Skill UI

A comprehensive guide covering core principles for game art production. It details art style selection (Pixel Art, PBR 3D, etc.), structured 2D and 3D asset pipelines, color theory, animation guidelines (including the 12 principles), and professional asset organization standards. Ideal for artists and designers managing the entire game art lifecycle.

Structured guidance for TAM/SAM/SOM calculations, combining top-down, bottom-up, and value-theory methods for startup market analysis and fundraising planning.

Guides symbolic mathematics work in Python, covering algebraic simplification, calculus, equation solving, linear algebra, physics, number theory, geometry, and code generation to deliver exact symbolic results instead of numeric approximations.

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.

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.

This skill applies behavioral economics, specifically prospect theory, to frame messages emphasizing the cost of inaction (loss) rather than just the benefits of action (gain). It guides the creation of persuasive copy, UX copy, and pricing strategies by setting credible reference points and quantifying the missed opportunity. The goal is to ethically leverage the psychological pain of delay, ensuring the approach remains credible and avoids manipulative fear-mongering.