NVIDIA's runtime safety framework for LLM applications. Features jailbreak detection, input/output validation, fact-checking, hallucination detection, PII filtering, toxicity detection. Uses Colang 2.0 DSL for programmable rails. Production-ready, runs on T4 GPU.
8.1
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AI & LLM
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Excellent skill documentation for NeMo Guardrails with comprehensive coverage of safety mechanisms. The description clearly conveys capabilities (jailbreak detection, PII filtering, hallucination detection, etc.), enabling a CLI agent to invoke appropriately. Five detailed workflows cover common use cases with complete code examples. Task knowledge is strong with practical implementations of toxicity checking, fact verification, and integration patterns. Structure is clear with logical progression from quick start to advanced topics, though the single-file format works well here given the focused scope. Novelty is high - implementing production-grade LLM safety rails with multiple detection mechanisms, Colang 2.0 DSL programming, and sub-500ms latency overhead requires significant expertise and would consume many tokens for a CLI agent to replicate. Minor improvements could include more details on the referenced guides (colang-guide.md, integrations.md, performance.md), but per instructions these are assumed present and functional. The skill provides substantial value for production LLM safety implementation.
davila7
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