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nextjs-turbopack

Next.js 16+ 與 Turbopack — 增量式打包、檔案系統快取、開發速度,以及何時使用 Turbopack 與 webpack。

nextjs-turbopack 是什麼?

此技能涵蓋 Next.js 16+ 中預設的增量式打包工具 Turbopack,這是一個用 Rust 撰寫的打包器,能大幅提升開發啟動與熱更新的速度。它詳細說明了何時使用 Turbopack(預設開發模式)以及何時回退至 Webpack(例如遇到 Turbopack 錯誤或依賴僅限 Webpack 的外掛程式),並提供了透過 `--webpack` 或 `--no-turbopack` 旗標切換的指令。此技能也探討了運作機制,包括檔案系統快取(可讓重新啟動速度快 5 至 14 倍)、Next.js 16.1+ 的實驗性 Bundle Analyzer,以及生產環境建置的行為。此外,它還釐清了 Next.js 16 中中介軟體檔名從 `middleware.ts` 改為 `proxy.ts` 的重要變更,並強調此變更與 Next.js 版本相關,而非與打包工具相關,同時也提供了改善開發工作流程與生產環境建置的最佳實務。

相容平台~Claude Code~Codex CLI~Cursor
npx skills add https://github.com/affaan-m/ECC/tree/main/skills/nextjs-turbopack

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開啟一個已預先載入此 Agent Skill 的新對話。

說明文件

Next.js 與 Turbopack

Next.js 16+ 預設使用 Turbopack 進行本地開發:這是一個用 Rust 撰寫的增量式打包工具,能大幅提升開發啟動與熱更新的速度。

使用時機

  • Turbopack (預設開發模式):日常開發時使用。大型應用程式的冷啟動與 HMR 速度更快。
  • Webpack (舊版開發模式):僅在遇到 Turbopack 錯誤或依賴僅限 Webpack 的外掛程式進行開發時才使用。使用 --webpack(或 --no-turbopack,取決於您的 Next.js 版本;請查閱您版本的官方文件)來停用。
  • 生產環境:生產環境建置行為 (next build) 可能會根據 Next.js 版本使用 Turbopack 或 Webpack;請查閱您版本的官方 Next.js 文件。

在開發或除錯 Next.js 16+ 應用程式、診斷開發啟動或 HMR 速度慢,或最佳化生產環境套件時使用。

運作方式

  • Turbopack:適用於 Next.js 開發的增量式打包工具。使用檔案系統快取,因此重新啟動速度快得多(例如大型專案可快 5 至 14 倍)。
  • 開發模式預設:從 Next.js 16 開始,next dev 會使用 Turbopack 執行,除非已停用。
  • 檔案系統快取:重新啟動會重複使用先前的工作;快取通常位於 .next 目錄下;基本使用無需額外設定。
  • Bundle Analyzer (Next.js 16.1+):實驗性的 Bundle Analyzer,可檢查輸出並找出大型依賴;透過設定或實驗性旗標啟用(請查閱您版本的 Next.js 文件)。

範例

指令

next dev
next build
next start

使用方式

執行 next dev 以使用 Turbopack 進行本地開發。使用 Bundle Analyzer(請參閱 Next.js 文件)來最佳化程式碼分割並縮減大型依賴。盡可能偏好使用 App Router 與伺服器元件。

中介軟體檔案命名

Next.js 16 引入了 proxy.ts 作為中介軟體的檔案名稱,取代了舊有的 middleware.ts 慣例:

  • Next.js 16+:在專案根目錄使用 proxy.ts
  • Next.js 16 之前:在專案根目錄使用 middleware.ts

檔案名稱的變更與 Next.js 版本 相關,而非與所使用的打包工具(Turbopack 或 Webpack)相關。務必查閱您所審閱版本的官方文件。

請勿將 proxy.ts 標記為 Next.js 16 專案中命名錯誤或遺失的中介軟體檔案。 這個檔案是正確且有意為之的。建議重新命名為 middleware.ts 將會導致中介軟體無法執行。

參考資料:Next.js proxy 文件

最佳實務

  • 保持在最新的 Next.js 16.x 版本,以獲得穩定的 Turbopack 與快取行為。
  • 如果開發速度緩慢,請確認您正在使用 Turbopack(預設),且快取沒有被不必要地清除。
  • 針對生產環境套件大小的問題,請使用您版本適用的官方 Next.js 套件分析工具。

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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