validation-pipeline

What problem does it solve?

Building AI systems that meet stringent accuracy, reliability, and regulatory compliance (like FDA/EMA) is incredibly complex and error-prone. This Skill provides a comprehensive framework to construct multi-stage validation pipelines, ensuring zero-hallucination, verifiable citations, and high confidence in AI outputs.

Core Features & Use Cases

• Multi-Stage Validation: Implement pre-generation data quality checks, real-time confidence monitoring, and post-generation citation, hallucination, and consistency checks.
• Hallucination & Citation Detection: Automatically detect fabricated claims and verify that all information is accurately sourced.
• Confidence Scoring: Quantify AI output quality with multi-dimensional confidence scores for critical decision-making.
• Use Case: A healthcare AI system needs to provide clinical decision support with 99.9%+ accuracy. Use this Skill to build a validation pipeline that checks input data quality, ensures every claim is cited, detects any hallucination, and provides an audit trail for FDA compliance.

Quick Start

Use the validation-pipeline skill to detect hallucinations in 'response.json' using 'sources.json' with a 99.9% confidence threshold.