ModelReady

Start using a local or Hugging Face model instantly, directly from chat.

This skill appears to implement a local vLLM/OpenAI-compatible server manager, but inspect and take the following precautions before installing/using it: - Dependencies: the script requires python3 and the 'vllm' Python package (and any of vllm's GPU/runtime dependencies). The registry metadata did not declare python3 or vllm and the skill provides no install steps. Only proceed if you install and trust vllm yourself. - Network exposure: default host is 0.0.0.0 which binds to all interfaces and makes the endpoint reachable from other machines on the LAN. Set the host to 127.0.0.1 (use /modelready set_ip ip=127.0.0.1) or run behind a firewall if you want localhost-only access. - Authentication: the server started is OpenAI-compatible but unauthenticated by this wrapper. Do not start models with sensitive data or on a public network without adding access controls. - Files written: the skill writes ~/.model2skill/defaults.env, PID and log files. Review these files for any sensitive content and for persistence you may want to remove them on uninstall. - Input handling: the script accepts EXTRA args and passes them to vllm; be careful when using extra=... to avoid unintended behavior. If the author provided: (1) explicit dependency list (python3, vllm, required versions), (2) an install or dependency-check step, and (3) a safer default bind (127.0.0.1) or an option to require authentication, this assessment could be upgraded to 'benign'. As-is, the mismatches and default network exposure make the skill 'suspicious.'

Type: OpenClaw Skill Name: modelready Version: 1.0.0 The skill is classified as suspicious due to the `extra` parameter in `tool/modelready.sh`. This parameter allows arbitrary arguments to be passed directly to the `vllm.entrypoints.openai.api_server` Python command. While not direct arbitrary shell code execution, this broad capability could be abused to misconfigure the vLLM server, potentially leading to resource exhaustion, unintended information disclosure, or other undesirable behaviors depending on the specific arguments supported by vLLM, without clear malicious intent being demonstrated in the provided files.