精选 Skills 索引（第 65 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。
- risk-compliance-super-intelligence
Risk & Compliance (GRC) Super Intelligence Team. Named real-world personas across 7 cells. Built local-first (LM Studio) and validator-gated. Illustrative composites; see DISCLAIMER.md.
- strategy-super-intelligence
Strategy Super Intelligence Team. Named real-world personas across 7 cells. Built local-first (LM Studio) and validator-gated. Illustrative composites; see DISCLAIMER.md.
- trading-super-intelligence
Trading Super Intelligence Team. Named real-world personas across 8 cells. Built local-first (LM Studio) and validator-gated. Illustrative composites; see DISCLAIMER.md.
- testdriver:extract
Read information from the screen using AI and return it as a string
- testdriver:machine-setup
Configure Linux and Windows sandboxes, persist machines between runs, and install custom software
- remotion-best-practices
Best practices for Remotion - Video creation in React
- 31_DrugProt — Drug-Protein Relation Query
Query drug/chemical and gene/protein entities in the **BioCreative VII DrugProt** dataset. Returns annotated relations (e.g., INHIBITOR, ACTIVATOR, SUBSTRATE) between chemicals and genes/proteins from biomedical literature.
- 60_GDSC_GDSC2 — Genomics of Drug Sensitivity in Cancer
| Field | Value | |---|---| | Category | Drug-centric | | Subcategory | Drug Molecular Property | | Source | Sanger / Wellcome Trust | | Datasets | **screened_compounds** (drug list), **GDSC1/GDSC2** (dose-response), **Cell Model Passports…
- 66 · SemaTyP
> Drug-Disease Association Knowledge Graph from literature mining + TTD > **Category:** Drug-centric | **Type:** KG | **Subcategory:** Drug-Disease Associations > **Access:** Local files (downloaded from GitHub)
- 67 · CPIC
> Clinical Pharmacogenomics Implementation Consortium — gene-based prescribing guidelines > **Category:** Drug-centric | **Type:** DB | **Subcategory:** Drug Knowledgebase > **API:** `https://api.cpicpgx.org/v1` (PostgREST, free, no key re…
- 68 · KEGG Drug
> Approved drugs — structures, targets, pathways & drug-drug interactions > **Category:** Drug-centric | **Type:** DB | **Subcategory:** DDI > **API:** `https://rest.kegg.jp` (free, no key required for academic use)
- Academic Literature Search — 学术文献检索与引用管理
Use this skill when the user asks to search for academic papers, retrieve literature, generate citations, format references, or any task involving PubMed, bioRxiv, arXiv, or academic reference management. Trigger keywords: "搜文献", "检索", "找论…
- aeon
This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. Use when working with temporal data, sequential pattern…
- arboreto
Infer gene regulatory networks (GRNs) from gene expression data using scalable algorithms (GRNBoost2, GENIE3). Use when analyzing transcriptomics data (bulk RNA-seq, single-cell RNA-seq) to identify transcription factor-target gene relatio…
- article-writing
Write articles, guides, blog posts, tutorials, newsletter issues, and other long-form content in a distinctive voice derived from supplied examples or brand guidance. Use when the user wants polished written content longer than a paragraph…
- astropy
Comprehensive Python library for astronomy and astrophysics. This skill should be used when working with astronomical data including celestial coordinates, physical units, FITS files, cosmological calculations, time systems, tables, world…
- bgpt-paper-search
Search scientific papers and retrieve structured experimental data extracted from full-text studies via the BGPT MCP server. Returns 25+ fields per paper including methods, results, sample sizes, quality scores, and conclusions. Use for li…
- bio-clinical-biostatistics-survival-analysis
Performs time-to-event analysis for clinical trials including Cox proportional hazards regression with PH diagnostics, restricted mean survival time (RMST) under non-PH, competing risks via Fine-Gray vs cause-specific Cox, weighted log-ran…
- bio-comparative-genomics-ortholog-inference
Infer orthologous genes and gene families across species using OrthoFinder3 (HOG-based phylogenetic orthology), SonicParanoid2, Broccoli, ProteinOrtho, OMA / FastOMA hierarchical orthologous groups, eggNOG-mapper, JustOrthologs, and TOGA w…
- bio-crispr-screens-batch-correction
Batch effect correction for CRISPR screens covering ComBat empirical-Bayes, RUV, SVA, control-sgRNA normalization, and the model-based alternative of including batch as a covariate in MAGeCK MLE or Chronos. Covers screen-specific batch sou…
- bio-differential-expression-batch-correction
Remove batch effects from RNA-seq data using ComBat, ComBat-Seq, limma removeBatchEffect, and SVA for unknown batch variables. Use when correcting batch effects in expression data.
