serving-llms-vllm
Serves LLMs with high throughput using vLLM's PagedAttention and continuous batching. Use when deploying production LLM APIs, optimizing inference latency/throughput, or serving models with limited GPU memory. Supports OpenAI-compatible endpoints, quantization (GPTQ/AWQ/FP8), and tensor parallelism. Also covers llama.cpp and SGLang (guides in references/).
84%
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Low
Low-risk findings worth noting
W012: Unverifiable external dependency detected (runtime URL that controls agent).
What this means
The skill fetches instructions or code from an external URL at runtime, and the fetched content directly controls the agent’s prompts or executes code. This dynamic dependency allows the external source to modify the agent’s behavior without any changes to the skill itself.
Why it was flagged
The referenced installation URL (https://flashinfer.ai/whl/cu121/torch2.4/) is a common/reputable unofficial wheel repository used at runtime/setup, meeting the operational dependency criteria for a medium-tier classification.
- Repository
OpenLAIR/dr-claw
- Revision
3456bb4
- Audited
- Security analysis
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