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Found 513 Skills
Apply production-ready best practices for weapp-vite projects. Use when creating or refactoring mini-program projects with weapp-vite, designing directory/config conventions, choosing subpackage and chunk strategy, enabling auto routes/components, setting CI/devtool workflows, or debugging build/output issues in `vite.config.ts` and `app.json`.
Workflow orchestration for complex coding tasks. Use for ANY non-trivial task (3+ steps or architectural decisions) to enforce planning, subagent strategy, self-improvement, verification, elegance, and autonomous bug fixing. Triggers: multi-step implementation, bug fixes, refactoring, architectural changes, or any task requiring structured execution.
React performance optimization guidelines for Single Page Applications (SPA) at Workleap. Use when writing, reviewing, or refactoring React SPA code to ensure optimal performance patterns. Triggers on tasks involving React components, state management, bundle optimization, re-render prevention, rendering performance, or JavaScript performance improvements. Covers async waterfall elimination, bundle size reduction, re-render optimization, rendering efficiency, JS micro-optimizations, and advanced React patterns. Does NOT cover server-side rendering (SSR), Next.js, or server components.
Ember.js performance optimization and accessibility guidelines. This skill should be used when writing, reviewing, or refactoring Ember.js code to ensure optimal performance patterns and accessibility. Triggers on tasks involving Ember components, routes, data fetching, bundle optimization, or accessibility improvements.
Evaluate and improve code modularization using the Balanced Coupling Model. Analyzes coupling strength, connascence types, and distance to identify refactoring opportunities and architectural improvements. Use when reviewing code architecture, refactoring modules, or designing new systems.
Systematic code refactoring following Martin Fowler's catalog. Methodologies: characterization tests, Red-Green-Refactor, incremental transformation. Capabilities: SOLID compliance, DRY cleanup, code smell detection, complexity reduction, legacy modernization, design patterns, functional programming patterns. Actions: refactor, extract, inline, rename, move, simplify code. Keywords: refactor, SOLID, DRY, code smell, complexity, extract method, inline, rename, move, clean code, technical debt, legacy code, design pattern, characterization test, Red-Green-Refactor, functional programming, higher-order function, immutability, pure function, composition, currying, side effects. Use when: improving code quality, reducing technical debt, applying SOLID principles, fixing DRY violations, removing code smells, modernizing legacy code, applying design patterns.
Swift/iOS static analysis CLI. Use `depgraph` to find who calls a function, what breaks if you change a file, track call sites and blast radius before refactoring, and map symbol dependencies across files. Use `ask` to consult Swift/iOS/tvOS/watchOS/macOS documentation and best practices.
Full-stack development skill with six-layer architecture, supporting cross-layer modifications initiated from any layer. It automatically coordinates the collaboration of six layers: UI Layer/Frontend Service Layer/Frontend API Layer/Backend API Layer/Backend Service Layer/Data Layer, enabling cross-layer consistent code generation and refactoring. Suitable for Vue3+FastAPI+PostgreSQL tech stack
Design System Governance Workflow for auditing, refactoring, and syncing enterprise design systems, design tokens, Figma variables, and developer handoff outputs.
Red-green-refactor development methodology requiring verified test coverage. Use for feature implementation, bugfixes, refactoring, or any behavior changes where tests must prove correctness.
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.
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.