據 AlphaMoat 統計,截至 2026-09,Mulerouter 累計下載 1,938 次、獲 0 個星標,在全部 5,078 個 AI 技能中排名第 4,469 位,在「設計創意」分類(512 個)中排名第 448 位。
| 平台 | 累計安裝 | 累計下載 | 星標 | 評論 |
|---|---|---|---|---|
| ClawHub ↗ | 48 | 1710 | - | - |
| SkillHub ↗ | 129 | 1938 | - | — |
各平台的計數口徑不同,統計時間不一致。
該技能提供文字生成圖像、圖像編輯、文字生成影片、圖像生成影片及影片編輯流程,並透過已配置的 API 服務提交請求。提示詞、媒體輸入和 API 金鑰會傳送到所選服務或自定義端點;只使用可信端點,不提交敏感素材,避免在程式碼庫儲存金鑰,並在上傳前核實本地圖像路徑。 需要 Python 3.10 或更高版本、uv 或 pip,以及網路訪問。
資料釋出於 2026-10-29
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 | 1938 | — | - |
| 2026-08 | 1675 | +8.8% | - |
| 2026-07 | 1540 | +18.1% | - |
| 2026-06 | 1304 | +10.8% | - |
| 2026-05 | 1177 | — | - |
| 2026-03 | 914 | — | - |
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: mulerouter description: Generates images and videos using MuleRouter or MuleRun multimodal APIs. Text-to-Image, Image-to-Image, Text-to-Video, Image-to-Video, video editing (VACE, keyframe interpolation). Use when the user wants to generate, edit, or transform images and videos using AI models like Wan2.6, Veo3, Nano Banana Pro, Sora2, Midjourney. compatibility: Requires Python 3.10+, uv (or pip), and network access to api.mulerouter.ai or api.mulerun.com --- # MuleRouter API Generate images and videos using MuleRouter or MuleRun multimodal APIs.
## Configuration Check
Before running any commands, verify the environment is configured:
### Step 1: Check for existing configuration
```bash
# Check environment variables
echo "MULEROUTER_BASE_URL: $MULEROUTER_BASE_URL"
echo "MULEROUTER_SITE: $MULEROUTER_SITE"
echo "MULEROUTER_API_KEY: ${MULEROUTER_API_KEY:+[SET]}"
# Check for .env file
ls -la .env 2>/dev/null || echo "No .env file found"
```
### Step 2: Configure if needed
**Option A: Environment variables with custom base URL (highest priority)**
```bash
export MULEROUTER_BASE_URL="https://api.mulerouter.ai" # or your custom API endpoint
export MULEROUTER_API_KEY="your-api-key"
```
**Option B: Environment variables with site (used if base URL not set)**
```bash
export MULEROUTER_SITE="mulerun" # or "mulerouter"
export MULEROUTER_API_KEY="your-api-key"
```
**Option C: Create .env file**
Create `.env` in the current working directory:
```env
# Option 1: Use custom base URL (takes priority over SITE)
MULEROUTER_BASE_URL=https://api.mulerouter.ai
MULEROUTER_API_KEY=your-api-key
# Option 2: Use site (if BASE_URL not set)
# MULEROUTER_SITE=mulerun
# MULEROUTER_API_KEY=your-api-key
```
**Note:** `MULEROUTER_BASE_URL` takes priority over `MULEROUTER_SITE`. If both are set, `MULEROUTER_BASE_URL` is used.
**Note:** The tool only reads `.env` from the current directory. Run scripts from the skill root (`skills/mulerouter-skills/`).
### Step 3: Using `uv` to run scripts
The skill uses `uv` for dependency management and execution. Make sure `uv` is installed and available in your PATH.
Run `uv sync` to install dependencies.
## Quick Start
### 1. List available models
```bash
uv run python scripts/list_models.py
```
### 2. Check model parameters
```bash
uv run python models/alibaba/wan2.6-t2v/generation.py --list-params
```
### 3. Generate content
**Text-to-Video:**
```bash
uv run python models/alibaba/wan2.6-t2v/generation.py --prompt "A cat walking through a garden"
```
**Text-to-Image:**
```bash
uv run python models/alibaba/wan2.6-t2i/generation.py --prompt "A serene mountain lake"
```
**Image-to-Video:**
```bash
uv run python models/alibaba/wan2.6-i2v/generation.py --prompt "Gentle zoom in" --image "https://example.com/photo.jpg" #remote image url
```
```bash
uv run python models/alibaba/wan2.6-i2v/generation.py --prompt "Gentle zoom in" --image "/path/to/local/image.png" #local image path
```
## Image Input
For image parameters (`--image`, `--images`, etc.), **prefer local file paths** over base64.
```bash
# Preferred: local file path (auto-converted to base64)
--image /tmp/photo.png
--images ["/tmp/photo.png"]
```
The skill automatically converts local file paths to base64 before sending to the API. This avoids command-line length limits that occur with raw base64 strings.
## Workflow
1. Check configuration: verify `MULEROUTER_BASE_URL` or `MULEROUTER_SITE`, and `MULEROUTER_API_KEY` are set
2. Install dependencies: run `uv sync`
3. Run `uv run python scripts/list_models.py` to discover available models
4. Run `uv run python models/<path>/<action>.py --list-params` to see parameters
5. Execute with appropriate parameters
6. Parse output URLs from results
## Tips
1. For an image generation model, a suggested timeout is 5 minutes.
2. For a video generation model, a suggested timeout is 15 minutes.
## References
- [REFERENCE.md](references/REFERENCE.md) - API configuration and CLI options
- [MODELS.md](references/MODELS.md) - Complete model specifications
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。