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Build Perf Diagnostics

  • 19 installs
  • 466 repo stars
  • Updated July 25, 2026
  • managedcode/dotnet-skills

Helps with ai & agent building tasks.

About

build-perf-diagnostics is a Claude Code skill for ai & agent building. It helps solo builders move faster with AI-assisted coding.

  • build-perf-diagnostics
  • AI & Agent Building
  • AI-coding skill

Build Perf Diagnostics by the numbers

  • 19 all-time installs (skills.sh)
  • +1 installs in the week ending Aug 2, 2026 (Skillselion tracking)
  • Ranked #10,571 of 16,546 AI & Agent Building skills by installs in the Skillselion catalog
  • Data as of Aug 3, 2026 (Skillselion catalog sync)
npx skills add https://github.com/managedcode/dotnet-skills --skill build-perf-diagnostics

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Listed on Skillselion
Installs19
repo stars466
Last updatedJuly 25, 2026
Repositorymanagedcode/dotnet-skills

What it does

Helps with ai & agent building tasks.

Files

SKILL.mdMarkdownGitHub ↗

Performance Analysis Methodology

1. Generate a binlog: dotnet build /bl:{} -m 2. Use the binlog MCP server (Microsoft.AITools.BinlogMcp, exposed under the binlog MCP namespace) which is bundled with this plugin

Alternate flow when MCP is unavailable: binlog replay to text logs

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)

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