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Nodejs Best Practices

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vudovn
nodejs-best-practices

Node.js development principles and decision-making. Framework selection, async patterns, security, and architecture. Teaches thinking, not copying.

Overview

Publishervudovn
Repositoryag-kit
Skill namenodejs-best-practices
Stars
8.2K
Forks
1.5K
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by vudovn on GitHub. Read the source before you install it.

Installation

Install the Nodejs Best Practices AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/vudovn/ag-kit/tree/main/.agents/skills/nodejs-best-practices
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/vudovn/ag-kit.git /tmp/ag-kit
mkdir -p .claude/skills
cp -r /tmp/ag-kit/.agents/skills/nodejs-best-practices .claude/skills/nodejs-best-practices
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Nodejs Best Practices in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Nodejs Best Practices on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Nodejs Best Practices is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Node.js Best Practices

Principles and decision-making for modern Node.js development. Learn to THINK, not memorize code patterns.


⚠️ How to Use This Skill

This skill teaches decision-making principles, not fixed code to copy.

  • ASK user for preferences when unclear
  • Choose framework/pattern based on CONTEXT
  • Don't default to same solution every time

1. Framework Selection

Decision Tree

What are you building?
│
├── Edge/Serverless (Cloudflare, Vercel)
│   └── Hono (zero-dependency, ultra-fast cold starts)
│
├── High Performance API
│   └── Fastify (~5x req/sec of Express in Fastify's own hello-world benchmark; benchmark your own workload)
│
├── Enterprise/Team familiarity
│   └── NestJS (structured, DI, decorators)
│
├── Legacy/Stable/Maximum ecosystem
│   └── Express (mature, most middleware)
│
└── Full-stack with frontend
    └── Next.js API Routes or tRPC

Comparison Principles

FactorHonoFastifyExpress
Best forEdge, serverlessPerformanceLegacy, learning
Cold startFastestFastModerate
EcosystemGrowingGoodLargest
TypeScriptNativeExcellentGood
Learning curveLowMediumLow

Selection Questions to Ask:

  1. What's the deployment target?
  2. Is cold start time critical?
  3. Does team have existing experience?
  4. Is there legacy code to maintain?

2. Runtime Considerations

Native TypeScript

Node.js 24+ (Active LTS): type-stripping ON by default
├── Run .ts files directly: node file.ts (no flag, stable since 24.12)
├── Erasable syntax only — enums, runtime namespaces, param properties error out
├── For those, use tsx (--experimental-transform-types was removed in Node 26)
└── Consider for: scripts, simple APIs

Module System Decision

ESM (import/export)
├── Modern standard
├── Better tree-shaking
├── Async module loading
└── Use for: new projects

CommonJS (require)
├── Legacy compatibility
├── More npm packages support
└── Use for: existing codebases, some edge cases

Runtime Selection

RuntimeBest For
Node.jsGeneral purpose, largest ecosystem
BunPerformance, built-in bundler
DenoSecurity-first, built-in TypeScript

3. Architecture Principles

Layered Structure Concept

Request Flow:
│
├── Controller/Route Layer
│   ├── Handles HTTP specifics
│   ├── Input validation at boundary
│   └── Calls service layer
│
├── Service Layer
│   ├── Business logic
│   ├── Framework-agnostic
│   └── Calls repository layer
│
└── Repository Layer
    ├── Data access only
    ├── Database queries
    └── ORM interactions

Why This Matters:

  • Testability: Mock layers independently
  • Flexibility: Swap database without touching business logic
  • Clarity: Each layer has single responsibility

When to Simplify:

  • Small scripts → Single file OK
  • Prototypes → Less structure acceptable
  • Always ask: "Will this grow?"

4. Error Handling Principles

Centralized Error Handling

Pattern:
├── Create custom error classes
├── Throw from any layer
├── Catch at top level (middleware)
└── Format consistent response

Error Response Philosophy

Client gets:
├── Appropriate HTTP status
├── Error code for programmatic handling
├── User-friendly message
└── NO internal details (security!)

