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bun-runtime

Bun como runtime, gerenciador de pacotes, bundler e executor de testes. Quando escolher Bun vs Node, notas de migração e suporte ao Vercel.

O que é bun-runtime?

A skill bun-runtime fornece orientação abrangente sobre o Bun, um runtime e toolkit JavaScript all-in-one que funciona como runtime, gerenciador de pacotes, bundler e executor de testes. Ela ajuda desenvolvedores a decidir quando usar Bun em vez do Node.js, destacando a preferência por Bun em novos projetos JS/TS, scripts que exigem velocidade de instalação/execução, deploys no Vercel e cenários que se beneficiam de uma toolchain unificada. A skill inclui notas detalhadas de migração do Node, substituindo comandos como `node script.js` por `bun run script.js` e `npm install` por `bun install`, além de explicar o uso de `bun run` para scripts npm e `bun x` para execuções avulsas estilo npx. Também cobre configuração do Bun no Vercel, definindo o runtime nas configurações do projeto e usando comandos como `bun run build` e `bun install --frozen-lockfile` para deploys reproduzíveis. Exemplos práticos demonstram instalação, execução, testes com API semelhante ao Jest e uso da API de runtime, como `Bun.file()` e `Bun.serve()`. A skill suporta Claude Code, Cursor e Codex, e enfatiza boas práticas como versionar o lockfile e preferir `bun run` para scripts, mantendo as dependências atualizadas devido à rápida evolução do ecossistema.

Funciona com~Claude Code~Codex CLI~Cursor
npx skills add https://github.com/affaan-m/ECC/tree/main/skills/bun-runtime

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Documentação

Runtime Bun

Bun é um runtime e toolkit JavaScript rápido e all-in-one: runtime, gerenciador de pacotes, bundler e executor de testes.

Quando Usar

  • Prefira Bun para: novos projetos JS/TS, scripts onde a velocidade de instalação/execução importa, deploys no Vercel com runtime Bun e quando você deseja uma única toolchain (executar + instalar + testar + construir).
  • Prefira Node para: máxima compatibilidade com o ecossistema, ferramentas legadas que presumem Node ou quando uma dependência tem problemas conhecidos com Bun.

Use ao: adotar Bun, migrar do Node, escrever ou debugar scripts/testes Bun ou configurar Bun no Vercel ou em outras plataformas.

Como Funciona

  • Runtime: Runtime compatível com Node (construído sobre JavaScriptCore, implementado em Zig).
  • Gerenciador de pacotes: bun install é significativamente mais rápido que npm/yarn. O lockfile é bun.lock (texto) por padrão no Bun atual; versões antigas usavam bun.lockb (binário).
  • Bundler: Bundler e transpilador integrados para aplicações e bibliotecas.
  • Executor de testes: bun test integrado com API semelhante ao Jest.

Migração do Node: Substitua node script.js por bun run script.js ou bun script.js. Execute bun install no lugar de npm install; a maioria dos pacotes funciona. Use bun run para scripts npm; bun x para execuções avulsas estilo npx. Os módulos internos do Node são suportados; prefira as APIs do Bun onde existirem para melhor desempenho.

Vercel: Defina o runtime como Bun nas configurações do projeto. Build: bun run build ou bun build ./src/index.ts --outdir=dist. Instalação: bun install --frozen-lockfile para deploys reproduzíveis.

Exemplos

Executar e instalar

# Instalar dependências (cria/atualiza bun.lock ou bun.lockb)
bun install

# Executar um script ou arquivo
bun run dev
bun run src/index.ts
bun src/index.ts

Scripts e env

bun run --env-file=.env dev
FOO=bar bun run script.ts

Testes

bun test
bun test --watch
// test/example.test.ts
import { expect, test } from "bun:test";

test("add", () => {
  expect(1 + 2).toBe(3);
});

API do Runtime

const file = Bun.file("package.json");
const json = await file.json();

Bun.serve({
  port: 3000,
  fetch(req) {
    return new Response("Olá");
  },
});

Melhores Práticas

  • Faça commit do lockfile (bun.lock ou bun.lockb) para instalações reproduzíveis.
  • Prefira bun run para scripts. Para TypeScript, o Bun executa .ts nativamente.
  • Mantenha as dependências atualizadas; o Bun e o ecossistema evoluem rapidamente.

