rsbuild-performance-profiling

Use when profiling, analyzing, reporting, or optimizing Rsbuild performance, including build, dev server, rebuild, static asset serving, memory usage, and CPU profile analysis.

Ir para a instalação

Repositório: web-infra-dev/rsbuild
Última atividade na origem: 22 de junho de 2026 às 02:48
Idioma detectado do SKILL.md: inglês
Estrelas: 3.364
Forks: 273

Opções de instalação

Por padrão, está selecionado o prompt que primeiro revisa a origem. Você pode mudar para um comando direto ou baixar uma cópia local.

Instalar com Codex ou Claude Copie este prompt, cole no Codex, Claude ou outro assistente e deixe que ele revise a página da skill e instale para você.

Um comando direto ignora o prompt de revisão. Verifique a origem antes de executá-lo.

npx skills add https://github.com/web-infra-dev/rsbuild --skill rsbuild-performance-profiling

O comando permanece em uma só linha. Role horizontalmente para revisá-lo antes de copiar.

Prefere uma cópia local? Baixe os arquivos disponíveis atualmente no SkillsMP.

Revise os arquivos de origem

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SKILL.md

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Rsbuild Performance Profiling

Workflow

Define the target scenario before collecting data:

operation: build, dev startup, rebuild, request serving, memory usage, or another explicit flow
benchmark project or fixture
metric: wall time, CPU time, self time, allocations, RSS, heap
success threshold, if the user provided one

Record the baseline first. Keep runtime, package manager, dependencies, environment variables, command flags, and input project unchanged for comparisons.

Save raw artifacts when available, such as CPU profiles, heap snapshots, logs, timing output, and benchmark commands. Do not rely only on subjective observations.

Separate costs by ownership:

Rsbuild code paths
Rspack or loader/plugin internals
third-party dependencies
user project code or benchmark fixture code

Rank findings by measured impact. Prefer self time for direct optimization targets and total time for understanding call-chain impact.

If implementing an optimization, keep behavior unchanged unless the user explicitly asked for a behavior change. Prefer small, measurable changes over broad refactors.

Re-run the same benchmark after changes. Report before/after numbers, absolute delta, percentage delta, and any variance or confidence limits you can observe.

Analysis Rules

Treat the user's supplied profiles, reports, and benchmark numbers as the source of truth for that task.

Do not claim a performance win without comparable before/after measurements.

Do not optimize generated output, dependencies, or benchmark fixture code unless the user asked for that scope.

For CPU profiles, call out both hot functions and why they are on the hot path.

For memory tasks, distinguish peak usage from stable usage after warmup or repeated rebuilds.

Output

Return a concise report with:

benchmark command or data source

top findings ordered by impact

Rsbuild-owned optimization opportunities

changes made, if any

validation results and remaining risk