An integration skill that brings StepFun high-speed reasoning and multimodal AI models to your local environment via the OpenRouter API.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install stepfun-openrouter
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
Copy this prompt to OpenClaw to install it automatically.
Help me install stepfun-openrouter using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Get the raw skill files in a ZIP archive.
This skill provides a seamless connection between the StepFun AI ecosystem and your local workspace using the OpenRouter API. By incorporating this into your Openclaw Skills library, you gain access to the Step-3.5 Flash and Step-3 models, which are renowned for their 'visible reasoning' capabilities—allowing you to see the logical steps the AI takes before reaching a conclusion.
Designed for speed and efficiency, the integration supports a free tier for developers looking to prototype quickly. It serves as a bridge for developers who need high-performance LLMs without the overhead of managing multiple proprietary API integrations, centralizing StepFun access through a unified interface.
To get started, first ensure you have an API key from the OpenRouter dashboard. Then, install the skill and set your credentials:
clawhub install stepfun-openrouter
export OPENROUTER_API_KEY="your-key-here"
You can verify the setup by running a simple query:
stepfun-cli "Verify installation"
The skill manages its configuration and model interactions through environment variables and standard CLI arguments. The following table outlines the primary data inputs:
| Parameter | Description | Required |
|---|---|---|
OPENROUTER_API_KEY |
Your unique authentication key from OpenRouter | Yes |
stepfun/step-3.5-flash:free |
The default free-tier model identifier | No |
--reasoning |
A flag to enable the display of AI thinking steps | No |
| Multimodal Input | Support for image paths or URLs for vision tasks | No |
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