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Found 183 Skills
Turn a finished, failed, or disappointing work cycle into portable lessons, anti-patterns, quality gates, and next-cycle vocabulary. Use after a build, QA pass, demo, user complaint, or abandoned attempt when the useful output is what the next pass must learn rather than the code itself.
Use when reviewing code for anti-patterns. Keywords: anti-pattern, common mistake, pitfall, code smell, bad practice, code review, is this an anti-pattern, better way to do this, common mistake to avoid, why is this bad, idiomatic way, beginner mistake, fighting borrow checker, clone everywhere, unwrap in production, should I refactor, 反模式, 常见错误, 代码异味, 最佳实践, 地道写法
Review Encore.ts code for best practices and anti-patterns.
Use when you need to set up, review, or improve Java integration tests — including generating a BaseIntegrationTest.java with WireMock for HTTP stubs, detecting HTTP client infrastructure from import signals, injecting service coordinates dynamically via System.setProperty(), creating WireMock JSON mapping files with bodyFileName, isolating stubs per test method, verifying HTTP interactions, or eliminating anti-patterns such as Mockito-mocked HTTP clients or globally registered WireMock stubs. Part of the skills-for-java project
Turborepo monorepo architecture decisions and anti-patterns. Use when: (1) choosing between monorepo vs polyrepo, (2) deciding when to split packages, (3) debugging cache misses, (4) setting package boundaries, (5) avoiding circular dependencies. NOT for CLI syntax (see turbo --help). Focuses on architectural decisions that prevent monorepo sprawl and maintenance nightmares. Triggers: turborepo, monorepo, package boundaries, when to split packages, turbo cache miss, circular dependency, workspace organization, task dependencies.
Use when clarifying fuzzy boundaries, defining quality criteria, teaching by counterexample, preventing common mistakes, setting design guardrails, disambiguating similar concepts, refining requirements through anti-patterns, creating clear decision criteria, or when user mentions near-miss examples, anti-goals, what not to do, negative examples, counterexamples, or boundary clarification.
Analyzes and improves LLM prompts and agent instructions for token efficiency, determinism, and clarity. Use when (1) writing a new system prompt, skill, or CLAUDE.md file, (2) reviewing or improving an existing prompt for clarity and efficiency, (3) diagnosing why a prompt produces inconsistent or unexpected results, (4) converting natural language instructions into imperative LLM directives, or (5) evaluating prompt anti-patterns and suggesting fixes. Applies to all LLM platforms (Claude, GPT, Gemini, Llama).
Expert patterns for Godot AutoLoad (singleton) architecture including global state management, scene transitions, signal-based communication, dependency injection, autoload initialization order, and anti-patterns to avoid. Use for game managers, save systems, audio controllers, or cross-scene resources. Trigger keywords: AutoLoad, singleton, GameManager, SceneTransitioner, SaveManager, global_state, autoload_order, signal_bus, dependency_injection.
Generic test writing discipline: test quality, real assertions, anti-patterns, and rationalization resistance. Use when writing tests, adding test coverage, or fixing failing tests for any language or framework. Complements language-specific skills.
Best practices, patterns, and examples for building goal-driven agents. Includes client-facing interaction, feedback edges, judge patterns, fan-out/fan-in, context management, and anti-patterns.
Stop your AI agent from generating Tailwind CSS v3 code. Rules for v4 syntax, CSS-first config, modern utility patterns, and common anti-patterns.
React patterns, anti-patterns, and performance optimization. Use when writing React components, reviewing React code, or debugging React issues.