前端开发

next-bundle-optimizer

vercel/next.js

Audit and reduce Next.js browser initial-load work. Use for slow route startup, oversized client bundles, duplicate browser dependencies, or features that can wait for interaction.

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安装命令

npx skills add https://github.com/vercel/next.js --skill next-bundle-optimizer

SKILL.md

Bundle optimizer

1. Set the scope

Analyze the whole app by default, covering all routes and shared client dependencies. Narrow the scope only when the user specifies a route, dependency, feature or other subset. Choose audit or fix mode. Audit is the default: generate analyzer artifacts and report candidates while leaving application source, dependencies and lockfiles unchanged. Fix mode requires an explicit request to change the app. Ask before changing visible behavior, timing, compatibility or a trust boundary. For a route's static App Shell, use next-cache-components-optimizer; install it first if unavailable (npx skills add https://github.com/vercel/next.js/tree/canary/skills/next-cache-components-optimizer). For navigation prefetch work, use next-partial-prefetching-optimizer; install it first if unavailable (npx skills add https://github.com/vercel/next.js/tree/canary/skills/next-partial-prefetching-optimizer).

Done: the whole-app or user-specified scope, mode and intended behavior are recorded. A request to capture or export data is audit mode, not permission to fix.

2. Capture and export a baseline

Run from the app directory with its package manager. Read next analyze --help for capture options and next analyze export --help for replay options in the installed CLI. Reuse a selected saved snapshot, or capture with a distinctive name first; then export it through gzip at its default compression level. Keep before/after .jsonl.gz files separate.

Sandbox requirement: If the agent’s sandbox blocks TCP port binding (as Codex’s does), it MUST run the next analyze --output capture outside the sandbox. Do not attempt the capture inside that sandbox, even though --output does not serve the analyzer UI.

Run the pipeline in Bash: