Agent Academy is a free, source-linked library of skills, prompts, MCP servers and bot templates, organised into courses by profession, for people who hand real work to AI agents: 1,467 live resources, each with its original link, license and safety tags.
Skill
modern-javascript-patterns
Original text · EnglishMaster ES6+ features including async/await, destructuring, spread operators, arrow functions, promises, modules, iterators, generators, and functional programming patterns for writing clean, efficient JavaScript code. Use when refactoring legacy code, implementing modern patterns, or optimizing JavaScript applications.
Republished in full under its license, with attribution. The source is authoritative.
name: modern-javascript-patterns
description: Master ES6+ features including async/await, destructuring, spread operators, arrow functions, promises, modules, iterators, generators, and functional programming patterns for writing clean, efficient JavaScript code. Use when refactoring legacy code, implementing modern patterns, or optimizing JavaScript applications.
Modern JavaScript Patterns
Comprehensive guide for mastering modern JavaScript (ES6+) features, functional programming patterns, and best practices for writing clean, maintainable, and performant code.
When to Use This Skill
Refactoring legacy JavaScript to modern syntax
Implementing functional programming patterns
Optimizing JavaScript performance
Writing maintainable and readable code
Working with asynchronous operations
Building modern web applications
Migrating from callbacks to Promises/async-await
Implementing data transformation pipelines
Detailed patterns and worked examples
Detailed pattern documentation lives in references/details.md. Read that file when the navigation tier above is insufficient.
Best Practices
Use const by default: Only use let when reassignment is needed
Prefer arrow functions: Especially for callbacks
Use template literals: Instead of string concatenation
Destructure objects and arrays: For cleaner code
Use async/await: Instead of Promise chains
Avoid mutating data: Use spread operator and array methods
Use optional chaining: Prevent "Cannot read property of undefined"
Use nullish coalescing: For default values
Prefer array methods: Over traditional loops
Use modules: For better code organization
Write pure functions: Easier to test and reason about
Use meaningful variable names: Self-documenting code
Keep functions small: Single responsibility principle
Handle errors properly: Use try/catch with async/await
Use strict mode: 'use strict' for better error catching
For common pitfalls (this binding, promise anti-patterns, memory leaks), see [references/advanced-patterns.md](references/advanced-patterns.md).
Reference for the Claude API / Anthropic SDK — model ids, pricing, params, streaming, tool use, MCP, agents, caching, token counting, model migration. TRIGGER — read BEFORE opening the target file; don't skip because it "looks like a one-liner" — whenever: the prompt names Claude/Anthropic in any form (Claude, Anthropic, Fable, Opus, Sonnet, Haiku, `anthropic`, `@anthropic-ai`, `claude-*`, `us.anthropic.*`,…
Guide users through a structured workflow for co-authoring documentation. Use when user wants to write documentation, proposals, technical specs, decision docs, or similar structured content. This workflow helps users efficiently transfer context, refine content through iteration, and verify the doc works for readers. Trigger when user mentions writing docs, creating proposals, drafting specs, or similar…
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.
Toolkit for interacting with and testing local web applications using Playwright. Supports verifying frontend functionality, debugging UI behavior, capturing browser screenshots, and viewing browser logs.
Use after generating code, after accepting AI suggestions, or when reviewing AI-written modules. Also use when code works but feels brittle, when error handling seems thin, when orphaned resources or missing cleanup are suspected, or when the agent claims done but hidden debt may exist. Catches the specific failure patterns AI agents produce that humans would not.