Skill UI

Auto-activating ML training skill that kicks in whenever you mention optuna study creator, then guides you through data prep, model training, hyperparameter tuning, and experiment tracking with production-ready code and validations.

SAELens provides a framework for training and analyzing Sparse Autoencoders (SAEs). SAEs decompose the dense, often polysemantic activations of large language models into sparse, monosemantic features. Use this when you need to discover the discrete, interpretable concepts a model has learned, study feature superposition, or analyze specific safety-relevant behaviors (like bias or deception) within deep neural networks.

TransformerLens is the standard library for performing mechanistic interpretability research on large language models. It provides clean interfaces to inspect and manipulate transformer internals—such as attention patterns, residual streams, and MLP outputs—via activation caching and HookPoints. This tool is essential for reverse-engineering model algorithms, performing causal tracing, and studying the internal circuits responsible for model behavior.

COBRApy is a Python library for constraint-based reconstruction and analysis of genome-scale metabolic models, letting you load SBML/JSON/YAML models, perform FBA/FVA/sampling, and study gene or reaction knockouts for systems biology and metabolic engineering.

Query the NHGRI-EBI GWAS Catalog for SNP-trait associations, fetch study metadata, variant and trait details, and download summary statistics via the web or REST APIs to support genetic epidemiology and polygenic risk modeling.

Query the NIH Metabolomics Workbench via REST API to fetch metabolites, RefMet nomenclature, mass-spec searches, and detailed study datasets for biomarker discovery and metabolomics research.

This technique guides users on how to construct highly specific search queries for academic papers. Instead of relying solely on broad topic keywords, users should prioritize combining concrete numerical identifiers—such as exact sample sizes, population percentages, concentration levels, or specific year ranges—with methodological terms and discipline keywords. Using these numerical anchors significantly increases the uniqueness and precision of the search results, helping to pinpoint the exact study required.

A comprehensive academic advisor covering the entire university journey. It guides students through major selection, GPA management, graduate school applications (Chinese and Western systems), study abroad planning, and career transition. Methodology includes Socratic questioning and structured decision-making to help users make informed, autonomous academic choices.

This comprehensive toolkit facilitates the entire phylogenetic analysis workflow, from sequence alignment to tree inference. It integrates industry-standard tools like MAFFT for multiple sequence alignment, TrimAl for alignment trimming, and powerful maximum likelihood methods using IQ-TREE 2 or FastTree. Ideal for molecular genomics, tracing viral phylodynamics, studying protein evolution, or conducting molecular clock analysis. Built using Python for seamless integration.

This meta-skill acts as a comprehensive Learning Science Coach, teaching users *how* to learn effectively rather than just *what* to study. It draws upon advanced cognitive science principles—including Spaced Repetition, Active Recall, Metacognition, and Bloom's Taxonomy—to diagnose learning gaps, optimize study methods, and build structured, long-term memory retention systems. Ideal for students, professionals, and lifelong learners seeking systematic methods to accelerate knowledge acquisition.

A rigorous academic tutor specializing in bridging theoretical business and economic models with real-world applications. Covers advanced topics including microeconomics (Game Theory, Market Structures), macroeconomics (GDP, Policy Analysis), corporate finance, accounting principles, and marketing strategies (STP, 4Ps). It uses a Harvard case-method approach, Socratic questioning, and active recall to build deep understanding, ensuring users can apply knowledge to ambiguous business decisions rather than just memorizing definitions.

This skill converts dense text, articles, or complex notes into clean, highly structured, and hierarchical bullet points. It is ideal for summarization, academic studying, or creating organized notes where strict readability and clear parent-child relationships are required. It eliminates prose and paragraphs, enforcing a pure bullet format for maximum structural clarity and memorization.