supeRpowers

Plugin supeRpowers from marketplace supeRpowers in alexvantwisk/supeRpowers. Commands read from the repo's manifest — 1 month ago.

Skills (26)

• r-analysis

  Guided data analysis pipeline — import, clean, explore, model, visualize, report

• r-bayesian

  Use when fitting Bayesian models, specifying priors, running MCMC, or summarizing posteriors in R using brms, rstanarm, cmdstanr, posterior, or tidybayes. Provides expert guidance on the prior-fit-diagnose-summarize workflow, weakly-informative prior choice, prior predictive checks, Hamiltonian Mont

• r-clinical

  Use when performing clinical trial analysis, biostatistics, regulatory submissions, or biomedical research in R. Provides expert guidance on trial design, CDISC standards (ADaM, SDTM), survival endpoints, Kaplan-Meier analysis, biomarker evaluation, power analysis, meta-analysis, and TLF generation

• r-data-analysis

  Use when working with data wrangling, cleaning, transformation, reshaping, or import in R using dplyr, tidyr, readr, lubridate, stringr, forcats, or purrr. Provides expert guidance on tidy data principles, column manipulation, joins, type conversion, string and date processing, factor reordering, li

• r-debug

  Guided debugging workflow — reproduce, isolate, diagnose, fix, regression test, verify

• r-debugging

  Use when diagnosing bugs, errors, or unexpected behavior in R code. Provides a systematic reproduce-isolate-diagnose-fix-test workflow covering browser(), traceback(), debug(), condition handling, and common R pitfalls for both interactive scripts and package code. Do NOT use for performance profili

• r-mcp-setup

  Use when the user wants to set up MCP tools for R — connecting Claude Code to a persistent agent-owned R session via mcp-repl, or to a live IDE R session via mcptools + btw. Covers installing mcp-repl (PyPI, install script, cargo, or prebuilt tarball), wiring it with `mcp-repl install`, sandbox and

• r-overview

  Use when the user asks what supeRpowers can do, requests a list or directory of available R skills / workflows / agents, or asks for an overview of the plugin — discovery-only intent, not actual R work. Renders a one-page inventory of the 26 skills (20 knowledge + 6 workflow) and 5 agents shipped he

• r-package-dev

  Use when creating, developing, documenting, or submitting R packages. Provides full-lifecycle guidance on usethis, devtools, roxygen2, pkgdown, NAMESPACE management, DESCRIPTION metadata, vignettes, CRAN submission, and CI/CD workflows. Do NOT use for initial project scaffolding only — use r-project

• r-package-skill-generator

  Use when the user provides a GitHub link to an R package and wants to generate a Claude skill from it, or asks Claude to become an expert at using a specific R package. Automates cloning, exploration via parallel sub-agents, and assembly of a complete SKILL.md with references from any public R packa

• r-performance

  Use when optimizing R code for speed or memory. Provides a profile-first methodology covering bench, profvis, data.table, vectorization, Rcpp, parallel processing, memory management, and proof-of-improvement benchmarks. Do NOT use for general data wrangling at normal scale — use r-data-analysis inst

• r-pkg-release

  Guided R package release workflow — audit deps, test, document, R CMD check, version bump, review, submit

• r-project-setup

  Use when setting up, initializing, or scaffolding a new R project, package, Shiny app, or Quarto document. Provides best-practice templates for directory structure, renv dependency management, .Rprofile configuration, git setup, and CI scaffolding for any R project type. Do NOT use for ongoing packa

• r-quarto

  Use when creating Quarto documents, presentations, websites, books, reusable templates and format extensions, or Word (.docx) output in R. Provides expert guidance on YAML configuration, code chunk options, cross-references, journal templates, reference docs (docx/pptx), custom format extensions, te

• r-report

  Scaffold and render a clean, minimalist Word (.docx) report from an R analysis

• r-reporting

  Use when producing a consulting or clinical Word (.docx) report as a deliverable in R — assembling the report's content and wiring the reproducible project pipeline that renders it through Quarto. Covers report structure and statistical content (sections, the ICH E9(R1) estimand framework, prespecif