- bio-flow-cytometry-doublet-detection
Detect and remove doublets from flow and mass cytometry data. Covers FSC/SSC gating and computational doublet detection methods. Use when filtering out cell aggregates before clustering or quantitative analysis.
- bio-long-read-splicing
Analyzes alternative splicing from PacBio Iso-Seq (HiFi, Kinnex/MAS-Iso-seq) and Oxford Nanopore (direct cDNA, direct RNA, R10.4.1+) long-read RNA-seq with full-isoform resolution. Tools include FLAIR (correct/collapse/quantify/diffSplice…
- bio-machine-learning-survival-analysis
Analyzes time-to-event data using Kaplan-Meier curves, log-rank tests, and Cox proportional hazards regression with lifelines. Builds survival models from clinical and omics features. Use when predicting patient survival or modeling time-t…
- bio-microbiome-differential-abundance
Differential abundance testing for microbiome data using compositionally-aware methods like ALDEx2, ANCOM-BC2, and MaAsLin2. Use when identifying taxa that differ between experimental groups while accounting for the compositional nature of…
- bio-ml-docking-rescoring
Performs ML-based protein-ligand pose prediction and scoring using DiffDock-L (diffusion-based), Boltz-1 / Boltz-2 (foundation model with affinity), Chai-1, AlphaFold3 ligand, EquiBind, TANKBind, NeuralPLexer, and hybrid workflows (DiffDoc…
- bio-ortholog-inference
Pull pre-computed ortholog calls from public databases (OrthoDB, Ensembl Compara, OMA browser, eggNOG, PANTHER, KEGG Orthology, HomoloGene) via their REST APIs. Use when orthologs are already curated upstream, when the question is "what is…
- bio-proteomics-differential-abundance
Statistical testing for differentially abundant proteins between conditions. Covers preprocessing (log2 transformation, normalization), limma and DEqMS workflows with empirical Bayes moderation, fold change shrinkage for accurate effect si…
- bio-restriction-fragment-analysis
Analyze restriction digest fragments using Biopython Bio.Restriction. Predict fragment sizes, get fragment sequences, simulate gel electrophoresis patterns, and perform double digests. Use when analyzing restriction digest fragment pattern…
- bio-single-cell-doublet-detection
Detect and remove doublets (multiple cells captured in one droplet) from single-cell RNA-seq data. Uses Scrublet (Python), DoubletFinder (R), and scDblFinder (R). Essential QC step before clustering to avoid artificial cell populations. Us…
- biomni
Autonomous biomedical AI agent framework for executing complex research tasks across genomics, drug discovery, molecular biology, and clinical analysis. Use this skill when conducting multi-step biomedical research including CRISPR screeni…
- brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
- brenda-database
Access BRENDA enzyme database via SOAP API. Retrieve kinetic parameters (Km, kcat), reaction equations, organism data, and substrate-specific enzyme information for biochemical research and metabolic pathway analysis.
- Bulk Omics Clustering Analysis
Systematic workflow for clustering biological samples, features, or any quantitative data matrix. Implements multiple clustering algorithms with rigorous validation, comparison, and interpretation to identify meaningful data groupings.
- bulk-rna-seq-batch-correction-with-combat
Use omicverse's pyComBat wrapper to remove batch effects from merged bulk RNA-seq or microarray cohorts, export corrected matrices, and benchmark pre/post correction visualisations.
- bulk-rna-seq-deconvolution-with-bulk2single
Turn bulk RNA-seq cohorts into synthetic single-cell datasets using omicverse's Bulk2Single workflow for cell fraction estimation, beta-VAE generation, and quality control comparisons against reference scRNA-seq.
- bulk-rna-seq-deseq2-analysis-with-omicverse
Walk Claude through PyDESeq2-based differential expression, including ID mapping, DE testing, fold-change thresholding, and enrichment visualisation.
- bulk-rna-seq-differential-expression-with-omicverse
Guide Claude through omicverse's bulk RNA-seq DEG pipeline, from gene ID mapping and DESeq2 normalization to statistical testing, visualization, and pathway enrichment. Use when a user has bulk count matrices and needs differential express…
- bulk-wgcna-analysis-with-omicverse
Assist Claude in running PyWGCNA through omicverse—preprocessing expression matrices, constructing co-expression modules, visualising eigengenes, and extracting hub genes.
- bulktrajblend-trajectory-interpolation
Extend scRNA-seq developmental trajectories with BulkTrajBlend by generating intermediate cells from bulk RNA-seq, training beta-VAE and GNN models, and interpolating missing states.