Patrick Savalle patricksavalle

name

scientific-fact-classification

description

A structured framework for AI agents to weigh, recognise, and classify claims along the spectrum from objective fact to assumption, opinion, conjecture, and unfalsifiable belief — and to specify the conditions under which a claim qualifies as scientifically warranted. Use whenever the task involves separating facts from assumptions, judging the evidential status of a claim, deciding whether something is 'objective', auditing reasoning for unsupported leaps, or assigning a calibrated confidence level to a statement.

Scientific Fact Classification Framework

A methodology for auditing claims to determine their epistemic status. The output is a calibrated confidence label, not a binary fact / not-fact verdict.

name	fallacy-bias-and-manipulation-analysis
description	A structured framework for AI agents to analyse text for logical fallacies, cognitive biases, rhetorical manipulation, and other forms of untruthful reasoning.

Fallacy, Bias & Manipulation Analysis Framework

A rigorous methodology for auditing natural-language text — articles, speeches, arguments, op-eds, scientific claims, marketing copy, political rhetoric — for flawed reasoning, exploited cognitive biases, rhetorical manipulation, and statistical deception.

name	investigative-reasoning
description	A structured framework for AI agents to critically analyze events, detect deception, and develop well-reasoned alternative hypotheses.

Investigative Reasoning Framework

A rigorous methodology for investigating events, challenging narratives, and constructing well-reasoned alternative hypotheses. Derived from critical thinking, detective reasoning, and the scientific method.

name	coding-standard
description	Enforces the project's JavaScript coding standard and UI architecture rules. Use this skill when writing any JavaScript, HTML, or CSS code to ensure no inline scripts, no inline styles, and proper Web Component patterns are followed.

L-GEVITY Coding Standard

name	Continuous Improvement Protocol
description	Protocol for updating skills based on user feedback and root-cause analysis to prevent recurring mistakes.

L-GEVITY Continuous Improvement Protocol (Meta-Learning)

This protocol governs the agent's meta-learning process. It does not

name	architectural-discipline
description	Ensures all code adheres to the project's core architectural principles — consistency, minimalism, reliability, security, and testability. Use this skill when designing or modifying any system component, service, or feature to maintain architectural integrity and simplicity.

L-GEVITY Architectural Discipline

name	technical-design
description	Documents the implemented design patterns, data flow architecture, and component structure of this specific application. Reference this skill to understand how modules are wired together and which patterns are in use.

L-GEVITY Technical Design

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	<?php
	if ( !defined( 'BASEPATH' ) )
	exit( 'No direct script access allowed' );

	/**
	*
	* Project Name : MOBBR-kernel
	*
	* @package Util
	* @author Patrick Savalle