verification-system

Verify experiment protocols and numerical analyses via Executor-Validator-Replicator consensus.

Updated Aug 27, 2026
One-click install
npx skills add https://github.com/yjang-git/HoneyPot --skill verification-system
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: verification-system
Source: https://github.com/yjang-git/HoneyPot/tree/main/plugins/powder-analyzer/skills/verification-system
Command: npx skills add https://github.com/yjang-git/HoneyPot --skill verification-system

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Ensures scientific validity and reproducibility by preventing hallucinations, verifying calculations and units, and enforcing consensus before accepting experimental results.

Core Features & Use Cases

  • Three-agent architecture: Executor generates protocols and results, Validator applies six-category checks, and Replicator independently reproduces outcomes.
  • Consensus Gate: Automated PASS/FAIL/CONDITIONAL_PASS decisions based on validator verdicts and Executor-Replicator agreement thresholds with configurable tolerances.
  • Validation checklist & failure protocol: Unit consistency, physical plausibility, ASTM standard compliance, mathematical accuracy, cross-consistency, literature comparison, and an escalation path with retry limits.
  • Use Cases: Verifying DEM parameter calibration, auditing experimental protocols for ASTM compliance, and triaging AI-generated numerical analyses for reproducibility.

Quick Start

Run the verification-system on an experimental protocol to validate units, standards, calculations, and attempt independent reproduction with agreement thresholds.

Frequently Asked Questions about verification-system

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I verify experiment protocols and numerical analysis outputs for reproducibility?

To verify experiment protocols for reproducibility, use a three-agent Executor-Validator-Replicator workflow that enforces provenance and consensus. This system validates units, checks standards compliance, and independently reproduces analytical results to prevent hallucinations.

What is the three-agent consensus workflow for reproducible experiments?

The three-agent consensus workflow pairs an Executor generating structured outputs with a Validator applying six-category checks and a Replicator independently reproducing outcomes. A Consensus Gate then issues PASS, FAIL, or CONDITIONAL_PASS decisions based on configurable agreement thresholds.

How do I audit experimental protocols for ASTM standard compliance?

Audit experimental protocols for ASTM standard compliance by applying the Validator component's six-category validation checklist. This checks unit consistency, physical plausibility, mathematical accuracy, and literature comparison before accepting results.

Can I use AI consensus to check DEM parameter calibration?

Yes, you can use the three-agent consensus workflow to check DEM parameter calibration. The Validator verifies physical plausibility and mathematical accuracy, while the Replicator independently reproduces the calibration results to ensure they meet agreement thresholds.

What happens when independent reproduction of analytical results fails?

When independent reproduction of analytical results fails, the system triggers an escalation path with retry limits. The Consensus Gate issues a FAIL or CONDITIONAL_PASS decision, requiring failure-resolution steps to address discrepancies before accepting the experiment protocol.

What validation categories are checked during scientific reproducibility verification?

During scientific reproducibility verification, the Validator checks six categories: unit consistency, physical plausibility, ASTM standard compliance, mathematical accuracy, cross-consistency, and literature comparison. These checks prevent hallucinations and ensure calculations are verified.