hallucination-risk-reviewer
SolidReviews an AI-generated response or LLM application output for factual risks, hallucination patterns, and confidence calibration issues.
Install
Quality Score: 85/100
Skill Content
Details
- Author
- Notysoty
- Repository
- Notysoty/openagentskills
- Created
- 5 months ago
- Last Updated
- 6 days ago
- Language
- JavaScript
- License
- MIT
Similar Skills
Semantically similar based on skill content — not just same category
ai-llm-security-review
Use for AI/LLM security assessments, prompt injection, RAG security, agent/tool permissioning, model supply chain, LLM red teaming, AI governance, eval design, data leakage, jailbreak testing, and secure AI application review.
hallucination-evaluator
Detect and measure ungroundedness in LLM and RAG outputs — claims the source doesn't support — by decomposing answers into atomic claims and checking each for entailment, so you can quantify faithfulness and gate on it instead of eyeballing it. Use when a RAG/LLM feature makes confident wrong claims, before shipping anything that must be factual, or to add a groundedness gate to evals/CI.
detect-hallucinations
Use this to detect when an LLM is making things up, so you can flag or block confident-but-wrong answers before users see them. Trigger on "detect hallucinations", "is the model making this up", "flag unreliable answers", "hallucination check", "confidence scoring for LLM output", or hardening a RAG/QA system. Pick a method that matches whether you have reference context or not.