claude-skills

Use multiple sub-agents to fetch and display news from Posit, including blog posts, podcast episodes, videos, and events. Use when the user wants to see recent Posit news, blog updates, podcast episodes, videos, or company announcements.

Type-stable vector operations and custom vector classes using vctrs. Use this skill when building R packages with custom types, need guaranteed output types regardless of input values, implementing consistent coercion/casting rules, or creating vector classes that work seamlessly with data frames. Covers when to use vctrs vs base R, building custom vector classes, coercion methods, and testing vctrs classes.

Object-oriented programming in R: S7, S3, S4, and vctrs class design. Use this skill when designing classes for R projects, choosing between OOP systems, building class hierarchies with inheritance, or migrating between systems. Covers S7 class definitions and methods, the decision matrix for choosing S7 vs S3 vs S4 vs vctrs, practical guidelines for each system, and migration strategies.

Building robust R packages with modern tidyverse patterns. Use this skill when creating or maintaining R packages, designing APIs, choosing dependencies, implementing input validation, writing error messages, or deciding between internal and exported functions. Covers dependency strategy, tidyverse API design patterns, validation approaches, error handling with cli/rlang, testing levels, and documentation priorities.

Tidy evaluation and programmatic tidyverse patterns using rlang. Use this skill when writing functions that accept column names as arguments, building tidyverse-compatible APIs, or working with data-masking and injection operators. Covers embracing with {{}}, injection (!! and !!!), dynamic dots, .data/.env pronouns, name injection with glue syntax, bridge patterns between selection and data-masking, and package development with rlang.

R performance profiling, benchmarking, and optimization strategies. Use this skill when code is running slowly, comparing alternative implementations, deciding between dplyr/data.table/base R, or implementing parallel processing. Covers profvis and bench usage, performance workflow, parallel processing with in_parallel(), data backend selection, modern purrr patterns (list_rbind, walk), and common performance anti-patterns to avoid.

Modern tidyverse patterns, style guide, and migration guidance for R development. Use this skill when writing R code with dplyr, reviewing tidyverse code, updating legacy R code to modern patterns, or enforcing consistent style. Covers native pipe usage, join_by() syntax, .by grouping, pick/across/reframe operations, tidy selection, stringr patterns, naming conventions, spacing, and migration from base R or older tidyverse APIs.