精选 Skills 索引（第 68 页）
按质量分排序的前 8,000 个 Skills，每个都有可收录的独立页面。需要全库 15.8 万条检索时，请使用 Skills 目录。
- scholar-evaluation
Systematically evaluate scholarly work using the ScholarEval framework, providing structured assessment across research quality dimensions including problem formulation, methodology, analysis, and writing with quantitative scoring and acti…
- scientific-brainstorming
Creative research ideation and exploration. Use for open-ended brainstorming sessions, exploring interdisciplinary connections, challenging assumptions, or identifying research gaps. Best for early-stage research planning when you do not h…
- scientific-problem-selection
This skill should be used when scientists need help with research problem selection, project ideation, troubleshooting stuck projects, or strategic scientific decisions. Use this skill when users ask to pitch a new research idea, work thro…
- scikit-bio
Biological data toolkit. Sequence analysis, alignments, phylogenetic trees, diversity metrics (alpha/beta, UniFrac), ordination (PCoA), PERMANOVA, FASTA/Newick I/O, for microbiome analysis.
- scikit-learn
Machine learning in Python with scikit-learn. Use when working with supervised learning (classification, regression), unsupervised learning (clustering, dimensionality reduction), model evaluation, hyperparameter tuning, preprocessing, or…
- scikit-survival
Comprehensive toolkit for survival analysis and time-to-event modeling in Python using scikit-survival. Use this skill when working with censored survival data, performing time-to-event analysis, fitting Cox models, Random Survival Forests…
- scvelo
RNA velocity analysis with scVelo. Estimate cell state transitions from unspliced/spliced mRNA dynamics, infer trajectory directions, compute latent time, and identify driver genes in single-cell RNA-seq data. Complements Scanpy/scVI-tools…
- scvi-tools
Deep generative models for single-cell omics. Use when you need probabilistic batch correction (scVI), transfer learning, differential expression with uncertainty, or multi-modal integration (TOTALVI, MultiVI). Best for advanced modeling,…
- shap
Model interpretability and explainability using SHAP (SHapley Additive exPlanations). Use this skill when explaining machine learning model predictions, computing feature importance, generating SHAP plots (waterfall, beeswarm, bar, scatter…
- SIDER - Side Effect Resource
**Category:** Drug-centric | **Type:** DB | **Subcategory:** Adverse Drug Reaction (ADR) **Link:** http://sideeffects.embl.de/ | **Paper:** https://doi.org/10.1093/nar/gkv1075
- Single-Cell RNA-seq Core Analysis (Scanpy)
Complete workflow for single-cell RNA-seq analysis using Scanpy and the scverse ecosystem. Process raw data through quality control, normalization, clustering, and cell type annotation with publication-ready visualizations.
- Single-Cell RNA-seq Core Analysis (Seurat)
Complete workflow for single-cell RNA-seq analysis using Seurat v5. Process raw data through quality control, normalization, clustering, and cell type annotation with publication-ready visualizations.
- Single-Cell Trajectory Inference
**Use when you have preprocessed scRNA-seq data and want to:** - ✅ Order cells along a differentiation or disease trajectory (pseudotime) - ✅ Identify branching points and terminal cell fates - ✅ Discover genes driving cell state transitio…
- single-cell-annotation-skills-with-omicverse
Guide Claude through SCSA, MetaTiME, CellVote, CellMatch, GPTAnno, and weighted KNN transfer workflows for annotating single-cell modalities.
- single-cell-cellphonedb-communication-mapping
Run omicverse's CellPhoneDB v5 wrapper on annotated single-cell data to infer ligand-receptor networks and produce CellChat-style visualisations.
- single-cell-clustering-and-batch-correction-with-omicverse
Guide Claude through omicverse's single-cell clustering workflow, covering preprocessing, QC, multimethod clustering, topic modeling, cNMF, and cross-batch integration as demonstrated in t_cluster.ipynb and t_single_batch.ipynb.
- single-cell-downstream-analysis
Checklist-style reference for OmicVerse downstream tutorials covering AUCell scoring, metacell DEG, and related exports.
- single-cell-multi-omics-integration
Quick-reference sheet for OmicVerse tutorials spanning MOFA, GLUE pairing, SIMBA integration, TOSICA transfer, and StaVIA cartography.