Logs get:
├── Full stack trace
├── Request context
├── User ID (if applicable)
└── Timestamp

Status Code Selection

SituationStatusWhen
Bad input400Client sent invalid data
No auth401Missing or invalid credentials
No permission403Valid auth, but not allowed
Not found404Resource doesn't exist
Conflict409Duplicate or state conflict
Validation422Schema valid but business rules fail
Server error500Our fault, log everything

5. Async Patterns Principles

When to Use Each

PatternUse When
async/awaitSequential async operations
Promise.allParallel independent operations
Promise.allSettledParallel where some can fail
Promise.raceTimeout or first response wins

Event Loop Awareness

I/O-bound (async helps):
├── Database queries
├── HTTP requests
├── File system
└── Network operations

CPU-bound (async doesn't help):
├── Crypto operations
├── Image processing
├── Complex calculations
└── → Use worker threads or offload

Avoiding Event Loop Blocking

  • Never use sync methods in production (fs.readFileSync, etc.)
  • Offload CPU-intensive work
  • Use streaming for large data

6. Validation Principles

Validate at Boundaries

Where to validate:
├── API entry point (request body/params)
├── Before database operations
├── External data (API responses, file uploads)
└── Environment variables (startup)

Validation Library Selection

LibraryBest For
ZodTypeScript first, inference
ValibotSmaller bundle (tree-shakeable)
ArkTypePerformance critical
YupExisting React Form usage

Validation Philosophy

  • Fail fast: Validate early
  • Be specific: Clear error messages
  • Don't trust: Even "internal" data

7. Security Principles

Security Checklist (Not Code)

  • Input validation: All inputs validated
  • Parameterized queries: No string concatenation for SQL
  • Password hashing: bcrypt or argon2
  • JWT verification: Always verify signature and expiry
  • Rate limiting: Protect from abuse
  • Security headers: Helmet.js or equivalent
  • HTTPS: Everywhere in production
  • CORS: Properly configured
  • Secrets: Environment variables only
  • Dependencies: Regularly audited

Security Mindset

Trust nothing:
├── Query params → validate
├── Request body → validate
├── Headers → verify
├── Cookies → validate
├── File uploads → scan
└── External APIs → validate response

8. Testing Principles

Test Strategy Selection

TypePurposeTools
UnitBusiness logicnode:test, Vitest
IntegrationAPI endpointsSupertest
E2EFull flowsPlaywright

What to Test (Priorities)

  1. Critical paths: Auth, payments, core business
  2. Edge cases: Empty inputs, boundaries
  3. Error handling: What happens when things fail?
  4. Not worth testing: Framework code, trivial getters

Built-in Test Runner (stable since Node.js 20)

node --test src/**/*.test.ts
├── No external dependency
├── Good coverage reporting
└── Watch mode available

9. Anti-Patterns to Avoid

❌ DON'T:

  • Use Express for new edge projects (use Hono)
  • Use sync methods in production code
  • Put business logic in controllers
  • Skip input validation
  • Hardcode secrets
  • Trust external data without validation
  • Block event loop with CPU work

✅ DO:

  • Choose framework based on context
  • Ask user for preferences when unclear
  • Use layered architecture for growing projects
  • Validate all inputs
  • Use environment variables for secrets
  • Profile before optimizing

10. Decision Checklist

Before implementing:

  • Asked user about stack preference?
  • Chosen framework for THIS context? (not just default)
  • Considered deployment target?
  • Planned error handling strategy?
  • Identified validation points?
  • Considered security requirements?

Remember: Node.js best practices are about decision-making, not memorizing patterns. Every project deserves fresh consideration based on its requirements.

Frequently asked questions

What does the Nodejs Best Practices AI skill do?

Node.js development principles and decision-making. Framework selection, async patterns, security, and architecture. Teaches thinking, not copying.

Why use Nodejs Best Practices on TypingMind?

Because you install it once and use it with any model. Nodejs Best Practices is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Nodejs Best Practices in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/vudovn/ag-kit/tree/main/.agents/skills/nodejs-best-practices. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Nodejs Best Practices?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Nodejs Best Practices?

As many as you like. As long as a model supports skills, you can use Nodejs Best Practices with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Nodejs Best Practices AI skill free?

Yes. It is published on GitHub by vudovn under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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