Discover and use technical skills to extend Claude's capabilities
433 Technical Skills Available
Expert knowledge for building SQL database sinks from Substreams. Covers database changes (CDC), relational mappings, PostgreSQL, ClickHouse, and materialized views.
Protocol-driven analysis executor. The consuming agent discovers relevant protocols, composes a prompt, and calls this tool.
Distributed computing for larger-than-RAM pandas/NumPy workflows. Use when you need to scale existing pandas/NumPy code beyond memory or across clusters. Best for parallel file processing, distributed ML, integration with existing pandas code. For out-of-core analytics on single machine use vaex; for in-memory speed use polars.
NGS analysis toolkit. BAM to bigWig conversion, QC (correlation, PCA, fingerprints), heatmaps/profiles (TSS, peaks), for ChIP-seq, RNA-seq, ATAC-seq visualization.
Comprehensive toolkit for creating, analyzing, and visualizing complex networks and graphs in Python. Use when working with network/graph data structures, analyzing relationships between entities, computing graph algorithms (shortest paths, centrality, clustering), detecting communities, generating synthetic networks, or visualizing network topologies. Applicable to social networks, biological networks, transportation systems, citation networks, and any domain involving pairwise relationships.
Automated LLM-driven hypothesis generation and testing on tabular datasets. Use when you want to systematically explore hypotheses about patterns in empirical data (e.g., deception detection, content analysis). Combines literature insights with data-driven hypothesis testing. For manual hypothesis formulation use hypothesis-generation; for creative ideation use scientific-brainstorming.
Comprehensive scientific research toolkit with 139 specialized skills for biology, chemistry, medicine, data science, and computational research. Transforms Claude into an AI research assistant with access to scientific databases, analysis tools, and domain-specific workflows.
Data structure for annotated matrices in single-cell analysis. Use when working with .h5ad files or integrating with the scverse ecosystem. This is the data format skill—for analysis workflows use scanpy; for probabilistic models use scvi-tools; for population-scale queries use cellxgene-census.
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, Gradient Boosting models, or Survival SVMs, evaluating survival predictions with concordance index or Brier score, handling competing risks, or implementing any survival analysis workflow with the scikit-survival library.
Work with Data Commons, a platform providing programmatic access to public statistical data from global sources. Use this skill when working with demographic data, economic indicators, health statistics, environmental data, or any public datasets available through Data Commons. Applicable for querying population statistics, GDP figures, unemployment rates, disease prevalence, geographic entity resolution, and exploring relationships between statistical entities.
Generate professional clinical decision support (CDS) documents for pharmaceutical and clinical research settings, including patient cohort analyses (biomarker-stratified with outcomes) and treatment recommendation reports (evidence-based guidelines with decision algorithms). Supports GRADE evidence grading, statistical analysis (hazard ratios, survival curves, waterfall plots), biomarker integration, and regulatory compliance. Outputs publication-ready LaTeX/PDF format optimized for drug develo
MATLAB and GNU Octave numerical computing for matrix operations, data analysis, visualization, and scientific computing. Use when writing MATLAB/Octave scripts for linear algebra, signal processing, image processing, differential equations, optimization, statistics, or creating scientific visualizations. Also use when the user needs help with MATLAB syntax, functions, or wants to convert between MATLAB and Python code. Scripts can be executed with MATLAB or the open-source GNU Octave interpreter
Query Reactome REST API for pathway analysis, enrichment, gene-pathway mapping, disease pathways, molecular interactions, expression analysis, for systems biology studies.
Spreadsheet toolkit (.xlsx/.csv). Create/edit with formulas/formatting, analyze data, visualization, recalculate formulas, for spreadsheet processing and analysis.
This skill should be used when the user asks to "create a BPA rule", "write a Best Practice Analyzer rule", "improve a BPA expression", "fix expression for BPA", "analyze BPA annotations", "check model for best practices", "audit BPA rules", "discover BPA rules", "list all BPA rules", "validate BPA rules", "recommend BPA rules for my model", "help me choose BPA rules", "what BPA rules should I use", "set up BPA for my team", "BPA rules for my organization", or mentions Tabular Editor BPA rules.
Work with labeled multidimensional arrays for scientific data analysis using Xarray. Use when handling climate data, satellite imagery, oceanographic data, or any multidimensional datasets with coordinates and metadata. Ideal for NetCDF/HDF5 files, time series analysis, and large datasets requiring lazy loading with Dask.
Deep planning via Oracle CLI (GPT-5.2 Codex). Use for complex tasks requiring extended thinking (10-60 minutes). Outputs plan.md for planner to transform into specs.
Use when analyzing code structure, researching codebase, investigating architecture, exploring dependencies, creating reports, auditing code quality, or when asked to проанализировать, исследовать, изучить, составить отчёт, провести аудит - provides structured approach for exploration tasks without immediate code changes
Generate professional clinical decision support (CDS) documents for pharmaceutical and clinical research settings, including patient cohort analyses (biomarker-stratified with outcomes) and treatment recommendation reports (evidence-based guidelines with decision algorithms). Supports GRADE evidence grading, statistical analysis (hazard ratios, survival curves, waterfall plots), biomarker integration, and regulatory compliance. Outputs publication-ready LaTeX/PDF format optimized for drug develo
Distributed computing for larger-than-RAM pandas/NumPy workflows. Use when you need to scale existing pandas/NumPy code beyond memory or across clusters. Best for parallel file processing, distributed ML, integration with existing pandas code. For out-of-core analytics on single machine use vaex; for in-memory speed use polars.