• r-shiny-app

  Guided Shiny app workflow — scaffold, design modules, wire reactivity, test, architecture review

• r-shiny

  Use when building, structuring, testing, or deploying R Shiny apps, including framework choice across base Shiny, golem, rhino, and teal (pharma-standard for CDISC ADaM/SDTM dashboards). Covers reactivity, modules, bslib UI with shinydashboard migration, reactive data-flow, render wrappers (Plot/Plo

• r-stats

  Use when performing statistical modeling, hypothesis testing, or model diagnostics in R. Provides expert guidance on linear models, GLMs, mixed models, survival analysis, time series, model comparison, assumption checking, and effect-size reporting. Do NOT use for machine learning or predictive mode

• r-tables

  Use when creating publication-quality tables in R with gt, gtsummary, gtExtras, or reactable. Provides expert guidance on summary tables, regression tables, demographic Table 1 layouts, journal themes, conditional formatting, sparklines, and multi-format output to HTML, PDF, and Word. Do NOT use for

• r-targets

  Use when creating reproducible analysis pipelines, managing computational workflows, or using the targets package for pipeline orchestration in R. Provides expert guidance on target definitions, static and dynamic branching, dependency graphs, caching, cloud storage backends, and integration with re

• r-tdd-cycle

  Guided TDD workflow — Red, Green, Refactor, Review for R packages using testthat 3e

• r-tdd

  Use when writing or running tests for R code, setting up testthat, or following TDD workflow in R packages or scripts. Provides expert guidance on the red-green-refactor cycle, testthat 3rd edition, snapshot tests, mocking, fixtures, test coverage, and test organization patterns. Do NOT use for R CM

• r-tidymodels

  Use when building machine learning models, predictive modeling, or model tuning in R using tidymodels, recipes, workflows, tune, or yardstick. Provides expert guidance on the split-preprocess-model-tune-evaluate pipeline, feature engineering with recipes, hyperparameter tuning, cross-validation, and

• r-visualization

  Use when creating plots, charts, figures, or visualizations in R with ggplot2 and its ecosystem — patchwork, scales, ggrepel, ggtext, ggdist, ggridges, ggbeeswarm, gghighlight, ggforce, ggh4x, ggsurvfit, ggsci, plotly, ggiraph, gganimate. Covers grammar of graphics, publication-quality figures, mult

• skill-auditor

  Use when auditing, reviewing, or improving Claude Code skills against best practices. Scores any skill folder against a 38-check rubric covering description quality, content efficiency, gotchas, examples, scripts, multi-skill orchestration, and testability. Do NOT use for creating new skills from sc

Subagents (5)

• r-code-reviewer

  Use when reviewing R code for style, correctness, performance, and documentation against supeRpowers conventions (base pipe |>, tidyverse-first, snake_case, double quotes). Supports full reviews or focused style-only and performance passes.

• r-dependency-manager

  Use when managing R dependencies with renv — audits packages, resolves version conflicts, handles Bioconductor and CRAN coexistence, and ensures reproducible environments. Supports setup, conflict resolution, audit, and Bioconductor-focused workflows.

• r-pkg-check

  Use when R CMD check produces errors, warnings, or notes on an R package — parses check output, diagnoses root causes, and provides specific fixes with usethis/devtools commands. Covers full and CRAN-stricter check modes.

• r-shiny-architect

  Use when reviewing Shiny application structure — evaluates module decomposition, reactivity patterns, performance bottlenecks, security, and framework adherence. Supports full reviews or focused passes on performance, modularity, or security.

• r-statistician

  Use when needing statistical consultation in R — model selection, assumption verification, result interpretation, or methodological risk assessment. Covers frequentist and Bayesian approaches with biostatistics depth for survival, mixed-effects, GLM, and clinical analyses.

Hooks (2)

• SessionStart

  "${CLAUDE_PLUGIN_ROOT}/hooks/run-hook.cmd" session-start

• PostToolUse

  "${CLAUDE_PLUGIN_ROOT}/hooks/run-hook.cmd" post-tool-use-format

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