Agent skill · Media & Video

mulerouter

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 or Nano Banana.

majiayu000github.com/majiayu000GitHub ↗
claude-codeMIT
Install
npx skills add majiayu000/claude-skill-registry --skill mulerouter --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 2
SKILL.md size: 3 KB
Bundled scripts: none
Requires: Requires Python 3.10+, uv (or pip), and network access to api.mulerouter.ai or api.mulerun.com
Path: skills/ai-llm/mulerouter/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 534
Language: HTML

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# 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_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** ```bash export MULEROUTER_SITE="mulerun" # or "mulerouter" export MULEROUTER_API_KEY="your-api-key" ``` **Option B: Create .env file** Create `.env` in the current working directory: ```env MULEROUTER_SITE=mulerun MULEROUTER_API_KEY=your-api-key ``` **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

What's inside
Steps it walks through
  1. Configuration Check
  2. Step 1: Check for existing configuration
  3. Step 2: Configure if needed
  4. Step 3: Using uv to run scripts
  5. Quick Start
  6. 1. List available models
  7. 2. Check model parameters
  8. 3. Generate content
  9. Workflow
  10. Tips
  11. References
Ships with 1 file
  • metadata.json
Commands it runs
Check environment variables
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"
export MULEROUTER_SITE="mulerun"    # or "mulerouter"
export MULEROUTER_API_KEY="your-api-key"
uv run python scripts/list_models.py
uv run python models/alibaba/wan2.6-t2v/generation.py --list-params
uv run python models/alibaba/wan2.6-t2v/generation.py --prompt "A cat walking through a garden"
More from claude-skill-registry
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About this skill
What does the mulerouter skill do?

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 or Nano Banana.

How do I install it?

Run `npx skills add majiayu000/claude-skill-registry --skill mulerouter --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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