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Agent Skill · 研究检索

build-perf-diagnostics(构建性能诊断)

build-perf-diagnostics 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

build-perf-diagnostics 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为需要联网;许可证信息还不明确,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 19,828。

总安装 5,441周安装 229GitHub Stars 1,481下载 1,905核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:build-perf-diagnostics(构建性能诊断)
来源仓库:https://github.com/dotnet/skills
仓库路径:skills/build-perf-diagnostics
安装命令:
npx skills add https://github.com/dotnet/skills --skill build-perf-diagnostics
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/dotnet/skills --skill build-perf-diagnostics

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

用于分析构建性能日志,识别昂贵目标和任务,优化 MSBuild 调度效率。适合在 Codex、Claude、Cursor、Gemini CLI 中使用 binlog 诊断构建瓶颈。通过 npx skills add 命令从 GitHub 安装,需生成 binlog 并使用 dotnet msbuild 回放分析。

注意权限范围和维护状态,避免触发不必要的联网、命令执行或文件写入操作。build-perf-diagnostics 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/build-perf-diagnostics

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/dotnet/skills --skill build-perf-diagnostics;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

build-perf-diagnostics 怎么安装?

在终端执行 npx skills add https://github.com/dotnet/skills --skill build-perf-diagnostics。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

build-perf-diagnostics 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

build-perf-diagnostics 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

build-perf-diagnostics 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

build-perf-diagnostics 用的人多吗?

公开数据是累计安装 5,441 次,近一周安装 229 次,下载 1,905 次,GitHub 1,481 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

build-perf-diagnostics 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。
  • 来源仓库有 1,481 星,维护活跃度相对可查。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
build-perf-diagnostics

构建性能诊断 · 本页

5,4411,481需要联网未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Performance Analysis Methodology

  1. Generate a binlog: dotnet build /bl:{} -m
  2. Replay to diagnostic log with performance summary: dotnet msbuild build.binlog -noconlog -fl -flp:v=diag;logfile=full.log;performancesummary
  3. Read the performance summary (at the end of full.log): grep "Target Performance Summary\|Task Performance Summary" -A 50 full.log
  4. Find expensive targets and tasks: The PerformanceSummary section lists all targets/tasks sorted by cumulative time
  5. Check for node utilization: grep for scheduling and node messages grep -i "node.*assigned\|building with\|scheduler" full.log | head -30
  6. Check analyzers: grep for analyzer timing grep -i "analyzer.*elapsed\|Total analyzer execution time\|CompilerAnalyzerDriver" full.log

Key Metrics and Thresholds

  • Build duration: what's "normal" — small project <10s, medium <60s, large <5min
  • Node utilization: ideal is >80% active time across nodes. Low utilization = serialization bottleneck
  • Single target domination: if one target is >50% of build time, investigate
  • Analyzer time vs compile time: analyzers should be <30% of Csc task time. If higher, consider removing expensive analyzers
  • RAR time: ResolveAssemblyReference >5s is concerning. >15s is pathological

Common Bottlenecks

1. ResolveAssemblyReference (RAR) Slowness

  • Symptoms: RAR taking >5s per project
  • Root causes: too many assembly references, network-based reference paths, large assembly search paths
  • Fixes: reduce reference count, use <DesignTimeBuild>false</DesignTimeBuild> for RAR-heavy analysis, set <ResolveAssemblyReferencesSilent>true</ResolveAssemblyReferencesSilent> for diagnostic
  • Advanced: <DesignTimeBuild> and <ResolveAssemblyWarnOrErrorOnTargetArchitectureMismatch>
  • Key insight: RAR runs unconditionally even on incremental builds because users may have installed targeting packs or GACed assemblies (see dotnet/msbuild#2015). With.NET Core micro-assemblies, the reference count is often very high.
  • Reduce transitive references: Set <DisableTransitiveProjectReferences>true</DisableTransitiveProjectReferences> to avoid pulling in the full transitive closure (note: projects may need to add direct references for any types they consume). Use ReferenceOutputAssembly="false" on ProjectReferences that are only needed at build time (not API surface). Trim unused PackageReferences.

2. Roslyn Analyzers and Source Generators

  • Symptoms: Csc task takes much longer than expected for file count (>2× clean compile time)
  • Diagnosis: Check the Task Performance Summary in the replayed log for Csc task time; grep for analyzer timing messages; compare Csc duration with and without analyzers (/p:RunAnalyzers=false)
  • Fixes:

- Conditionally disable in dev: <RunAnalyzers Condition="'$(ContinuousIntegrationBuild)'!= 'true'">false</RunAnalyzers> - Per-configuration: <RunAnalyzers Condition="'$(Configuration)' == 'Debug'">false</RunAnalyzers> - Code-style only: <EnforceCodeStyleInBuild Condition="'$(ContinuousIntegrationBuild)' == 'true'">true</EnforceCodeStyleInBuild> - Remove genuinely redundant analyzers from inner loop - Severity config in.editorconfig for less critical rules

  • Key principle: Preserve analyzer enforcement in CI. Never just "remove" analyzers — configure them conditionally.
  • GlobalPackageReference: Analyzers added via GlobalPackageReference in Directory.Packages.props apply to ALL projects. Consider if test projects need the same analyzer set as production code.
  • EnforceCodeStyleInBuild: When set to true in Directory.Build.props, forces code-style analysis on every build. Should be conditional on CI environment (ContinuousIntegrationBuild) to avoid slowing dev inner loop.

