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Found 817 Skills
Assesses and responds to incoming code review feedback on PRs (reviewer comments, requested changes), especially when suggestions are unclear, technically questionable, or scope-expanding. Use before implementing review suggestions to align on intent and keep changes minimal.
Verification discipline for completion claims. Use when about to assert success, claim a fix is complete, report tests passing, or before commits and PRs. Enforces evidence-first workflow.
Clean Code, Dart Guidelines & Documentation
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.
Python coding standards with automatic version detection. Use when writing, reviewing, or refactoring Python to ensure adherence to LBYL exception handling patterns, modern type syntax (list[str], str | None), pathlib operations, ABC-based interfaces, absolute imports, and explicit error boundaries at CLI level. Also provides production-tested code smell patterns from Dagster Labs for API design, parameter complexity, and code organization. Essential for maintaining erk's dignified Python standards.