Search Skills

Provides automated code review for OpenShift CLI (oc) PRs, including build, test, linting, Go style improvements, and detailed feedback.

Enforces standardized commit message formats and safety rules prior to creating a Git commit, ensuring consistency and quality in version control.

Provides a usage guide for global feedback components including Toast, Message, and Loading in frontend applications.

Provides a usage guide for the lightweight routing library @wot-ui/router, helping developers implement navigation in frontend applications.

Removes example content and monorepo configurations from wot-starter to generate a minimal, clean project template for immediate development.

Quickly generates uni-app pages according to project specifications, accelerating cross-platform frontend development.

Generates Alova-based API request modules and mock data for efficient frontend development and testing workflows.

Generates Vue.js Pinia stores adhering to project-specific coding standards and structure.

Generates Vue 3 composition functions (composables) to streamline frontend development with the Composition API.

Expert code review for Go, ensuring idiomatic practices, concurrency safety, and clean code architecture. Activates on 'review', 'idiomatic', and 'refactor'.

Specializes in building and maintaining robust HTTP services and RESTful APIs using the Go programming language.

Provides expert guidance on Go testing patterns including table-driven tests, httptest, benchmarking, and fuzzing.

Automates Go project setup with standard directory structure and dependency management for new projects.

Generates tailored prompts for content creation using a 3-step agent pipeline (analysis, structure, generation).

Automates conventional commit message generation and execution with user confirmation upon '/commit' command.

Automates adding translated Korean Markdown files to readings.ts, parsing content into ReadingContent objects and updating syllabus data for web publication.

Translates source reading content into Korean Markdown using a multi-step quality pipeline, including YouTube chapter summaries.

Automates session cleanup, suggests CLAUDE.md updates, and identifies repetitive task automation opportunities upon user request.

Validates cheat sheet images against corresponding markdown files using Gemini Vision to detect technical errors, text discrepancies, and visual inaccuracies.

Evaluates summary field quality in readings.ts against original Korean markdown, proposes improvements, and updates code after user confirmation.

Verifies Korean translation quality via AI cross-validation, assessing accuracy, naturalness, and terminology consistency.

Verifies AI prompts against Korean translations, fact-checks via WebSearch, and secures user confirmation before modifications.

Automates copying cheat sheet images to public directory and updating readings.ts with image path.

Automates creation of chapter-based subpage structures in readings.ts and splits master translation files into chapter-specific files for YouTube content.