What is the 150% Proof Rule?

It requires 100% core primary evidence plus an additional 50% enhancement through independent secondary validation and active gap-filling to ensure maximum reliability.

When is it best to use the Analyze-Verify skill?

Use it for high-stakes situations such as legal compliance, architectural choices, or any scenario where an unverified claim could result in production failures or business risk.

How does the Loop150 protocol work?

If a claim's confidence score is below 85%, the skill triggers a recursive research loop to broaden the search scope, use alternative research methods, and perform deeper analysis until the threshold is met.

What happens if the 85% confidence threshold cannot be met?

If sources are exhausted and confidence remains low, the skill will escalate the issue to the user, providing a transparent report of findings, gaps, and why a higher certainty could not be achieved.

Analyze-Verify 150 Protocol

Name: Analyze-Verify 150 Protocol
Author: MykhailoDmytriakha

byMykhailoDmytriakha

Seguridad y Pruebas

Verifies critical claims and factual assertions through source-backed evidence and recursive confidence-building loops.

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The Analyze-Verify 150 Protocol is a high-integrity verification framework designed for Claude Code users who need absolute certainty in high-stakes environments. It transforms raw assertions into 'proof-grade' facts by requiring primary and secondary sources, assigning quantitative confidence scores, and automatically triggering deep-research loops (Loop150) whenever confidence falls below 85%. Whether you are making architectural decisions, legal compliance assessments, or critical business claims, this skill ensures that every piece of information is cross-validated and transparently documented, minimizing the risk of hallucinations or errors in professional workflows.

Características Principales

0 GitHub stars
Automated Loop150 recursive research for low-certainty data
Multi-source cross-validation for high-stakes technical claims
Rigorous source reliability assessment (Authority, Currency, Objectivity)
Quantitative confidence scoring based on evidence strength
Standardized 'Proof-Grade' verification output formatting

Casos de Uso

Validating critical software architecture and infrastructure decisions
Verifying performance metrics and data-driven business claims
Ensuring factual accuracy in legal, compliance, and security audits

Acerca de

Características Principales

0 GitHub stars
Automated Loop150 recursive research for low-certainty data
Multi-source cross-validation for high-stakes technical claims
Rigorous source reliability assessment (Authority, Currency, Objectivity)
Quantitative confidence scoring based on evidence strength
Standardized 'Proof-Grade' verification output formatting

Casos de Uso

Validating critical software architecture and infrastructure decisions
Verifying performance metrics and data-driven business claims
Ensuring factual accuracy in legal, compliance, and security audits