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Found 225 Skills
Generates comprehensive API test suites using Jest, Vitest, or Supertest from Express, Next.js, Fastify, or other API routes. Creates integration tests, contract tests, and edge case coverage. Use when users request "generate api tests", "create endpoint tests", "api test suite", or "integration tests for api".
Expert-level Tableau Desktop/Server, calculated fields, LOD expressions, dashboards, data blending, and performance optimization
n8n expression syntax validation, context-aware testing, common pitfalls detection, and performance optimization. Use when validating n8n expressions and data transformations.
Create and debug Home Assistant automations, scripts, blueprints, and Jinja2 templates. Use when working with triggers, conditions, actions, automation YAML, scripts, blueprints, or template expressions. Activates on keywords: automation, trigger, condition, action, blueprint, script, template, jinja2.
Expert patterns for AnimationTree including StateMachine transitions, BlendSpace2D for directional movement, BlendTree for layered animations, root motion, transition conditions, advance expressions, and state machine sub-states. Use for complex character animation systems with movement blending and state management. Trigger keywords: AnimationTree, AnimationNodeStateMachine, BlendSpace2D, BlendSpace1D, BlendTree, transition_request, blend_position, advance_expression, AnimationNodeAdd2, AnimationNodeBlend2, root_motion.
Schedules Claude Code tasks to run automatically at specific times using native OS schedulers (launchd on macOS, crontab on Linux, Task Scheduler on Windows). Handles one-time tasks like "today at 3pm remind me to deploy", "tomorrow morning run the test suite", "next Tuesday at 2pm review the API changes", "January 15th check the quarterly metrics". Also handles recurring tasks like "every weekday at 9am review yesterday's code", "daily at 6pm summarize what I accomplished", "every Monday at 10am check for security vulnerabilities", "every 4 hours check API health". Recognizes time formats like "at 9am", "at 1015am", "at 10:30pm", "at noon", relative times like "tomorrow", "tonight", "later", "next week", and dates like "January 15th". Use this skill instead of executing immediately whenever the user's request contains a time expression like "at Xam", "tomorrow", or any future time reference.
Create a delightful, unexpected "wow" experience for the user by dynamically discovering and creatively combining other enabled skills. Triggers when the user says "surprise me" or any request expressing a desire for an unexpected creative showcase. Also triggers when the user is bored, wants inspiration, or asks for "something interesting".
Walk Claude through PyDESeq2-based differential expression, including ID mapping, DE testing, fold-change thresholding, and enrichment visualisation.
Comprehensive patient stratification for precision medicine by integrating genomic, clinical, and therapeutic data. Given a disease/condition, genomic data (germline variants, somatic mutations, expression), and optional clinical parameters, performs multi-phase analysis across 9 phases covering disease disambiguation, genetic risk assessment, disease-specific molecular stratification, pharmacogenomic profiling, comorbidity/DDI risk, pathway analysis, clinical evidence and guideline mapping, clinical trial matching, and integrated outcome prediction. Generates a quantitative Precision Medicine Risk Score (0-100) with risk tier assignment (Low/Intermediate/High/Very High), treatment algorithm (1st/2nd/3rd line), pharmacogenomic guidance, clinical trial matches, and monitoring plan. Use when clinicians ask about patient risk stratification, treatment selection, prognosis prediction, or personalized therapeutic strategy across cancer, metabolic, cardiovascular, neurological, or rare diseases.
Analyze spatial transcriptomics data to map gene expression in tissue architecture. Supports 10x Visium, MERFISH, seqFISH, Slide-seq, and imaging-based platforms. Performs spatial clustering, domain identification, cell-cell proximity analysis, spatial gene expression patterns, tissue architecture mapping, and integration with single-cell data. Use when analyzing spatial transcriptomics datasets, studying tissue organization, identifying spatial expression patterns, mapping cell-cell interactions in tissue context, characterizing tumor microenvironment spatial structure, or integrating spatial and single-cell RNA-seq data for comprehensive tissue analysis.
Integrate and analyze multiple omics datasets (transcriptomics, proteomics, epigenomics, genomics, metabolomics) for systems biology and precision medicine. Performs cross-omics correlation, multi-omics clustering (MOFA+, NMF), pathway-level integration, and sample matching. Coordinates ToolUniverse skills for expression data (RNA-seq), epigenomics (methylation, ChIP-seq), variants (SNVs, CNVs), protein interactions, and pathway enrichment. Use when analyzing multi-omics datasets, performing integrative analysis, discovering multi-omics biomarkers, studying disease mechanisms across molecular layers, or conducting systems biology research that requires coordinated analysis of transcriptome, genome, epigenome, proteome, and metabolome data.
Analyze mass spectrometry proteomics data including protein quantification, differential expression, post-translational modifications (PTMs), and protein-protein interactions. Processes MaxQuant, Spectronaut, DIA-NN, and other MS platform outputs. Performs normalization, statistical analysis, pathway enrichment, and integration with transcriptomics. Use when analyzing proteomics data, comparing protein abundance between conditions, identifying PTM changes, studying protein complexes, integrating protein and RNA data, discovering protein biomarkers, or conducting quantitative proteomics experiments.