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在 OpenClaw 中安装
/install free-ride-1-0-4
功能描述
Manages free AI models from OpenRouter for OpenClaw. Automatically ranks models by quality, configures fallbacks for rate-limit handling, and updates opencla...
使用说明 (SKILL.md)
FreeRide - Free AI for OpenClaw
What This Skill Does
Configures OpenClaw to use free AI models from OpenRouter. Sets the best free model as primary, adds ranked fallbacks so rate limits don't interrupt the user, and preserves existing config.
Prerequisites
Before running any FreeRide command, ensure:
-
OPENROUTER_API_KEY is set. Check with
echo $OPENROUTER_API_KEY. If empty, the user must get a free key at https://openrouter.ai/keys and set it:export OPENROUTER_API_KEY="sk-or-v1-..." # Or persist it: openclaw config set env.OPENROUTER_API_KEY "sk-or-v1-..." -
The
freerideCLI is installed. Check withwhich freeride. If not found:cd ~/.openclaw/workspace/skills/free-ride pip install -e .
Primary Workflow
When the user wants free AI, run these steps in order:
# Step 1: Configure best free model + fallbacks
freeride auto
# Step 2: Restart gateway so OpenClaw picks up the changes
openclaw gateway restart
That's it. The user now has free AI with automatic fallback switching.
Verify by telling the user to send /status to check the active model.
Commands Reference
| Command | When to use it |
|---|---|
freeride auto |
User wants free AI set up (most common) |
freeride auto -f |
User wants fallbacks but wants to keep their current primary model |
freeride auto -c 10 |
User wants more fallbacks (default is 5) |
freeride list |
User wants to see available free models |
freeride list -n 30 |
User wants to see all free models |
freeride switch \x3Cmodel> |
User wants a specific model (e.g. freeride switch qwen3-coder) |
freeride switch \x3Cmodel> -f |
Add specific model as fallback only |
freeride status |
Check current FreeRide configuration |
freeride fallbacks |
Update only the fallback models |
freeride refresh |
Force refresh the cached model list |
After any command that changes config, always run openclaw gateway restart.
What It Writes to Config
FreeRide updates only these keys in ~/.openclaw/openclaw.json:
agents.defaults.model.primary— e.g.openrouter/qwen/qwen3-coder:freeagents.defaults.model.fallbacks— e.g.["openrouter/free", "nvidia/nemotron:free", ...]agents.defaults.models— allowlist so/modelcommand shows the free models
Everything else (gateway, channels, plugins, env, customInstructions, named agents) is preserved.
The first fallback is always openrouter/free — OpenRouter's smart router that auto-picks the best available model based on the request.
Watcher (Optional)
For auto-rotation when rate limited, the user can run:
freeride-watcher --daemon # Continuous monitoring
freeride-watcher --rotate # Force rotate now
freeride-watcher --status # Check rotation history
Troubleshooting
| Problem | Fix |
|---|---|
freeride: command not found |
cd ~/.openclaw/workspace/skills/free-ride && pip install -e . |
OPENROUTER_API_KEY not set |
User needs a key from https://openrouter.ai/keys |
| Changes not taking effect | openclaw gateway restart then /new for fresh session |
| Agent shows 0 tokens | Check freeride status — primary should be openrouter/\x3Cprovider>/\x3Cmodel>:free |
安全使用建议
This skill's code appears to implement what it claims (fetching free models from OpenRouter, ranking them, and updating your OpenClaw config), but there are a few red flags to check before installing:
- Confirm the OPENROUTER_API_KEY requirement: SKILL.md and skill.json require it despite header metadata saying 'none'. Only provide an API key you trust and prefer one scoped/limited if possible. The code reads the key from your environment or from ~/.openclaw/openclaw.json.
- Inspect the packaged files (main.py, watcher.py, setup.py, README, skill.json) locally before running pip install -e . — installing executes local code on your machine.
- Backup ~/.openclaw/openclaw.json before running FreeRide so you can restore configuration if changes are unwanted.
- The watcher daemon will make outbound calls to openrouter.ai and will write state and cache files under ~/.openclaw; if you want to avoid background activity, run only the CLI commands or run the watcher in a controlled environment (or as a one-shot cron job) rather than a continuous daemon.
- Verify the skill's provenance: the manifest includes differing owner IDs and the package's 'install' path references the local workspace. If you care about supply-chain trust, find the GitHub repository (skill.json points to a repo) and verify the source and publisher before trusting and installing.
Given the inconsistencies in metadata and packaging, proceed with caution: reasonable and expected behavior is present (verdict not 'benign'), but the metadata mismatches and local installation requirement mean you should manually review files and back up config before installing.
