Explora nuestra colección completa de Habilidades de Claude que extienden las capacidades de los agentes de IA.
Automates data quality testing and results analysis using dbt and dbt-expectations to maintain high-integrity data pipelines.
Provides a prioritized framework and actionable fixes for security vulnerabilities, technical debt, and repository hygiene in audit reports.
Performs comprehensive MCMC diagnostic checks and posterior predictive assessments for Bayesian models implemented in Stan or JAGS.
Streamlines data preprocessing and feature engineering using R's Tidymodels recipes framework.
Analyzes R machine learning code to detect data leakage, resampling violations, and workflow anti-patterns using tidymodels principles.
Optimizes and refactors dbt models to improve SQL performance and data transformation efficiency.
Analyzes dbt project structures, lineage, and dependencies using a multi-agent RAG workflow to automate documentation and code generation.
Optimizes React application development through standardized hooks, composition patterns, and performance-tuned implementation strategies.
Optimizes AI coding performance by applying principles of context window management, token budgeting, and signal-to-noise ratio.
Performs comprehensive Bayesian statistical modeling and posterior analysis using Stan-based R packages like brms and rstanarm.
Standardizes the creation of high-quality, CRAN-compliant documentation for R packages and biostatistical projects.
Implements hierarchical and multilevel Bayesian models with optimized parameterizations for robust statistical inference.
Manages complex PDF operations including text extraction, document merging, table parsing, and automated PDF generation using Python and CLI tools.
Transforms product requirements into structured, INVEST-compliant Agile user stories and visual business flowcharts.
Optimizes clinical trial designs through advanced sample size determination, event count tuning, and multi-objective tradeoff analysis.
Performs comprehensive epidemiological analysis in R, covering study designs, causal inference, and measures of association.
Automates the generation of ER diagrams, lineage charts, and metadata reports for DBT projects using dbterd and Mermaid.
Automates dbt data quality testing and provides intelligent analysis of test failures and remediation steps.
Simulates time-to-event clinical trial data and performs complex statistical analyses including weighted logrank and MaxCombo tests.
Provides foundational knowledge and best practices for developing, optimizing, and reviewing Stan 2.37 probabilistic models.
Implements comprehensive machine learning pipelines in R using the tidymodels ecosystem, from data preprocessing to model deployment.
Implements a Test-Driven Development (TDD) approach to creating, testing, and optimizing high-performance documentation for AI agents.
Standardizes Indirect Treatment Comparison (ITC) analyses in R using tidy modeling principles and reproducible workflow patterns.
Translates natural language into precise DBT semantic layer queries with automated filtering, visualization, and context-aware data exploration.
Provisions and manages isolated Docker-based Ignition gateway environments for streamlined development and testing.
Executes complex implementation plans through a structured, batch-based workflow with mandatory human review checkpoints.
Standardizes the way Claude processes and implements code review feedback with a focus on technical verification and rigor over performative agreement.
Implements and simulates complex adaptive clinical trial designs using industry-standard R packages like adaptr, rpact, and RBesT.
Generates and executes high-performance SQL queries directly from natural language using your dbt project schema.
Manage the complete Git lifecycle from repository initialization to advanced team collaboration and conflict resolution.
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