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clarity-gate

Pre-ingestion verification for epistemic quality in RAG systems with 9-point verification and Two-Round HITL workflow

Author

@sickn33

Category

AI Skill Development

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Clarity Gate — Pre-ingest Cognitive Quality Verification Tool for RAG Systems

Skill Overview

Clarity Gate is an open-source pre-ingest verification system designed to ensure documents entering a RAG knowledge base carry correct cognitive-quality markings, preventing LLMs from presenting unverified guesses as confident hallucinations.

Use Cases

  • RAG corpus quality control: When your knowledge base contains draft documents, tickets, meeting notes, or user-provided content, Clarity Gate can automatically check and add missing uncertainty markers before documents are ingested.

  • Scalable HITL verification: When you need to go beyond spot-checking in human-in-the-loop (HITL) workflows, Clarity Gate intelligently splits verification requests into "data confirmation" and "ground-truth verification" rounds, focusing human attention on the statements that truly require verification.

  • Automated ingestion gateway: When you need to enforce quality standards automatically before document ingestion, ensuring statements are correctly classified as fact, assumption, or prediction, and requiring human verification when markers are missing.

    • Core Features

  • 9-point verification system: Covers cognitive-quality checks (hypothesis vs. fact tagging, enforcement of uncertainty markers, hypothesis visibility, verification of authoritatively appearing data) and data-quality checks (data consistency, implicit causality, mislabeling of future states, temporal coherence, routing of externally verifiable claims).

  • Two-round HITL verification workflow: Intelligently routes statements requiring human verification to Round A (quick confirmation for statements with found sources) and Round B (statements needing true verification), optimizing human attention allocation.

  • Verify and Annotate modes: Verify mode generates a verification report and initiates a HITL workflow; Annotate mode directly produces a repaired Clarity-Gated Document (CGD) that can be safely ingested into a RAG system.

    • FAQ

    How is Clarity Gate different from traditional fact-checking tools?

    Traditional fact-checking tools focus on whether content matches sources (accuracy), whereas Clarity Gate focuses on whether a statement is properly qualified (cognitive quality). For example, treating "revenue is expected to reach 50 million" as a factual assertion might pass accuracy checks, but would fail cognitive-quality checks because a prediction is being presented as a fact. Clarity Gate fills the gap of enforcing cognitive constraints before ingestion.

    Can Clarity Gate automatically verify the truth of facts?

    No. Clarity Gate verifies form rather than veracity — it checks whether statements are properly marked as uncertain, but it cannot determine whether the statements themselves are true. This is why the two-round HITL verification is mandatory — LLMs can fabricate facts and add source markers to pass checks. HITL ensures real human verification before statements enter the knowledge base.

    How do I use Clarity Gate in Claude?

    There are several ways: 1) upload the dist/clarity-gate.skill file in the claude.ai web app; 2) use the same skill file in Claude Desktop; 3) when using Claude Code, clone the repository — it will auto-detect skills in the .claude/skills/ directory. To run it, simply say "Run clarity gate on this document" to start verification.