Checks blocking IO in async, unnecessary allocations, sync sleep, string concat in loops, missing to_thread, redundant copies. Returns findings with severity and effort.

Audits layer boundaries + cross-layer consistency: I/O violations, transaction boundaries (commit ownership), session ownership (DI vs local).

Frontend structure worker: SCAFFOLD new React project or RESTRUCTURE existing monolith to component-based architecture

Creates reference documentation structure + smart documents (ADRs/Guides/Manuals) based on TECH_STACK. Only creates justified documents (nontrivial technology choices).

Test suite audit coordinator: automated + manual tests. Delegates to 7 workers (Business Logic, E2E, Value, Coverage, Isolation, Manual Quality, Structure). Output: docs/project/test_audit.md.

Checks transaction scope, missing rollback handling, long-held transactions, trigger/notify interaction. Returns findings with severity, location, effort.

Executes all test suites and reports results with coverage

Detects and fixes accessibility issues in React/Fluent UI webviews. Use when reviewing code for screen reader compatibility, fixing ARIA labels, ensuring keyboard navigation, adding live regions for status messages, or managing focus in dialogs.

Record real OpenAI/Anthropic HTTP back-and-forth (requests + responses, including streaming text/event-stream) and print paste-ready Swift fixtures for SwiftAgent unit tests (ReplayHTTPClient) using the AgentRecorder CLI or HTTPReplayRecorder. Use when adding/updating any provider adapter tests (text, streaming, structured outputs, tool calls), when payload formats change, or when debugging agent loop mismatches by inspecting recorded JSON/SSE payloads.

Azure Cosmos DB performance optimization and best practices guidelines for NoSQL, partitioning, queries, and SDK usage. Use when writing, reviewing, or refactoring code that interacts with Azure Cosmos DB, designing data models, optimizing queries, or implementing high-performance database operations.

Designs integration and E2E tests with mock boundaries and behavior verification rules. Use when writing E2E or integration tests.

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.

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.

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.

AI agent governance, trust scoring, and policy enforcement powered by AgentMesh. Activate when: (1) user wants to enforce token limits, tool restrictions, or content policies on agent actions, (2) checking an agent's trust score before delegation or collaboration, (3) verifying agent identity with Ed25519 cryptographic DIDs, (4) auditing agent actions with tamper-evident hash chain logs, (5) user asks about agent safety, governance, compliance, or trust. Enterprise-grade: 1,600+ tests, merged into Dify (65K★), LlamaIndex (47K★), Microsoft Agent-Lightning (15K★).

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 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.

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.

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.

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.