Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
101 skills found
Automated single-cell RNA-seq quality control pipeline following scverse best practices. Performs MAD-based outlier detection, cell filtering, and diagnostic visualization for .h5ad and .h5 datasets.
Analyze product performance using KPI frameworks, cohort analysis, and funnel metrics to drive growth, retention, and feature adoption.
Evaluate scientific claims and research methodology for rigor, bias, and validity. Use evidence-based frameworks like GRADE and Cochrane to analyze experiments, protocols, and study conclusions.
Generate, validate, and refine Mermaid diagrams including flowcharts, sequence diagrams, ERDs, and architecture maps to visualize complex software systems and workflows.
Comprehensive biosignal processing toolkit for ECG, EEG, EDA, RSP, PPG, EMG, and EOG signal analysis, enabling psychophysiology research and multi-modal integration.
Build, audit, and iterate high-converting landing pages using React, Vite, TypeScript, Tailwind, and shadcn/ui. Expert in CRO, hero structures, and conversion-focused design with Iconify icons.
Analyze periodic signals in unevenly sampled astronomical time series data using the Lomb-Scargle periodogram method with the lightkurve library.
Reactive UI patterns for remote data fetching, enabling smooth in-place updates, persistent scroll position, and efficient loading state management using the .current property.
Expert LangGraph architect skill for designing stateful, multi-actor AI agent workflows with robust persistence, conditional branching, and ReAct patterns.
Best practices and code patterns for ManimGL (3Blue1Brown's OpenGL animation engine). Provides templates, rules for 3D/interactive scenes, camera control, and LaTeX math visualization for technical creators.
Analyze geospatial data using GeoPandas with proper coordinate projections for accurate distance, filtering, and spatial relationship calculations.
Classical machine learning with scikit-learn. Use for classification, regression, clustering, dimensionality reduction, preprocessing, model evaluation, and building robust ML pipelines in Python.