NGS analysis toolkit. BAM to bigWig conversion, QC (correlation, PCA, fingerprints), heatmaps/profiles (TSS, peaks), for ChIP-seq, RNA-seq, ATAC-seq visualization.
Comprehensive toolkit for creating, analyzing, and visualizing complex networks and graphs in Python. Use when working with network/graph data structures, analyzing relationships between entities, computing graph algorithms (shortest paths, centrality, clustering), detecting communities, generating synthetic networks, or visualizing network topologies. Applicable to social networks, biological networks, transportation systems, citation networks, and any domain involving pairwise relationships.
Automated LLM-driven hypothesis generation and testing on tabular datasets. Use when you want to systematically explore hypotheses about patterns in empirical data (e.g., deception detection, content analysis). Combines literature insights with data-driven hypothesis testing. For manual hypothesis formulation use hypothesis-generation; for creative ideation use scientific-brainstorming.
Data structure for annotated matrices in single-cell analysis. Use when working with .h5ad files or integrating with the scverse ecosystem. This is the data format skill—for analysis workflows use scanpy; for probabilistic models use scvi-tools; for population-scale queries use cellxgene-census.
Query Reactome REST API for pathway analysis, enrichment, gene-pathway mapping, disease pathways, molecular interactions, expression analysis, for systems biology studies.
Work with Data Commons, a platform providing programmatic access to public statistical data from global sources. Use this skill when working with demographic data, economic indicators, health statistics, environmental data, or any public datasets available through Data Commons. Applicable for querying population statistics, GDP figures, unemployment rates, disease prevalence, geographic entity resolution, and exploring relationships between statistical entities.
MATLAB and GNU Octave numerical computing for matrix operations, data analysis, visualization, and scientific computing. Use when writing MATLAB/Octave scripts for linear algebra, signal processing, image processing, differential equations, optimization, statistics, or creating scientific visualizations. Also use when the user needs help with MATLAB syntax, functions, or wants to convert between MATLAB and Python code. Scripts can be executed with MATLAB or the open-source GNU Octave interpreter
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, Gradient Boosting models, or Survival SVMs, evaluating survival predictions with concordance index or Brier score, handling competing risks, or implementing any survival analysis workflow with the scikit-survival library.
Comprehensive analysis operations for code, skills, processes, data, and patterns. Task-based operations with pattern recognition, metrics calculation, trend identification, and actionable insights generation. Use when analyzing code quality, reviewing skill effectiveness, identifying process improvements, extracting patterns, or generating insights from data.
This skill should be used when the user asks to "run TabularEditor.exe", "deploy a model via CLI", "use Tabular Editor command line", "set up CI/CD for Power BI", "automate model deployment", "run BPA from command line", "save model as TMDL", "compare model schemas", or mentions TabularEditor.exe flags like -D, -S, -A, -B, -T, -O, -C. Provides CLI syntax reference for Tabular Editor 2/3 deployment, scripting, BPA analysis, and CI/CD integration. Distinct from c-sharp-scripting skill which covers
Spreadsheet toolkit (.xlsx/.csv). Create/edit with formulas/formatting, analyze data, visualization, recalculate formulas, for spreadsheet processing and analysis.
Generates professional diagrams for educational flashcards using Python (matplotlib) or Mermaid syntax. Automatically selects the best visualization tool based on diagram type. Use when creating visual aids for flashcards or adding diagrams to learning materials.
Provides quantitative rubrics and criteria for scoring code quality on a 1-10 scale. Use when reviewing code, performing code audits, establishing quality baselines, comparing implementations, or providing objective code feedback.
Create visual diagrams and representations of OSCAL documents including control hierarchies, component relationships, implementation flows, and SSP overviews. Inspired by oscal-diagrams and community visualization tools.
[UI/UX] Visualizes interaction sequences and system communications as ASCII diagrams. Represents user-system interactions, API call sequences, and event flows. Use when requesting 'sequence diagram', 'interaction flow', or 'API sequence'.
Use when user asks about N+1 queries, performance optimization, query optimization, reduce API calls, improve render performance, fix slow code, optimize database, or reduce bundle size. Provides guidance on identifying and fixing performance anti-patterns across database, backend, frontend, and API layers.
Data quality testing with dbt tests, Great Expectations, and monitoring.
Documents HOW code works with surgical precision - traces data flow, explains implementation details, provides file:line references. Purely documentarian, no critiques or suggestions for improvement.
Calculates technical mapping statistics for any aligned BAM file (ChIP or ATAC). It assesses the performance of the aligner itself by generating metrics on read depth, mapping quality, error rates, and read group data using samtools and Picard.Use this skill to check "how well the reads mapped" or to validate BAM formatting/sorting before further processing. Do NOT use this skill for biological signal validation (like checking for peaks or open chromatin) or for filtering/removing reads.
Enriches Excel tables with up-to-date web data using Bright Data MCP tools. Use when the user asks to enrich, update, or add information to spreadsheet data from LinkedIn, Instagram, Amazon, e-commerce sites, social media, or any web source. Supports company profiles, product data, social media metrics, reviews, and more.