3. Serialization Bottlenecks (Single-threaded targets)

  • Symptoms: Performance summary shows most build time concentrated in a single project; diagnostic log shows idle nodes while one works
  • Common culprits: targets without proper dependency declaration, single project on critical path
  • Fixes: split large projects, optimize the critical path project, ensure proper BuildInParallel

4. Excessive File I/O (Copy tasks)

  • Symptoms: Copy task shows high aggregate time
  • Root causes: copying thousands of files, copying across network drives, Copy task unintentionally running once per item (per-file) instead of as a single batch (see dotnet/msbuild#12884)
  • Fixes: use hardlinks (<CreateHardLinksForCopyFilesToOutputDirectoryIfPossible>true</CreateHardLinksForCopyFilesToOutputDirectoryIfPossible>), reduce CopyToOutputDirectory items, use <UseCommonOutputDirectory>true</UseCommonOutputDirectory> when appropriate, set <SkipCopyUnchangedFiles>true</SkipCopyUnchangedFiles>, consider --artifacts-path (.NET 8+) for centralized output layout
  • Dev Drive: On Windows, switching to a Dev Drive (ReFS with copy-on-write and reduced Defender scans) can significantly reduce file I/O overhead for Copy-heavy builds. Recommend for both dev machines and self-hosted CI agents.

5. Evaluation Overhead

  • Symptoms: build starts slow before any compilation
  • Root causes: complex Directory.Build.props, wildcard globs scanning large directories, NuGetSdkResolver overhead (adds 180-400ms per project evaluation even when restored — see dotnet/msbuild#4025)
  • Fixes: reduce Directory.Build.props complexity, use <EnableDefaultItems>false</EnableDefaultItems> for legacy projects with explicit file lists, avoid NuGet-based SDK resolvers if possible
  • See: eval-performance skill for detailed guidance

6. NuGet Restore in Build

  • Symptoms: restore runs every build even when unnecessary
  • Fixes:

- Separate restore from build: dotnet restore then dotnet build --no-restore - Enable static graph evaluation: <RestoreUseStaticGraphEvaluation>true</RestoreUseStaticGraphEvaluation> in Directory.Build.props — can save significant time in large builds (results are workload-dependent)

7. Large Project Count and Graph Shape

  • Symptoms: many small projects, each takes minimal time but overhead adds up; deep dependency chains serialize the build
  • Consider: project consolidation, or use /graph mode for better scheduling
  • Graph shape matters: a wide dependency graph (few levels, many parallel branches) builds faster than a deep one (many levels, serialized). Refactoring from deep to wide can yield significant improvements in both clean and incremental build times.
  • Actions: look for unnecessary project dependencies, consider splitting a bottleneck project into two, or merging small leaf projects

Using Binlog Replay for Performance Analysis

Step-by-step workflow using text log replay:

  1. Replay with performance summary: dotnet msbuild build.binlog -noconlog -fl -flp:v=diag;logfile=full.log;performancesummary
  2. Read target/task performance summaries (at the end of full.log): grep "Target Performance Summary\|Task Performance Summary" -A 50 full.log This shows all targets and tasks sorted by cumulative time — equivalent to finding expensive targets/tasks.
  3. Find per-project build times: grep "done building project\|Project Performance Summary" full.log
  4. Check parallelism (multi-node scheduling): grep -i "node.*assigned\|RequiresLeadingNewline\|Building with" full.log | head -30
  5. Check analyzer overhead: grep -i "Total analyzer execution time\|analyzer.*elapsed\|CompilerAnalyzerDriver" full.log
  6. Drill into a specific slow target: grep 'Target "CoreCompile"\|Target "ResolveAssemblyReferences"' full.log

Quick Wins Checklist

  • Use /maxcpucount (or -m) for parallel builds
  • Separate restore from build (dotnet restore then dotnet build --no-restore)
  • Enable static graph restore (<RestoreUseStaticGraphEvaluation>true</RestoreUseStaticGraphEvaluation>)
  • Enable hardlinks for Copy (<CreateHardLinksForCopyFilesToOutputDirectoryIfPossible>true</CreateHardLinksForCopyFilesToOutputDirectoryIfPossible>)
  • Disable analyzers conditionally in dev inner loop: <RunAnalyzers Condition="'$(ContinuousIntegrationBuild)'!= 'true'">false</RunAnalyzers>
  • Enable reference assemblies (<ProduceReferenceAssembly>true</ProduceReferenceAssembly>)
  • Check for broken incremental builds (see incremental-build skill)
  • Check for bin/obj clashes (see check-bin-obj-clash skill)
  • Use graph build (/graph) for multi-project solutions
  • Use --artifacts-path (.NET 8+) for centralized output layout
  • Enable Dev Drive (ReFS) on Windows dev machines and self-hosted CI

Impact Categorization

When reporting findings, categorize by impact to help prioritize fixes:

  • 🔴 HIGH IMPACT (do first): Items consuming >10% of total build time, or a single target >50% of build time
  • 🟡 MEDIUM IMPACT: Items consuming 2-10% of build time
  • 🟢 QUICK WINS: Easy changes with modest impact (e.g., property flags in Directory.Build.props)

平台分布

Codex

36.35%
按下载量换算692

Claude

27.37%
按下载量换算521

Cursor

16.91%
按下载量换算322

Gemini CLI

10.1%
按下载量换算192

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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