Improve scientific collaboration in AI-assisted research. Citation validation, claim verification, cross-file consistency.

This repository contains a solutions for the exercises in the "Math Concepts For Developers" course at SoftUni .

Structured observation management for research agents

97 reasoning patterns from history's greatest minds — as Claude Code agents. Curie to Toulmin. Engineering to humanities. Every claim cites its source. Every commit is checked. The only agent system where "I don't know" is a feature.

Please fork and criticize!

Desktop app built with Flutter to simulate solar PV array energy assessment using the OSM-MEPS model at fixed tilt-azimuth orientations (check the releases sidebar/tab).

MCP server for Claude Desktop that applies Popperian falsifiability to verify claims from social media, news and blogs — with real academic sources, not opinions.

ASRP (AI Scientific Research Platform) Desktop — Multi-Agent collaborative scientific research platform

A conservation-honest diagnostic framework for auditing early-universe models and separating physical dynamics from descriptive bookkeeping.

Notes for the Anleitung zum wissenschaftlichen Arbeiten (scientific writing) course at HdM Stuttgart.

railroad industry and manufacturing

Introduction in the scientific method using the Hertzsprung-Russel-Diagram

A logic engine and persona bootloader for LLMs (validated on Gemini 3) designed to bypass consensus bias through rigorous inquiry. Using a 4-Axiom hierarchy (Data, Scope, Mechanism, Probability), it enables human-AI symbiosis to preserve persistent logic across sessions.

Learning material on the scientific method for security research

Epistemic method visibility project. Reduce cognitive stagnation. Promote self-doubt across positions. Pro-method, not pro-science.

Experimental Methodology at Royal Institute of Technology KTH

Theorem of the Unnameable [⧉/⧉ₛ] — Epistemological framework for binary information classification (Fixed Point/Fluctuating Point). Application to LLMs via 3-6-9 anti-loop matrix. Empirical validation: 5 models, 73% savings, zero hallucination on marked zones.

A research protocol for falsifiable multi-agent inquiry that prevents confirmation bias through role separation, sequence enforcement, and pre-committed falsification criteria (PACI).