Train AI agents for safe medical reasoning using reinforcement learning.
npx skills add https://github.com/surfiniaburger/med-safety-gym-v2 --skill med-safety-gym
Please help me install this Agent Skill. Skill: med-safety-gym Source: https://github.com/surfiniaburger/med-safety-gym-v2/tree/main Command: npx skills add https://github.com/surfiniaburger/med-safety-gym-v2 --skill med-safety-gym
This Skill trains AI agents to provide safe and reliable medical advice by strictly adhering to provided clinical context and avoiding hallucinations.
Use the med-safety-gym skill to evaluate your AI agent's response to a medical question.
High-intent search queries and answers about installing and using this skill.
LLM evaluation for medical AI is done by enforcing contextual grounding, ensuring answers are based only on provided clinical data, and requiring the AI to cite evidence in a structured XML format (with proof and answer tags) for auditability.
Yes, you can stop medical AI from hallucinating by applying a safety enforcement mechanism that trains the AI to refuse answering when clinical context is insufficient or conflicting, rewarding correct abstention rather than inventing facts.
Evaluating an LLM's response to a medical question is best done by checking its verifiable reasoning chain, which requires the AI to cite evidence from the provided clinical context using a structured XML output format for strict adherence and auditability.
Yes, the reinforcement learning framework penalizes hallucinations and rewards correct abstention from answering when information is insufficient or conflicting, ensuring the AI acts as a safe medical assistant.
Yes, you need FastAPI, Pydantic, and a Python environment with dependencies like openenv-core and uvicorn to run the framework and evaluate your AI agent's medical reasoning responses.
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