功能分析
Type: OpenClaw Skill
Name: free-ride-1-0-4
Version: 1.0.0
The FreeRide skill bundle is a legitimate utility designed to manage and rotate free AI models from OpenRouter for the OpenClaw platform. The core logic in main.py and watcher.py fetches model metadata from OpenRouter's official API, ranks them by quality, and updates the user's openclaw.json configuration to automate model switching and rate-limit handling. While the skill requires write access to the OpenClaw configuration file and makes network requests using the user's API key, these actions are strictly aligned with its stated purpose and lack any indicators of malicious intent, data exfiltration, or unauthorized execution.
能力评估
Purpose & Capability
The skill's name/description (manage OpenRouter free models) aligns with the included Python code that calls openrouter.ai and updates ~/.openclaw/openclaw.json. However the registry/header metadata published with this evaluation is inconsistent: the top-level 'Requirements' block said 'Required env vars: none' while SKILL.md and skill.json clearly require OPENROUTER_API_KEY. The skill also contains install packaging (setup.py, entry points) despite the registry saying 'No install spec — this is an instruction-only skill.' These metadata mismatches reduce trust and should be resolved before install.
Instruction Scope
SKILL.md instructs the agent/user to set OPENROUTER_API_KEY, install the local freeride package (pip install -e . in ~/.openclaw/workspace/skills/free-ride), run freeride commands, and restart the OpenClaw gateway. Those actions are within the stated purpose (fetching models, ranking them, and writing OpenClaw config). The instructions ask the agent to read and write the user's OpenClaw config (~/.openclaw/openclaw.json) and to run the local CLI — expected for this functionality. Note: SKILL.md advises using openclaw config set env... which would store the API key in OpenClaw config; ensure you accept that storage location.
Install Mechanism
There is no remote binary download; installation is a local pip install of the packaged code (setup.py). That's a low-to-moderate risk pattern but the registry text earlier incorrectly said 'instruction-only'. The skill.json includes an 'install' recommendation (npx clawhub... && pip install -e .). No external archives or downloads from untrusted URLs are used in the code. Still, pip installing local code executes Python code on your machine — review files before installing.
Credentials
The only credential the code actually needs is an OpenRouter API key (OPENROUTER_API_KEY), which is proportionate to the described purpose. However, the manifest presented to you earlier claimed no required env vars while skill.json and SKILL.md require OPENROUTER_API_KEY. That mismatch should be corrected. The code reads the key from the environment or from ~/.openclaw/openclaw.json; it does not appear to request unrelated credentials.
Persistence & Privilege
The skill writes cache and state files under ~/.openclaw (cache, .freeride-watcher-state.json) and updates ~/.openclaw/openclaw.json to set primary and fallback models. 'always' is false and autonomous invocation is allowed (default). Writing the OpenClaw config and state files is expected for this feature and is scoped to the user's OpenClaw directory; it does not request system-wide or other skills' credentials.
如何使用
- 确保已安装 OpenClaw（本地或 Docker 部署）
- 在对话框中输入安装命令：
/install free-ride-1-0-4 - 安装完成后，直接呼叫该 Skill 的名称或使用
/free-ride-1-0-4触发 - 根据 Skill 的参数说明提供必要输入，即可获得结构化输出
版本历史
v1.0.0
FreeRide 1.0.0 initial release
- Enables OpenClaw to use free AI models from OpenRouter, with ranked fallbacks for rate-limit resilience.
- Automatically detects and sets up the best free model as primary and manages fallback switching.
- Preserves user’s OpenClaw config except for necessary model keys.
- Provides CLI commands to list, switch, and manage free models with clear usage instructions.
- Includes troubleshooting guidance and optional watcher for automatic model rotation.
- Requires user to set their OPENROUTER_API_KEY and install the freeride CLI.
元数据
常见问题
Free Ride 1.0.4 是什么？
Manages free AI models from OpenRouter for OpenClaw. Automatically ranks models by quality, configures fallbacks for rate-limit handling, and updates opencla... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 318 次。
如何安装 Free Ride 1.0.4？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install free-ride-1-0-4」即可一键安装，无需额外配置。
Free Ride 1.0.4 是免费的吗？
是的，Free Ride 1.0.4 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。
Free Ride 1.0.4 支持哪些平台？
Free Ride 1.0.4 跨平台运行，可在任意部署了 OpenClaw / Claude Code 的环境中使用（cross-platform）。
谁开发了 Free Ride 1.0.4？
由 Taron M.（@taron-ai）开发并维护，当前版本 v1.0.0。
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