Clarity Gate

소개

Clarity Gate is a rigorous verification protocol designed to safeguard RAG (Retrieval-Augmented Generation) systems by ensuring all ingested documents are properly qualified with uncertainty markers. Unlike traditional detection tools that merely identify existing hedges, Clarity Gate enforces the presence of qualifiers wherever they are epistemically required, effectively preventing AI models from mistaking assumptions or projections for established facts. By producing standardized Clarity-Gated Documents (CGD) and implementing a mandatory Human-In-The-Loop verification routing, it provides a structured framework for maintaining high-integrity knowledge bases in professional AI workflows.

주요 기능

• Compliance with Clarity Gate Format Specification v2.0 (CGD format)
• 12 GitHub stars
• Integrity verification via document SHA-256 hashing and YAML frontmatter state tracking
• Mandatory Human-In-The-Loop (HITL) two-round verification routing
• Automated enforcement of epistemic uncertainty markers and qualifiers
• Nine-point verification framework covering hypotheses, data consistency, and temporal coherence

사용 사례

• Auditing internal methodology papers for hidden assumptions and unverified claims
• Preparing technical documentation for ingestion into a RAG knowledge base
• Verifying project specifications and financial projections before AI analysis