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Found 174 Skills
Review Encore.ts code for best practices and anti-patterns.
Core catalog of 8 critical Elixir/Phoenix anti-patterns covering error handling, separation of concerns, Ecto queries, and testing. Trigger: During Elixir code review, refactoring sessions, or when writing Phoenix/Ecto code.
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.
Stop your AI agent from generating Tailwind CSS v3 code. Rules for v4 syntax, CSS-first config, modern utility patterns, and common anti-patterns.
Debug and fix polizy authorization issues. Use when permission checks fail unexpectedly, errors occur, or authorization behavior is confusing. Covers check algorithm, common issues, and anti-patterns.
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.
Optimizes Snowflake SQL query performance from provided query text. Use when optimizing Snowflake SQL for: (1) User provides or pastes a SQL query and asks to optimize, tune, or improve it (2) Task mentions "slow query", "make faster", "improve performance", "optimize SQL", or "query tuning" (3) Reviewing SQL for performance anti-patterns (function on filter column, implicit joins, etc.) (4) User asks why a query is slow or how to speed it up
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 code reviewer for TypeScript + React 19 applications. Use when reviewing React code, identifying anti-patterns, evaluating state management, or assessing code maintainability. Triggers: code review requests, PR reviews, React architecture evaluation, identifying code smells, TypeScript type safety checks, useEffect abuse detection, state management review.
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.
Audits code for design pattern opportunities and anti-patterns — identifies places where a specific GoF or architectural pattern would solve an observable problem, and flags misapplied patterns that add complexity without benefit. Generates fix prompts. Trigger phrases: "design patterns", "pattern check", "pattern review", "refactoring patterns", "pattern analysis".
Detects code smells and anti-patterns — long methods, large classes, feature envy, data clumps, primitive obsession, dead code, magic numbers, deep nesting, and more. Uses configurable thresholds from .codeprobe-config.json when available. Trigger phrases: "code smells", "smell check", "anti-patterns", "clean code review".