- single-cell-rna-qc
Performs quality control on single-cell RNA-seq data (.h5ad or .h5 files) using scverse best practices with MAD-based filtering and comprehensive visualizations. Use when users request QC analysis, filtering low-quality cells, assessing da…
- SKILL.md — William C. Campbell (2015 Nobel Prize in Physiology or Medicine)
> **蒸馏对象**: William Cecil Campbell > **获奖年份**: 2015 > **获奖理由**: 与 Satoshi Ōmura 共享一半奖项，"发现针对线虫寄生虫感染的新型疗法" > **蒸馏引擎**: 女娲蒸馏引擎 v1 > **蒸馏日期**: 2026-04-06
- Spatial Transcriptomics Visium Analysis
- You have **10x Visium** spatial gene expression data (with or without H&E image) - You want to identify **spatially variable genes** across a tissue section - You want to discover **spatial tissue domains** via clustering - You want to q…
- Statistical Analysis & Quality Control
| Data Type | Groups | Paired? | Normal? | Recommended Test | |-----------|--------|---------|---------|-----------------| | Continuous | 2 | No | Yes | Independent t-test | | Continuous | 2 | No | No | Mann-Whitney U | | Continuous | 2 |…
- statistical-analysis
Guided statistical analysis with test selection and reporting. Use when you need help choosing appropriate tests for your data, assumption checking, power analysis, and APA-formatted results. Best for academic research reporting, test sele…
- statsmodels
Statistical models library for Python. Use when you need specific model classes (OLS, GLM, mixed models, ARIMA) with detailed diagnostics, residuals, and inference. Best for econometrics, time series, rigorous inference with coefficient ta…
- string-protein-interaction-analysis-with-omicverse
Help Claude query STRING for protein interactions, build PPI graphs with pyPPI, and render styled network figures for bulk gene lists.
- sympy
Use this skill when working with symbolic mathematics in Python. This skill should be used for symbolic computation tasks including solving equations algebraically, performing calculus operations (derivatives, integrals, limits), manipulat…
- torchdrug
PyTorch-native graph neural networks for molecules and proteins. Use when building custom GNN architectures for drug discovery, protein modeling, or knowledge graph reasoning. Best for custom model development, protein property prediction,…
- transformers
This skill should be used when working with pre-trained transformer models for natural language processing, computer vision, audio, or multimodal tasks. Use for text generation, classification, question answering, translation, summarizatio…
- Two-Sample Mendelian Randomization
- You have **GWAS summary statistics** for an exposure and outcome trait - You want to test **causal direction** between two traits (not just correlation) - You need to assess whether an observed association is likely causal or confounded…
- umap-learn
UMAP dimensionality reduction. Fast nonlinear manifold learning for 2D/3D visualization, clustering preprocessing (HDBSCAN), supervised/parametric UMAP, for high-dimensional data.
- UniD3 - Drug Discovery Knowledge Graph
UniD3 is a multi-knowledge-graph built from 150,000+ PubMed articles, stored as 6 GraphML files. It supports drug-disease matching, effectiveness assessment, and drug-target analysis.
- Upstream Regulator Analysis
Identify transcription factors (TFs) driving observed differential expression by integrating **ChIP-Atlas TF binding data** (epigenomics) with **RNA-seq DE results** (transcriptomics). Ranks TFs by a combined regulatory score incorporating…
- Weighted Gene Co-expression Network Analysis (WGCNA)
Build weighted gene co-expression networks to identify modules of coordinately expressed genes and discover hub genes that may be key regulators. This workflow uses WGCNA (Weighted Gene Co-expression Network Analysis) to group genes into m…
- what-if-oracle
Run structured What-If scenario analysis with multi-branch possibility exploration. Use this skill when the user asks speculative questions like "what if...", "what would happen if...", "what are the possibilities", "explore scenarios", "s…
- xlsx
Use this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .csv, or .tsv file (e.g., adding columns, computing formulas, format…
- earnings-calendar
This skill retrieves upcoming earnings announcements for US stocks using the Financial Modeling Prep (FMP) API. Use this when the user requests earnings calendar data, wants to know which companies are reporting earnings in the upcoming we…
- pair-trade-screener
Statistical arbitrage tool for identifying and analyzing pair trading opportunities. Detects cointegrated stock pairs within sectors, analyzes spread behavior, calculates z-scores, and provides entry/exit recommendations for market-neutral…
- rtvi-cv-customize-model
How to swap the DeepStream CV detection model in the VSS Alerts Blueprint verification (2d_cv) mode - covers ONNX export, custom bbox parsers, compose mount gotchas, nvinfer config, runtime TRT engine build, deployment, and a segmentation-…
- skywork-music-maker
Create professional music with Mureka AI API — songs, instrumentals, and lyrics from natural language descriptions in any language. Use when users want to generate a song, create a beat or instrumental, write lyrics, clone vocals, upload r…
- 32_ADE_Corpus
**ADE Corpus V2** — Adverse Drug Event relation extraction dataset from annotated PubMed case reports.