FreeRide automates the selection and configuration of free OpenRouter AI models for OpenClaw, ensuring cost-effective and resilient agent performance.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install freerid
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install freerid using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is FreeRide?
FreeRide is a specialized utility designed to bridge the gap between OpenClaw and the vast ecosystem of free AI models available via OpenRouter. By prioritizing high-quality free models and configuring robust fallback chains, it ensures that developers can run complex AI workflows without incurring high API costs. This tool is essential for users of Openclaw Skills who want to maximize uptime by automatically navigating rate limits through a tiered model architecture.
The skill seamlessly integrates with the OpenClaw configuration, preserving existing settings while optimizing the model selection process. By automating the update of the openclaw.json file, FreeRide removes the manual toil of tracking which free models are currently active or performant, making it a cornerstone for budget-conscious Openclaw Skills development.
FreeRide Use Cases
- Reducing operational costs by leveraging free AI endpoints via OpenRouter.
- Implementing automatic rate-limit handling to prevent workflow interruptions during long coding sessions.
- Discovering and ranking the latest high-performance free models for coding and general chat.
- Managing a dynamic list of model fallbacks for resilient Openclaw Skills performance.
How FreeRide Works
- Validates the OpenRouter API key and checks for existing OpenClaw configurations in the environment.
- Scans the OpenRouter API for currently available free-tier models and ranks them based on quality and availability.
- Updates the openclaw.json file to set the primary model and a sequence of ranked fallbacks.
- Triggers a restart of the OpenClaw gateway to apply the new model settings and refresh the model allowlist.
- Optionally runs a background watcher to monitor for rate limit triggers and rotate models in real-time.
FreeRide Setup
Ensure your OpenRouter API key is set in your environment:
export OPENROUTER_API_KEY="sk-or-v1-..."
# Or persist it via OpenClaw config:
openclaw config set env.OPENROUTER_API_KEY "sk-or-v1-..."
Install the FreeRide CLI tool from the local skill directory:
cd ~/.openclaw/workspace/skills/free-ride
pip install -e .
Run the auto-configuration and restart the gateway:
freeride auto
openclaw gateway restart
FreeRide Data Schema & Taxonomy
FreeRide specifically manages model-related keys within the ~/.openclaw/openclaw.json configuration file to ensure compatibility with other Openclaw Skills. It modifies the following structure:
| Key Path | Purpose | Example Value |
|---|---|---|
agents.defaults.model.primary |
Defines the main free model for all agents | openrouter/qwen/qwen3-coder:free |
agents.defaults.model.fallbacks |
An ordered list of models used if the primary hits a rate limit | ["openrouter/free", "google/gemma-2-9b-it:free"] |
agents.defaults.models |
The allowlist that populates the /model command in the UI | ["openrouter/free", "...:free"] |
FreeRide Advanced Features
- Continuous monitoring with
freeride-watcher --daemonto automatically rotate models upon detecting rate limits. - Granular control over the number of fallback models generated using the
-cflag. - The ability to update fallback models without changing the current primary model using
freeride auto -f. - Support for OpenRouter's smart routing via the
openrouter/freeendpoint, which is always prioritized in the fallback chain.
SKILL.md
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