetic from Reference A"
### Technical Details
**Lighting:**
- Cinematic rim lighting
- Soft diffused sunlight
- Harsh strobes
- Warm tungsten lighting
- Golden hour warmth
**Composition:**
- Wide-angle shot
- Macro detail
- Bird's-eye view
- Shallow depth of field
- Product as hero element
**Color Theory:**
- Monochromatic blue
- High-contrast complementary
- Warm amber tones
- Dark moody palette
**Text Rendering:**
Use double quotes for specific text:
> "The word 'FUTURE' written in bold, brushed-metal 3D lettering across the center"
## 3. Optimization Rules
### DO:
- Use descriptive positive language
- Expand vague terms ("cool" → "iridescent", "pretty" → "ethereal", "realistic" → "photorealistic 8k texture")
- Maintain consistency with reference images
- Use powerful adjectives for mood ("gritty," "serene," "industrial," "whimsical")
- Specify "8k texture detail" or "8k photorealistic detail" for quality
### DON'T:
- Use negative prompts (say what you want, not what you don't)
- Contradict visual data in reference images
- Use vague terms without expansion
## 4. Product Photography Best Practices
When generating images with products as protagonists:
1. **Always use `--reference-type SUBJECT`** to maintain product consistency
2. **Describe the product prominently** in the prompt:
> "Milkaut Crematto container with blue label and red lid prominently displayed"
3. **Position product as hero element:**
> "the product container as co-star product placement"
> "product container in sharp focus"
4. **Include product in scene naturally:**
> "positioned next to", "beside", "prominently arranged"
### Example Product Photography Prompt:
```
Hyper-realistic commercial food photography with a [PRODUCT NAME] container
prominently displayed next to [FOOD ITEM], [food description],
[setting/background], [lighting style], the [product] as hero element,
8k photorealistic detail
```
## 5. Output Format
Provide the optimized prompt in English, without additional commentary.
---
## Examples
### Product + Food Scene
```bash
uv run ~/.clawdbot/skills/nano-banana-pro/scripts/generate_image.py \
--prompt "Hyper-realistic commercial food photography with a Milkaut Crematto container prominently displayed next to a gourmet double smash burger with perfectly melted cheddar cheese cascading down juicy beef patties, artisan brioche bun, wisps of steam rising, dark moody background with dramatic rim lighting, the cream cheese container as hero product placement, 8k texture detail" \
--filename "2026-01-28-product-burger.png" \
--reference-image "product-photo.jpg" \
--reference-type SUBJECT \
--resolution 2K
```
### Style Transfer
```bash
uv run ~/.clawdbot/skills/nano-banana-pro/scripts/generate_image.py \
--prompt "Using the warm golden hour aesthetic from the reference, create a serene Japanese garden with cherry blossoms, koi pond reflecting soft pink petals, traditional wooden bridge, ethereal morning mist, 8k photorealistic detail" \
--filename "2026-01-28-japanese-garden.png" \
--reference-image "style-reference.jpg" \
--reference-type STYLE \
--resolution 2K
```
### Image Editing
```bash
uv run ~/.clawdbot/skills/nano-banana-pro/scripts/generate_image.py \
--prompt "Change the background to a dramatic sunset over mountains, maintain the subject in sharp focus" \
--filename "2026-01-28-edited-sunset.png" \
--input-image "original.jpg" \
--resolution 2K
```
ContextWeave 架構圖一鍵生成
用 Nano Banana Pro 生成或編輯圖片的指令碼技能。
用 whisper 命令列工具在本機將音訊轉成文字或進行翻譯。
透過 MCP 服務生成與編輯圖表的技能。
面向介面設計的思路與落地建議技能,覆蓋佈局、互動流程、設計令牌與前端改動。
面向多家影片模型 API 的 AI 影片生成與編排技能。
用 ffmpeg 從影片裡取出畫面幀,或生成便於快速檢視的縮圖。
用本地 Whisper 把音訊檔案轉成文字,模型下載完成後可完全離線執行。
資料月份:2026-09 · 下載/星標/安裝數聚合自公開技能註冊庫(ClawHub、SkillHub),按月更新。口徑說明見資料方法。