vLLM

Use this skill when the user asks how to install, use, serve, configure, troubleshoot, or optimize vLLM, the high-throughput inference and serving engine for LLMs. This root skill is a router; open the focused sub-skill before writing substantial commands or code.

First Checks

• Confirm whether the user wants in-process Python inference or an OpenAI-compatible HTTP server.
• Ask for the model identifier/path, hardware target, and whether model downloads, remote code, local media, or credentials are allowed before running live model commands.
• Treat GPU execution, model downloads, multi-node launches, and benchmark runs as environment-gated; prefer help/static checks until the user confirms resources.
• Use references/repo-provenance.md to check whether this skill is aligned with the current vLLM checkout.
• Use references/troubleshooting.md for cross-cutting install/import/backend triage before routing to workflow-specific troubleshooting.

Route by Workflow