Skill UI

This skill provides a structured approach to systematically identify security threats by applying the STRIDE methodology (Spoofing, Tampering, Repudiation, Information Disclosure, Denial of Service, Elevation of Privilege). It is crucial for conducting thorough threat modeling sessions, analyzing system architectures, reviewing security design decisions, and creating robust security documentation for compliance and auditing purposes.

Automates threat modeling guidance within Security Advanced: step-by-step best practices, compliance-ready code, and validation for enterprise security workflows.

A specialized skill for conducting comprehensive security architecture reviews, risk assessments, and threat identification. It masters advanced methodologies like STRIDE, PASTA, and attack tree construction. Use this to build secure-by-design systems, identify potential attack vectors, and strengthen system resilience before deployment.

Guidance for creating, editing, and analyzing .xlsx workbooks while preserving formulas, formatting, and assumptions, leveraging pandas/openpyxl for data work and LibreOffice recalc to ensure error-free financial models.

Automates zero trust configuration support for advanced security operations, offering guidance, code/config generation, and validation whenever zero trust config helper topics arise during penetration testing, compliance, or threat modeling workflows.

Combines ESM3 and ESM C protein language models to generate sequences, predict structures, condition functions, and extract embeddings via local or Forge API inference for protein design and engineering workflows.

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.

Structured workflow for building hierarchical Bayesian models with PyMC 5+, covering data prep, NUTS sampling, diagnostics, posterior checks, and predictive inference.

Cloud-native Rowan orchestrates medicinal chemistry and molecular modeling pipelines via a Python API, offering pKa prediction, docking, descriptors, dynamics, and AI-driven structure workflows for scalable batch screening without local HPC.

Toolkit for Python-based survival and time-to-event modeling with scikit-survival, supporting Cox models, ensemble learners, SVMs, and evaluation metrics for censored data.

SimPy is a powerful, process-based discrete-event simulation framework written in Python. It is designed for modeling complex systems where entities interact with shared resources and time-based events occur, such as manufacturing lines, service queues, network traffic, or logistics networks. Use this skill to analyze resource contention, simulate process optimization, conduct capacity planning, and model dynamic system behaviors.

Statsmodels is a comprehensive Python library dedicated to advanced statistical modeling and econometrics. It provides tools for rigorous statistical inference, including Ordinary Least Squares (OLS), Generalized Linear Models (GLM), mixed-effects models, and time series analysis (ARIMA). Use this skill for detailed diagnostics, coefficient estimation, hypothesis testing, and producing publication-ready statistical reports in fields like econometrics and biostatistics.