据 AlphaMoat 统计,截至 2026-09,Mulerouter 累计下载 1,938 次、获 0 个星标,在全部 5,078 个 AI 技能中排名第 4,469 位,在「设计创意」分类(512 个)中排名第 448 位。
| 平台 | 累计安装 | 累计下载 | 星标 | 评论 |
|---|---|---|---|---|
| ClawHub ↗ | 48 | 1,710 | - | - |
| SkillHub ↗ | 129 | 1,938 | - | — |
各平台的计数口径不同,统计时间不一致。
该技能提供文本生成图像、图像编辑、文本生成视频、图像生成视频及视频编辑流程,并通过已配置的 API 服务提交请求。提示词、媒体输入和 API 密钥会发送到所选服务或自定义端点;只使用可信端点,不提交敏感素材,避免在代码库保存密钥,并在上传前核实本地图像路径。 需要 Python 3.10 或更高版本、uv 或 pip,以及网络访问。
资料发布于 2026-10-29
以下是根据技能文档生成的示例,不代表实际运行结果。
2026-09 起统计方法调整:同名技能按作者分别统计,并覆盖全部技能。图中虚线为调整前的月份,与之后的数据不直接比较,也不计算跨越调整的增长。
| 月份 | 累计下载 | 环比 | 星标 |
|---|---|---|---|
| 2026-09 | 1,938 | — | - |
| 2026-08 | 1,675 | +8.8% | - |
| 2026-07 | 1,540 | +18.1% | - |
| 2026-06 | 1,304 | +10.8% | - |
| 2026-05 | 1,177 | — | - |
| 2026-03 | 914 | — | - |
以下是作者发布的原始文件,按纯文本显示,本站未做修改或审核;其中的链接不可点击,命令请核实后再运行。抓取于 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 架构图一键生成
用 Nano Banana Pro 生成或编辑图片的脚本技能。
用 whisper 命令行在本地把音频转写成文字或做翻译的技能。
通过 MCP 服务生成与编辑图表的技能。
面向界面设计的思路与落地建议技能,覆盖布局、交互流程、设计令牌与前端改动。
面向多家视频模型 API 的 AI 视频生成与编排技能。
用 ffmpeg 从视频里取出画面帧,或生成便于快速查看的缩略图。
用本地 Whisper 把音频文件转成文字,模型下载完成后可完全离线运行。
数据月份:2026-09 · 下载/星标/安装数聚合自公开技能注册库(ClawHub、SkillHub),按月更新。口径说明见数据方法。