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Pydicom is a Python toolkit for reading, writing, and manipulating DICOM medical imaging files, helping teams extract pixel data, manage metadata, anonymize records, convert to standard formats, and integrate with PACS workflows in healthcare research and radiology applications.

Pysam offers Python bindings to htslib for reading and writing SAM/BAM/CRAM alignments, VCF/BCF variants, and FASTA/FASTQ sequences, enabling coverage stats, pileup analysis, variant queries, and seamless integration into NGS pipelines.

Generates minimal macOS Seatbelt sandbox profiles with allowlist-based resource rules so apps can be isolated by permissions, useful for restricting file, network, and IPC access when defending against high-risk execution or supply chain threats.

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.

This comprehensive guide outlines best practices for building reliable and robust AI agent harnesses. It covers optimizing action spaces, defining structured tools, managing observation formats, and implementing essential error recovery contracts. Use these principles to dramatically improve agent completion rates, manage context budgets effectively, and transition AI prototypes into stable, production-grade autonomous systems.

This protocol defines communication standards for C-suite AI agents, enabling structured queries and responses between roles like CFO, CTO, and CEO. It includes syntax for invocations, response formats, and strict rules to prevent infinite loops and circular reasoning. Ideal for orchestrating multi-agent teams in enterprise settings, ensuring coordinated cross-functional analysis and safe board meeting simulations without chaos.

A comprehensive guide for creating high-value competitor comparison and alternative pages. Designed for SEO and sales enablement, this skill covers multiple formats (You vs Competitor, Competitor Alternatives, etc.), emphasizing deep research, trust-building content, and modular architecture to capture competitive search traffic and guide users toward conversion.

This script automates the generation of a complete set of favicons (including favicon.ico, various PNG sizes, and SVG) from a single source image. It intelligently detects the project framework (e.g., Next.js, Rails, Gatsby) to place assets in the correct static directory, generates the necessary webmanifest, and updates the project's HTML/layout files with the proper link tags.

Provides setup logic for integrating WhatsApp services, likely linking messaging workflows for automation or notifications.

This methodology provides a structured framework for stress-testing critical business assumptions before they fail in the market. Learn to systematically identify, challenge, and model the downside risk associated with market size, revenue projections, competitive moats, and customer behavior. It moves beyond optimism to achieve crucial business calibration.

A comprehensive utility for handling asset loading within Three.js environments. It supports various formats, including GLTF/GLB models, textures, HDR environments, and complex image assets. Features include robust asynchronous loading patterns, progress tracking via LoadingManager, and detailed configuration for PBR materials and environment mapping.

This skill integrates multiple digital health sources (such as Apple Health, Fitbit, Oura, and CSV/JSON files) into a unified system. It processes, standardizes, and validates diverse health data formats, and connects this data to a dedicated knowledge base (WellAlly.tech). It provides intelligent recommendations and article retrieval based on the user's current health context and needs.