Skill UI

This workflow performs a comprehensive review against the Azure Well-Architected Framework (WAF) using your existing Infrastructure as Code (IaC) and deployed resources. It systematically checks the five pillars—Reliability, Security, Cost Optimization, Operational Excellence, and Performance Efficiency—identifying architectural risks, drift, and compliance gaps. Findings are automatically logged and converted into actionable GitHub issues for streamlined remediation.

This guide helps scholars assess if their social, economic, or cultural history manuscript aligns with the rigorous, problem-driven standards of Past & Present. It instructs authors on framing their research around a core "big question"—a genuine historical problem—ensuring comparative significance, adhering to historiographical expectations, and meeting specific academic standards like double-blind review and Chicago style.

This tool assists researchers in assembling and rigorously validating a complete replication package for academic submission. It checks the master script, pinned environment, data plan, and methodology against specific journal policies, ensuring that every reported number is reproducible and deterministic, preventing 'my machine' errors.

A comprehensive guide for authors submitting to SIGMETRICS, detailing how to structure the Related Work section. It emphasizes shifting from a simple citation catalog to a 'delta-first' contrast, highlighting the specific technical novelty (e.g., tighter bounds, weaker assumptions) relative to existing literature across multiple performance evaluation lanes (systems, measurement, learning, etc.).

This skill serves as a comprehensive guide for authors targeting The William and Mary Quarterly. It helps users re-frame local studies into arguments that engage with the field's major debates concerning 'vast early America,' covering topics such as slavery, indigenous encounters, and transatlantic exchange. It details field positioning, historiographical intervention, and submission standards.

Astropy is the essential Python package for astronomical research and data analysis. It provides a comprehensive suite of tools for handling celestial coordinate transformations (e.g., ICRS, Galactic), managing physical units and quantities, processing FITS files, performing complex cosmological calculations, and ensuring precise time handling. It is indispensable for any project involving scientific data in the field of astronomy and astrophysics.

gget is a versatile CLI and Python package designed for rapid, reproducible bioinformatics searches across major genomic reference databases (e.g., Ensembl, UniProt). It allows users to quickly query gene metadata, perform initial BLAST/BLAT style alignments, and explore associated pathways, cancer, or disease modules. It is ideal for initial data exploration and generating reproducible evidence logs before building complex, full-scale local pipelines.

Polars is a lightning-fast DataFrame library designed for efficient, memory-efficient data processing in Python and Rust. Built upon Apache Arrow, it supports lazy evaluation and parallel execution, making it ideal for ETL pipelines, large-scale data transformations, and scenarios where standard Pandas performance is insufficient. It excels at handling datasets up to 100GB that fit within available RAM.

Statsmodels is Python's premier library for rigorous statistical modeling. It provides comprehensive tools for estimation, inference, and diagnostics across a wide range of statistical methods. Use this skill for advanced analysis, including linear regression (OLS, WLS), generalized linear models (Logistic, Poisson), and complex time series forecasting (ARIMA). Ideal for econometric studies and producing publication-ready results.

A comprehensive white-box security auditing workflow designed for proprietary source code. It integrates static analysis security testing (SAST) tools like Semgrep and CodeQL to detect common vulnerabilities (e.g., injection, IDOR, crypto misuse), followed by mandatory manual threat modeling and verification steps. Applicable for PR reviews and pre-deployment security checks.

A specialized downstream skill for CTF-sandbox workflows. Used to analyze complex security challenges driven by AI agent interactions, prompt injection, or infrastructure vulnerabilities. Focuses on tracing control chains involving untrusted input, tool side effects, deployment drift, container runtime issues, and CI/CD supply chain provenance. Ideal for rigorous vulnerability assessment in modern, distributed systems.

This specialized skill is designed for in-depth security and forensic analysis of Windows secrets protected by DPAPI. It maps the entire lifecycle of encrypted credentials, tracing the flow from the initial protected blob or masterkey through the context unwrapping (e.g., user logon, machine context, domain backup keys) to the specific service that finally accepts the plaintext secret. Use this to prove the decisive access edge in a complex compromise scenario.