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

accessibility

Design, implement, and audit inclusive digital products using WCAG 2.2 Level AA. Use when building or auditing UI that must meet WCAG 2.2 Level AA, or when reviewing a change for keyboard, contrast, or screen-reader support.

affaan-m/content-engine

Create platform-native content systems for X, LinkedIn, TikTok, YouTube, newsletters, and repurposed multi-platform campaigns. Use when the user wants social posts, threads, scripts, content calendars, or one source asset adapted cleanly across platforms.

affaan-m/ECC

Multi-platform content distribution across X, LinkedIn, Threads, and Bluesky. Adapts content per platform using content-engine patterns. Never posts identical content cross-platform. Use when the user wants to distribute content across social platforms.

affaan-m/fal-ai-media

Unified media generation via fal.ai MCP — image, video, and audio. Covers text-to-image (Nano Banana), text/image-to-video (Seedance, Kling, Veo 3), text-to-speech (CSM-1B), and video-to-audio (ThinkSound). Use when the user wants to generate images, videos, or audio with AI.

affaan-m/manim-video

日本語翻訳:このファイルは manim-video 用の日本語翻訳が必要です

affaan-m/remotion-video-creation

Remotion のベストプラクティス - React で動画を作成する。3D、アニメーション、音声、字幕、チャート、トランジションなどをカバーするドメイン固有の29のルール。

affaan-m/video-editing

AI-assisted video editing workflows for cutting, structuring, and augmenting real footage. Covers the full pipeline from raw capture through FFmpeg, Remotion, ElevenLabs, fal.ai, and final polish in Descript or CapCut. Use when the user wants to edit video, cut footage, create vlogs, or build video content.

agent-architecture-audit

Full-stack diagnostic for agent and LLM applications. Audits the 12-layer agent stack for wrapper regression, memory pollution, tool discipline failures, hidden repair loops, and rendering corruption. Produces severity-ranked findings with code-first fixes. Essential for developers building agent applications, autonomous loops, or any LLM-powered feature. Use when an agent or LLM feature misbehaves and the failing layer is unknown, or before shipping an agent stack.

agent-eval

Head-to-head comparison of coding agents (Claude Code, Aider, Codex, etc.) on custom tasks with pass rate, cost, time, and consistency metrics. Use when choosing between coding agents, or when a change to an agent setup needs measured pass rate, cost, and time rather than an impression.

agent-harness-construction

Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates. Use when defining or revising an agent

agentic-engineering

Operate as an agentic engineer using eval-first execution, decomposition, and cost-aware model routing. Use when planning or executing engineering work that agents will carry out end to end.

agentic-os

Build persistent multi-agent operating systems on Claude Code. Covers kernel architecture, specialist agents, slash commands, file-based memory, scheduled automation, and state management without external databases. Use when building a persistent multi-agent system on Claude Code with its own memory, commands, and scheduling.

agent-introspection-debugging

Structured self-debugging workflow for AI agent failures using capture, diagnosis, contained recovery, and introspection reports. Use when an agent run fails and you need a reproducible diagnosis instead of a retry.

agent-payment-x402

Add x402 payment execution to AI agents with per-task budgets, spending controls, and non-custodial wallets. Supports Base through agentwallet-sdk and X Layer through OKX Payments / OKX Agent Payments Protocol. Use when an agent must pay for something itself and needs per-task budgets, spending controls, and a non-custodial wallet.

agent-self-evaluation

Use after completing any non-trivial task. The agent self-rates its output on 5 axes — accuracy, completeness, clarity, actionability, conciseness — with concrete evidence per criterion. Produces a structured 1-5 scorecard with specific improvement suggestions.

agent-sort

Build an evidence-backed ECC install plan for a specific repo by sorting skills, commands, rules, hooks, and extras into DAILY vs LIBRARY buckets using parallel repo-aware review passes. Use when ECC should be trimmed to what a project actually needs instead of loading the full bundle.

ai-first-engineering

Engineering operating model for teams where AI agents generate a large share of implementation output. Use when setting team process, review gates, or ownership rules for a codebase largely written by agents.

ai-regression-testing

Regression testing strategies for AI-assisted development. Sandbox-mode API testing without database dependencies, automated bug-check workflows, and patterns to catch AI blind spots where the same model writes and reviews code. Use when adding regression coverage to AI-assisted code, or when the same model both wrote and reviewed a change.

android-clean-architecture

Clean Architecture patterns for Android and Kotlin Multiplatform projects — module structure, dependency rules, UseCases, Repositories, and data layer patterns. Use when structuring modules, layers, or data flow in an Android or KMP project.

angular-developer

Generates Angular code and provides architectural guidance. Trigger when creating projects, components, or services, or for best practices on reactivity (signals, linkedSignal, resource), forms, dependency injection, routing, SSR, accessibility (ARIA), animations, styling (component styles, Tailwind CSS), testing, or CLI tooling.

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