Comprehensive R package for command-line interface styling, semantic messaging, and user communication. Use this skill when working with R code that needs to: (1) Format console output with inline markup and colors, (2) Display errors, warnings, or messages with cli_abort/cli_warn/cli_inform, (3) Show progress indicators for long-running operations, (4) Create semantic CLI elements (headers, lists, alerts, code blocks), (5) Apply themes and customize output styling, (6) Handle pluralization in user-facing text, (7) Work with ANSI strings, hyperlinks, or custom containers. Also use when migrating from base R message/warning/stop, debugging cli code, or improving existing cli usage.

Create and use brand.yml files for consistent branding across Shiny apps and Quarto documents. Use when working with brand styling, colors, fonts, logos, or corporate identity in Shiny or Quarto projects. Covers: (1) Creating new _brand.yml files from brand guidelines, (2) Applying brand.yml to Shiny for R apps with bslib, (3) Applying brand.yml to Shiny for Python apps with ui.Theme, (4) Using brand.yml in Quarto documents, presentations, dashboards, and PDFs, (5) Modifying existing brand.yml files, (6) Troubleshooting brand integration issues. Includes complete specifications and framework-specific integration guides.

Best practices for writing R package tests using testthat version 3+. Use when writing, organizing, or improving tests for R packages. Covers test structure, expectations, fixtures, snapshots, mocking, and modern testthat 3 patterns including self-sufficient tests, proper cleanup with withr, and snapshot testing.

Guidance for managing R package lifecycle according to tidyverse principles using the lifecycle package. Use when: (1) Setting up lifecycle infrastructure in a package, (2) Deprecating functions or arguments, (3) Renaming functions or arguments, (4) Superseding functions, (5) Marking functions as experimental, (6) Understanding lifecycle stages (stable, experimental, deprecated, superseded), or (7) Writing deprecation helpers for complex scenarios.

Conduct rigorous, adversarial code reviews with zero tolerance for mediocrity. Use when users ask to "critically review" my code or a PR, "critique my code", "find issues in my code", or "what's wrong with this code". Identifies security holes, lazy patterns, edge case failures, and bad practices across Python, R, JavaScript/TypeScript, SQL, and front-end code. Scrutinizes error handling, type safety, performance, accessibility, and code quality. Provides structured feedback with severity tiers (Blocking, Required, Suggestions) and specific, actionable recommendations.

Create a release checklist and GitHub issue for an R package. Use when the user asks to "create a release checklist" or "start a release" for an R package.

Research a codebase and create architectural documentation describing how features or systems work. Use when the user asks to: (1) Document how a feature works, (2) Create an architecture overview, (3) Explain code structure for onboarding or knowledge transfer, (4) Research and describe a system's design. Produces markdown documents with Mermaid diagrams and stable code references suitable for humans and AI agents.

Prepare R packages for CRAN submission by checking for common ad-hoc requirements not caught by devtools::check(). Use when: (1) Preparing a package for first CRAN release, (2) Preparing a package update for CRAN resubmission, (3) Reviewing a package to ensure CRAN compliance, (4) Responding to CRAN reviewer feedback. Covers documentation requirements, DESCRIPTION field standards, URL validation, examples, and administrative requirements.

**Skill Name:**

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Provides AWS CloudFormation patterns for CloudWatch monitoring, metrics, alarms, dashboards, logs, and observability. Use when creating CloudWatch metrics, alarms, dashboards, log groups, log subscriptions, anomaly detection, synthesized canaries, Application Signals, and implementing template structure with Parameters, Outputs, Mappings, Conditions, cross-stack references, and CloudWatch best practices for monitoring production infrastructure.

Provides patterns for unit testing external REST APIs using WireMock to mock HTTP endpoints. Use when testing service integrations with external APIs.

Provides AWS CloudFormation patterns for Amazon Bedrock resources including agents, knowledge bases, data sources, guardrails, prompts, flows, and inference profiles. Use when creating Bedrock agents with action groups, implementing RAG with knowledge bases, configuring vector stores, setting up content moderation guardrails, managing prompts, orchestrating workflows with flows, and configuring inference profiles for model optimization.

Provides patterns for unit testing utility/helper classes and static methods. Validates pure functions and helper logic. Use when verifying utility code correctness.

Provides patterns for unit testing @ConfigurationProperties classes with @ConfigurationPropertiesTest. Use when validating application configuration binding and validation.

Provides patterns for unit testing REST controllers using MockMvc and @WebMvcTest. Validates request/response mapping, validation, and exception handling. Use when testing web layer endpoints in isolation.

Provides patterns for unit testing Jakarta Bean Validation (@Valid, @NotNull, @Min, @Max, etc.) with custom validators and constraint violations. Validates logic without Spring context. Use when ensuring data integrity and validation rules are correct.

Provides comprehensive NestJS framework patterns with Drizzle ORM integration. Use when building NestJS applications, setting up APIs, implementing authentication, working with databases, or integrating Drizzle ORM. Covers controllers, providers, modules, middleware, guards, interceptors, testing, microservices, GraphQL, and database patterns.

Provides patterns for unit testing mappers and converters (MapStruct, custom mappers). Validates object transformation logic in isolation. Use when ensuring correct data transformation between DTOs and domain objects.

Provides patterns for unit testing scheduled and async tasks using @Scheduled and @Async. Handles mocking task execution and timing. Use when validating asynchronous operations and scheduling behavior.