---
title: ToolRouter — Agent Use Case Guide
description: Step-by-step guide for completing a task with a specific AI agent using ToolRouter.
url: https://toolrouter.com/tools/similar-movies/use-cases/blend-several-favorite-movies-into-one-shortlist/openclaw
---
# How to Blend Movie Taste with OpenClaw

OpenClaw is the best fit when multi-seed recommendation runs need to stay normalized across many briefs. Use `blend_taste` for batch-style curation where the same schema should work for every taste profile.

## Setup

openclaw mcp add toolrouter -- npx -y toolrouter-mcp

## Steps

1. Connect ToolRouter in OpenClaw: openclaw mcp add toolrouter -- npx -y toolrouter-mcp
2. Define the seed movie bundle, the avoid list, and the output shape before running the blend.
3. Run `similar-movies.blend_taste` and keep the matched-seed and score fields consistent across briefs.
4. Review the shortlist, then rerun only when you need deeper pagination or a stricter quality floor.
5. Save the normalized output for repeatable recommendation workflows.

## Example Prompt

```
Use similar-movies to blend Zodiac, Gone Girl, and Knives Out into one shortlist, exclude Se7en, and keep the output normalized so I can compare recommendation bundles later.
```

## Tips

- Stay within two to five seeds or the blend becomes noisy.
- Keep thresholds consistent if the output will be compared across runs.
- Use the matched-seed field as the first sanity check on every recommendation.
