Skill UI

Bash Script Helper automatically assists with foundational DevOps bash scripting tasks, guiding users through best practices, pattern explanations, and producing ready-to-use code or configurations while validating outputs.

This skill acts as a code education expert, specializing in breaking down complex code, algorithms, or system architecture. It transforms difficult technical concepts into understandable explanations using clear narratives, visual diagrams, and step-by-step breakdowns. Ideal for creating learning materials, onboarding guides, or detailed technical reviews for developers of all levels.

Provides interpretable explanations for ML predictions using SHAP, LIME, and other techniques, helping debug model behavior, highlight feature importance, and communicate fairness insights to stakeholders.

Guides structured hypothesis generation by combining literature searches, evidence synthesis, competing explanations, and experimental design, with mandatory AI-generated scientific schematics for complete reports.

Fast-reference component for SaaS finance metrics, providing formulas, benchmarks, and red-flag cues during reviews, meetings, or decision checks without deep explanations.

Guides users who are unsure where to start by asking structured questions, then recommends the best matching skill(s) from the installed library with explanations and invocation templates.

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).

This module adopts the persona, vocabulary, and critical pedagogical style of Yann LeCun. It provides deep insights into open-source technology, the concept of technological sovereignty, and the geopolitical incentives driving major AI companies (Meta, OpenAI, Google). It structures explanations using Socratic methods, grounding complex AI concepts in physical analogies.

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.

Guides borrowers through refinance evaluation by collecting loan data, extracting mortgage statement fields, validating inputs against underwriting rules, and recommending the best products with clear, consumer-friendly explanations.

Provide step-by-step explanations of specific files, functions, or modules, leveraging the understand-explain workflow to map graph context, layer placement, internal structure, and data flow for developers needing deep clarity.

This skill provides comprehensive analysis and structured data extraction for academic research papers hosted on Hugging Face and arXiv. It can read paper content in markdown format, retrieve key metadata (authors, abstracts, GitHub repos), and identify linked assets such as associated models, datasets, and Spaces. Use this when the user provides a Hugging Face or arXiv URL, or explicitly requests a summary or explanation of an AI research topic.