Agent skill · security · davila7
nemo-guardrails
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.
Why this skill is useful
Adds executable safety workflows and validation scripts that enhance LLM applications with runtime safety features not commonly available.
What it needs
Requires nemoguardrails installed locally. About 4k tokens when loaded. Last updated 2026-08-06. 30,138 stars on the source repository.
What this skill does
NeMo Guardrails - Programmable Safety for LLMs Quick start NeMo Guardrails adds programmable safety rails to LLM applications at runtime. Installation: Basic example (input validation): Common workflows Workflow 1: Jailbreak detection Detect prompt injection attempts: Workflow 2: Self-check input/output Validate both input and output: Workflow 3: Fact-checking with retrieval Verify factual claims: Workflow 4: PII detection with Presidio Filter sensitive information: Workflow 5: LlamaGuard integration Use Meta's moderation model: When to use vs alternatives Use NeMo Guardrails when: Need runtime safety checks Want programmable safety rules Need multiple safety mechanisms (jailbreak, hallucination, PII) Building production LLM applications Need low-latency filtering (runs on T4) Safety mechanisms: Jailbreak detection: Pattern matching + LLM Self-check I/O: LLM-based validation Fact-checking: Retrieval + verification Hallucination detection: Consistency checking PII filtering: Presidio integration Toxicity detection: ActiveFence integration Use alternatives instead: LlamaGuard: Standalone moderation model OpenAI Moderation API: Simple API-based filtering Perspective API: Google's toxicity detection Constitutional AI: Training-time safety Common issues Issue: False positives blocking valid queries Adjust threshold: Issue: High latency from multiple checks Parallelize checks: Issue: Hallucination detection misses errors Use stronger verification: Advanced topics Colang 2.0 DSL: See references/colang-guide.md for flow syntax, actions, variables, and advanced patterns. Integration guide: See references/integrations.md for LlamaGuard, Presidio, ActiveFence, and custom models. Performance optimization: See references/performance.md for latency reduction, caching, and batching strategies. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills davila7/safety-alignment-nemo-guardrails