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Found 1,079 Skills
Run after making Docyrus API changes to catch bugs, performance issues, and code quality problems. Use when implementing or modifying code that uses Docyrus collection hooks (.list, .get, .create, .update, .delete), direct RestApiClient calls, query payloads with filters/calculations/formulas/childQueries/pivots, or TanStack Query integration with Docyrus data sources. Triggers on tasks involving Docyrus API logic, data fetching, mutations, or query payload construction.
Auto-fix CodeRabbit review comments - get CodeRabbit review comments from GitHub and fix them interactively or in batch
Analyse PHP code with PHPStan via the playground API. Tests across all PHP versions (7.2–8.5) and reports errors grouped by version. Supports configuring level, strict rules, and bleeding edge.
Review Go code for language and runtime conventions: concurrency, context usage, error handling, resource management, API stability, type semantics, and testability. Language-only atomic skill; output is a findings list.
Keep cyclomatic complexity low; flatten control flow, extract helpers, and prefer table-driven/strategy patterns over large switches
Review PowerShell code for language and runtime conventions: advanced functions, parameter design, error handling, object pipeline behavior, compatibility, and testability. Language-only atomic skill; output is a findings list.
Iteratively review changes, run automated tests, and apply targeted fixes until issues are resolved (or a stop condition is reached).
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.
Scans codebases for technical debt with AST parsing, prioritizes debt items by impact, and generates trend dashboards. Use when tracking tech debt, prioritizing refactoring, or measuring code quality trends over time.
Adversarial code review using the opposite model. Spawns 1–3 reviewers on the opposing model (Claude spawns Codex, Codex spawns Claude) to challenge work from distinct critical lenses. Triggers: "adversarial review".
Comprehensive code investigation and audit tool. Discovers all project features, then dispatches parallel subagents to analyze issues, risks, dead code, missing functionality, and redundancies. Produces a prioritized risk report. Use this skill when the user asks to "investigate code", "audit project", "find risks", "check code quality", "analyze codebase", "what's wrong with this code", "project health check", "code review entire project", "find dead code", "find redundant code", or any request for a thorough codebase analysis.
Type-driven design principle: transform unstructured data into structured types at system boundaries, making illegal states unrepresentable. Use when writing or reviewing code that validates input, designs data types, defines function signatures, handles errors, or models domain logic. Use when you see validation functions that return void/undefined, redundant null checks, stringly-typed data, boolean flags controlling behavior, or functions that can receive data they shouldn't. Triggers on: "parse don't validate", "type-driven design", "make illegal states unrepresentable", "input validation", "data modeling", "refactor types", "strengthen types", "smart constructor", "newtype", "branded type".