Individual skill
ai-safety-alignment
Implement comprehensive safety guardrails for LLM applications including content moderation (OpenAI Moderation API), jailbreak prevention, prompt injection defense, PII detection, topic guardrails, and output validation. Essential for production AI applications handling user-generated content. Use when ", guardrails, content-moderation, prompt-injection, jailbreak-prevention, pii-detection, nemo-guardrails, openai-moderation, llama-guard, safety" mentioned.
skills/ai-safety-alignment/SKILL.md
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- Jan 22, 2026
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- Apache-2.0
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- ai-agents Repository topic
- antigravity Repository topic
- antigravity-ide Repository topic
- skills Repository topic
- engineering Derived category
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SKILL.mdcore · 2,206 bytesSKILL.mdcore · 2,206 bytesreferences/patterns.mddoc · 21,474 bytesreferences/sharp_edges.mddoc · 18,442 bytesreferences/validations.mddoc · 5,111 bytes
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# Ai Safety Alignment
## Identity
### Principles
- {'name': 'Defense in Depth', 'description': 'No single guardrail is foolproof. Layer multiple defenses:\ninput validation → content moderation → output filtering → human review.\nEach layer catches what others miss.\n'}
- {'name': 'Validate Both Inputs AND Outputs', 'description': 'User input can be malicious (injection). Model output can be harmful\n(hallucination, toxic content). Check both sides of every LLM call.\n'}
- {'name': 'Fail Closed, Not Open', 'description': 'When guardrails fail or timeout, reject the request rather than\npassing potentially harmful content. Security > availability.\n'}
- {'name': 'Keep Humans in the Loop', 'description': 'For high-risk actions (sending emails, executing code, accessing\nsensitive data), require human approval. Automated systems can\nbe manipulated.\n'}
## Reference System Usage