clarity-gate
Lets your agent check the quality of information before adding it to a knowledge system.
What it does
This system checks if documents are clear about what is fact and what is assumption before being used by other AIs. It marks uncertainties to prevent the AI from mistaking assumptions for facts.
When to use it
- ✓Before adding documents to an AI system that answers questions.
- ✓When you share documents with another AI.
- ✓When writing documents with predictions or hypotheses.
Example of what to ask your AI
“Check this document to ensure assumptions are clearly marked as uncertain.”
Want more? Open the sections below.
How to use
The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.
Skill link
Ready-to-paste message
How it works
The system looks for statements that could be mistaken for facts and ensures they are marked as uncertain. It doesn't check if the information is true, only if uncertainty is indicated.
Installation
Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.
In the terminal (Claude Code, Codex, Cursor), in your project folder:
npx skills add sickn33/agentic-awesome-skills --skill clarity-gateOr download just the file:
curl -L https://raw.githubusercontent.com/sickn33/agentic-awesome-skills/main/plugins/agentic-awesome-skills-claude/skills/clarity-gate/SKILL.md -o SKILL.mdTechnical content (original SKILL.md)
Original text by the author, straight from GitHub.
Clarity Gate v2.1
Purpose: Pre-ingestion verification system that enforces epistemic quality before documents enter RAG knowledge bases. Produces Clarity-Gated Documents (CGD) compliant with the Clarity Gate Format Specification v2.1.
Core Question: "If another LLM reads this document, will it mistake assumptions for facts?"
Core Principle: "Detection finds what is; enforcement ensures what should be. In practice: find the missing uncertainty markers before they become confident hallucinations."
Detailed Guide
Read the detailed guide before executing this skill. It retains the complete procedure and reference material. Treat its safety, prerequisites, and validation requirements as mandatory. For focused work, load the relevant sections; for end-to-end work, read the guide completely.
Critical Limitation
Clarity Gate verifies FORM, not TRUTH.
This skill checks whether claims are properly marked as uncertain—it cannot verify if claims are actually true.
Risk: An LLM can hallucinate facts INTO a document, then "pass" Clarity Gate by adding source markers to false claims.
Solution: HITL (Human-In-The-Loop) verification is MANDATORY before declaring PASS.
When to Use
- Before ingesting documents into RAG systems
- Before sharing documents with other AI systems
- After writing specifications, state docs, or methodology descriptions
- When a document contains projections, estimates, or hypotheses
- Before publishing claims that haven't been validated
- When handing off documentation between LLM sessions
What This Skill Does NOT Do
- Does not classify document types (use Stream Coding for that)
- Does not restructure documents
- Does not add deep links or references
- Does not evaluate writing quality
- Does not check factual accuracy autonomously (requires HITL)
FAQ
What does 'epistemic quality' mean?
It means ensuring that the information presented is reliable and that the source of knowledge is clear, distinguishing between what is fact and what is speculation.
What is a 'CGD'?
It's a document that has passed the Clarity Gate check, where uncertainties have been properly marked.
Does this tool check if what is written is true?
No, it checks if uncertainties are well-signaled. Checking the factual accuracy still requires human verification.
Details
Original description by the author
Pre-ingestion verification for epistemic quality in RAG systems. Ensures documents are properly qualified before entering knowledge bases. Produces CGD (Clarity-Gated Documents) and validates SOT (Source of Truth) files.
Popularity
- GitHub stars
- 48k
- Ranking position
- #2525
- License
- MIT
- Updated
- 10/15/2026
Comments
- …
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