Query COSMIC (Catalogue Of Somatic Mutations In Cancer) for cancer somatic mutations, gene census data, mutational signatures, drug resistance variants, and cancer gene annotations. REST API v3.1 supports gene/sample/variant queries. Free registration required. For germline clinical variants use clinvar-database; for drug-target data use opentargets-database or chembl-database-bioactivity.
Retrieve quantitative phenotype measurements across inbred mouse strains from the Mouse Phenome Database (MPD) for metabolic, behavioral, and physiological traits. Query strain means and raw individual measurements for body weight, glucose, blood pressure, behavioral assays, and 40+ additional procedures. Use for QTL analysis support, cross-strain phenotype comparison, and identifying mouse models for metabolic or behavioral traits. For mouse gene-disease-phenotype associations use monarch-database; for mouse genome annotations use ensembl-database.
Conduct enterprise-grade research with multi-source synthesis, citation tracking, and verification. Use when user needs comprehensive analysis requiring 10+ sources, verified claims, or comparison of approaches. Triggers include "deep research", "comprehensive analysis", "research report", "compare X vs Y", or "analyze trends". Do NOT use for simple lookups, debugging, or questions answerable with 1-2 searches.
Research workflow patterns specific to {project}. Covers research agent coordination, source management, and synthesis strategies.
Visualize datasets in 2D using embeddings with UMAP or t-SNE dimensionality reduction. Use when users want to explore dataset structure, find clusters in images, identify outliers, color samples by class or metadata, or understand data distribution. Requires FiftyOne MCP server with @voxel51/brain plugin installed.
Generate phylogenies from genome assemblies using BUSCO/compleasm-based single-copy orthologs with scheduler-aware workflow generation
Set up and execute phylogenetic biogeographic analyses using BioGeoBEARS in R. Use when users request biogeographic reconstruction, ancestral range estimation, or want to analyze species distributions on phylogenies. Handles input file validation, data reformatting, RMarkdown workflow generation, and result visualization.
This skill should be used when the user asks to "create a packmol input", "pack molecules with packmol", "solvate a protein", "build an initial configuration", "setup molecular dynamics", or discusses molecular packing, solvation, or building simulation starting structures.
Convert laboratory instrument output files (PDF, CSV, Excel, TXT) to Allotrope Simple Model (ASM) JSON format or flattened 2D CSV. Use this skill when scientists need to standardize instrument data for LIMS systems, data lakes, or downstream analysis. Supports auto-detection of instrument types. Outputs include full ASM JSON, flattened CSV for easy import, and exportable Python code for data engineers. Common triggers include converting instrument files, standardizing lab data, preparing data for upload to LIMS/ELN systems, or generating parser code for production pipelines.
Run nf-core bioinformatics pipelines (rnaseq, sarek, atacseq) on sequencing data. Use when analyzing RNA-seq, WGS/WES, or ATAC-seq data—either local FASTQs or public datasets from GEO/SRA. Triggers on nf-core, Nextflow, FASTQ analysis, variant calling, gene expression, differential expression, GEO reanalysis, GSE/GSM/SRR accessions, or samplesheet creation.
리액티브 스프레드시트 엔진 설계 가이드. 셀 수식 파싱, 의존성 그래프(DAG), 증분 재계산, 내장 함수 구현 시 사용한다.
Expert data science covering machine learning, statistical modeling, experimentation, predictive analytics, and advanced analytics. Use when selecting ML algorithms, engineering features, designing A/B tests, evaluating model performance, or building predictive pipelines.
Take any claim and design + execute a complete research protocol to test it. Apply scientific method automatically: design study, gather data, run analysis, provide verdict with confidence level.
ARGUS NANO v2.1 - Compact research skill for context-limited sessions (~3KB). FOCO: Triangulacao (Academico + Pratico + Empirico), validacao de claims, busca multi-fonte com niveis de confianca. DROID: argus-quant-researcher.md tem conhecimento COMPLETO incluindo workflows detalhados, decision trees, e exemplos extensos. Triggers: "Argus", "pesquisa", "research", "papers", "repos", "validar claim", "triangular", "deep dive", "estado da arte", "como outros fazem"
Scientific dataset discovery and access for neuroscience (OpenNeuro, PhysioNet, DANDI) and general domains.
Full token lifecycle from creation through bonding curve trading, graduation detection, AMM migration, fee collection, and volume tracking on Solana using PumpSdk and OnlinePumpSdk.
Use Clay's AI research agent (Claygent) for web research, custom data extraction, and information that does not exist in standard databases. Use when the user asks about Claygent, AI research in Clay, web browsing for data, custom data points, real-time company research, or scraping with AI. Triggers on "Claygent", "AI research", "Clay AI agent", "web research in Clay", "browse web", "research agent", "custom data points", "scrape with AI". Do NOT use for standard enrichments available via providers, Clayscript formulas, or general AI text generation without web research.
Data analysis and statistical computation. Use when user needs "数据分析/统计/计算指标/数据洞察". Supports general analysis, financial data (stocks, returns), business data (sales, users), and scientific research. Uses pandas/numpy/scikit-learn for processing. Automatically activates data-base for data acquisition.
Use when ML engineers need to identify symmetries in their data but don't know where to start. Invoke when user mentions data symmetry, invariance discovery, what transformations matter, or needs help recognizing patterns their model should respect. Works collaboratively through domain analysis, transformation testing, and physical constraint identification.
Automatically identify metamorphic properties (symmetry, linearity, additivity, input invariances) from programs or functions. Use when generating metamorphic tests, discovering program properties, validating transformations, or creating test oracles without explicit specifications. Analyzes control flow, data flow, and sample executions to output structured properties for metamorphic test generation and verification.
Best practices for SciPy scientific computing, optimization, signal processing, and statistical analysis in Python
Causal inference specialist for causal discovery, counterfactual reasoning, and effect estimationUse when "causal inference, causal discovery, counterfactual, intervention effect, confounder, structural causal model, SCM, dowhy, causal graph, causal, dowhy, scm, dag, counterfactual, intervention, causalnex, confounding, ml-memory" mentioned.
