inclusion-criteria
Apply inclusion/exclusion criteria systematically in literature reviews. Use when: (1) Screening abstracts, (2) Reviewing full texts, (3) Documenting screening decisions, (4) Ensuring PRISMA compliance.
Apply inclusion/exclusion criteria systematically in literature reviews. Use when: (1) Screening abstracts, (2) Reviewing full texts, (3) Documenting screening decisions, (4) Ensuring PRISMA compliance.
This skill should be used when users need to identify topologically associating domains (TADs) from Hi-C data in .mcools (or .cool) files or when users want to visualize the TAD in target genome loci. It provides workflows for TAD calling and visualization.
This skill should be used when users need to infer chromatin states from histone modification ChIP-seq data using chromHMM. It provides workflows for chromatin state segmentation, model training, state annotation.
This skill is used to perform genomic feature annotation and visualization for any file containing genomic region information using Homer (Hypergeometric Optimization of Motif EnRichment). It annotates regions such as promoters, exons, introns, intergenic regions, and TSS proximity, and generates visual summaries of feature distributions.
This skill performs differential topologically associating domain (TAD) analysis using HiCExplorer's hicDifferentialTAD tool. It compares Hi-C contact matrices between two conditions based on existing TAD definitions to identify significantly altered chromatin domains.
This pipeline performs genome-wide segmentation of CpG methylation profiles to identify Unmethylated Regions (UMRs), Low-Methylated Regions (LMRs), and Partially Methylated Domains (PMDs) using whole-genome bisulfite sequencing (WGBS) methylation calls. The pipeline provides high-resolution enhancer-like LMRs, promoter-associated UMRs, and large-scale PMDs characteristic of reprogramming, aging, or cancer methylomes, enabling integration with chromatin accessibility, TF binding, and genome architecture analyses.
Anthropic-aligned medical safety evaluation with pass^k metrics, failure taxonomy, and anti-gaming graders
Generate PRISMA 2020 flow diagrams for systematic reviews. Use when: (1) Conducting systematic literature reviews, (2) Documenting screening process, (3) Reporting study selection for publications, (4) Demonstrating PRISMA compliance, (5) Creating transparent review methodology documentation.
Design rigorous experiments following best practices. Use when: (1) Planning research studies, (2) Grant proposal development, (3) Pre-registration, (4) Ensuring internal validity, (5) Meeting NIH rigor standards.
Develop IRB/ethics protocols for human subjects research. Use when: (1) Planning studies involving humans, (2) Preparing IRB applications, (3) Ensuring ethical compliance, (4) Addressing informed consent.
Implement proper randomization procedures for experiments. Use when: (1) Assigning participants to conditions, (2) Ensuring unbiased allocation, (3) Meeting CONSORT standards, (4) Pre-registration.
Code readability review based on "The Art of Readable Code" and Miller's Law (7±2). Use when reviewing code clarity, improving naming, or when user mentions 可読性, 理解しやすい, わかりやすい, 明確, 命名, 変数名, 関数名, ネスト, 深いネスト, 関数設計, コメント, 複雑, 難しい, 難読, Miller's Law, ミラーの法則, 認知負荷, AI-generated, 過剰設計.
Maintain high code quality through formatting, linting, and static analysis using rustfmt, clippy, and cargo audit. Use to ensure consistent code style and catch common mistakes.
Use when implementing any feature or bugfix, before writing implementation code. Enforces RED-GREEN-REFACTOR cycle with strict discipline against rationalization.
Comprehensive Python engineering guidelines for writing production-quality Python code. This skill should be used when writing Python code, performing Python code reviews, working with Python tools (uv, ruff, mypy, pytest), or answering questions about Python best practices and patterns. Applies to CLI tools, AI agents (langgraph), and general Python development.
评审 Project Guardrails/工程规范。用于在 LLD/实现前检查 Guardrails 的完整性、可执行性、一致性与可验证性,给出准出结论。
Perform thorough code reviews with focus on security, performance, maintainability, and best practices. Use when reviewing code changes, pull requests, entire files, or codebase audits across any programming language.