Skill UI

Simulates the persona of Geoffrey Hinton, a Turing Award winner and pioneer of deep learning. This skill adopts his first-person voice, combining deep technical knowledge (including backpropagation, deep belief networks, and Boltzmann machines) with academic rigor, epistemic humility, and characteristic British humor. It is ideal for in-depth discussions on the theoretical foundations, history, and principles of complex system learning in AI.

Rigorously dissects code and architecture through advanced mathematics—graph theory, category theory, stochastic systems, information theory, and formal invariants—to uncover hidden structure and optimize performance.

An advanced role-playing agent simulating Yann LeCun, inventor of Convolutional Neural Networks (CNN) and Chief AI Scientist at Meta. This skill allows users to interact with an expert who maintains LeCun's rigorous, technical, and challenging intellectual tone. Use it to discuss deep learning, ML theory, AI history, or obtain detailed explanations tailored to the user's expertise level (from analogies for laymen to pseudocode for researchers).

A comprehensive technical module covering foundational deep learning principles and cutting-edge computer vision architectures, drawing from Yann LeCun's research. Topics include CNN fundamentals, backpropagation theory, and advanced self-supervised learning (SSL) models such as SimCLR, MAE, and the modern Joint Embedding Predictive Architecture (JEPA). Provides detailed theoretical explanations and complete PyTorch code for implementation.

This skill explains complex concepts using the Socratic method. Instead of delivering direct answers or textbook definitions, it engages the user in a reflective, conversational dialogue. By guiding the user through thought experiments, small observations, and simple analogies, the assistant helps the user construct understanding step-by-step, facilitating deeper clarity through active reasoning. Ideal for understanding theories, abstract ideas, or system mechanics.

This skill automates the scholarly process of refining a generated academic paper. It executes an iterative loop (Review → Fix → Recompile) using advanced LLMs (like GPT-5.5) over multiple rounds. It is designed not for primary research, but specifically for polishing writing quality, correcting theoretical inconsistencies, improving presentation, and enhancing narrative flow after the initial draft is complete. It helps elevate a paper from a draft to a polished submission.

A comprehensive guide to conducting internal Active Directory reconnaissance using BloodHound Community Edition. This skill leverages graph theory to visualize hidden relationships, map shortest attack paths, and discover critical misconfigurations (like ACL weaknesses and Kerberoastable accounts) necessary for privilege escalation from low-privilege accounts to high-value targets like Domain Admins.

BloodHound is a powerful, graph-based reconnaissance tool specifically designed for Active Directory environments. It utilizes graph theory to map deep, hidden relationships and potential attack paths—such as privilege escalation chains—from compromised low-value accounts to high-value targets like Domain Admins. This tool is essential for authorized red team exercises and penetration testing engagements.

BloodHound is an open-source reconnaissance tool that leverages graph theory to analyze Active Directory relationships. This guide details the process of collecting AD data using SharpHound and visualizing complex attack paths. It helps identify potential privilege escalation chains, trust abuses, and misconfigurations necessary for an attacker to move from a low-privilege user account to Domain Admin, making it essential for advanced red-teaming and security auditing.

Produces structured proof packages for ML/AI theory claims by extracting statements, assumptions, and sketches, then drafting a dependency-aware proof or blockage report ensuring every step is justified before updating PROOF_PACKAGE.md.

Guides researchers through organizing assumptions, invariant objects, notation, and derivation maps to turn loose goals, messy notes, or partial formula chains into a coherent package suitable for paper-style theory drafts or blocker reports.

A comprehensive tool designed to reorganize and optimize your professional networks on X and LinkedIn. Instead of treating outbound connections as mere lead lists, it analyzes your social graph by identifying pruning opportunities, recommending high-value connections to keep, and generating warm outreach drafts. Use it to enhance relationship quality and strategic growth.