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Node

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mcollina
node

Provides domain-specific best practices for Node.js development with TypeScript, covering type stripping, async patterns, error handling, streams, modules, testing, performance, caching, logging, and more. Use when setting up Node.js projects with native TypeScript support, configuring type stripping (--experimental-strip-types), writing Node 22+ TypeScript without a build step, or when the user mentions 'native TypeScript in Node', 'strip types', 'Node 22 TypeScript', '.ts files without compilation', 'ts-node alternative', or needs guidance on error handling, graceful shutdown, flaky tests, profiling, or environment configuration in Node.js. Helps configure tsconfig.json for type stripping, set up package.json scripts, handle module resolution and import extensions, and apply robust patterns across the full Node.js stack.

Overview

Publishermcollina
Repositoryskills
Skill namenode
Stars
1.9K
Forks
149
Bundled files
18
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.

  • 18 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

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

Installation

Install the Node 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/mcollina/skills/tree/main/skills/node
  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/mcollina/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/skills/node .claude/skills/node
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Node 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 Node 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 Node 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.

When to use

Use this skill whenever you are dealing with Node.js code to obtain domain-specific knowledge for building robust, performant, and maintainable Node.js applications.

TypeScript with Type Stripping

When writing TypeScript for Node.js, use type stripping (Node.js 22.6+) instead of build tools like ts-node or tsx. Type stripping runs TypeScript directly by removing type annotations at runtime without transpilation.

Key requirements for type stripping compatibility:

  • Use import type for type-only imports
  • Use const objects instead of enums
  • Avoid namespaces and parameter properties
  • Use .ts extensions in imports

Minimal example — a valid type-stripped TypeScript file:

ts
// greet.ts
import type { IncomingMessage } from 'node:http';

const greet = (name: string): string => `Hello, ${name}!`;
console.log(greet('world'));

Run directly with:

bash
node greet.ts

See rules/typescript.md for complete configuration and examples.

Common Workflows

For multi-step processes, follow these high-level sequences before consulting the relevant rule file:

Graceful shutdown: Register signal handlers (SIGTERM/SIGINT) → stop accepting new work → drain in-flight requests → close external connections (DB, cache) → exit with appropriate code. See rules/graceful-shutdown.md.

Error handling: Define a shared error base class → classify errors (operational vs programmer) → add async boundary handlers (process.on('unhandledRejection')) → propagate typed errors through the call stack → log with context before responding or crashing. See rules/error-handling.md.

Diagnosing flaky tests: Isolate the test with --test-only → check for shared state or timer dependencies → inspect async teardown order → add retry logic as a temporary diagnostic step → fix root cause. See rules/flaky-tests.md.

Diagnosing stuck processes/tests (node --test hangs, "process did not exit", CI timeout, open handles): isolate file/test → run with explicit timeout/reporter → inspect handles via why-is-node-running (SIGUSR1) → patch deterministic teardown in resource-creation scope → rerun isolated + full suite until stable. See rules/stuck-processes-and-tests.md.

Profiling a slow path: Reproduce under realistic load → capture a CPU profile with --cpu-prof → identify hot functions → check for stream backpressure or unnecessary serialisation → validate improvement with a benchmark. See rules/profiling.md and rules/performance.md.

High-priority activation checklist (streams + caching)

When the task mentions CSV, ETL, ingestion pipelines, large file processing, backpressure, repeated lookups, or deduplicating concurrent async calls, explicitly apply this checklist:

  1. Use await pipeline(...) from node:stream/promises (prefer this over chained .pipe() in guidance/code).
  2. Include at least one explicit async function* transform when data is being transformed in-stream.
  3. Choose a cache strategy when repeated work appears:
    • lru-cache for bounded in-memory reuse in a single process.
    • async-cache-dedupe for async request deduplication / stale-while-revalidate behavior.
  4. Show where backpressure is handled (implicitly via pipeline() or explicitly via drain).

Integrated example pattern (CSV/ETL)

For CSV/ETL-style prompts, prefer an answer structure like:

  • createReadStream(input)
  • async function* parser/transform
  • optional cached enrichment lookup (async-cache-dedupe or lru-cache)
  • await pipeline(...) to a writable destination

Link relevant rules directly in explanations so models can retrieve details:

How to use

Read individual rule files for detailed explanations and code examples:

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Node AI skill do?

Provides domain-specific best practices for Node.js development with TypeScript, covering type stripping, async patterns, error handling, streams, modules, testing, performance, caching, logging, and more. Use when setting up Node.js projects with native TypeScript support, configuring type stripping (--experimental-strip-types), writing Node 22+ TypeScript without a build step, or when the user mentions 'native TypeScript in Node', 'strip types', 'Node 22 TypeScript', '.ts files without compilation', 'ts-node alternative', or needs guidance on error handling, graceful shutdown, flaky tests...

Why use Node on TypingMind?

Because you install it once and use it with any model. Node 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 Node in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/mcollina/skills/tree/main/skills/node. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Node?

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 Node?

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

Is the Node AI skill free?

Yes. It is published on GitHub by mcollina 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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