
Build Performance Diagnostics
FreeIdentify MSBuild performance bottlenecks effectively.
Free · Opens the source repo
What Build Performance Diagnostics does
Build Performance Diagnostics is a specialized tool designed for developers who need to analyze and optimize the performance of their MSBuild processes. By utilizing binary log analysis, this skill helps pinpoint the specific reasons behind slow builds, allowing teams to address issues that hinder productivity. The skill focuses on key performance metrics and provides insights into common bottlenecks such as ResolveAssemblyReference (RAR) delays, excessive Roslyn analyzer usage, and inefficient task execution.
To get started, users generate a binary log during the build process, which can then be analyzed using the bundled MCP server. Alternatively, if the MCP server is unavailable, users can replay the binary log to text logs for diagnostic purposes. The skill guides users through a systematic approach to identifying performance issues by examining target and task performance summaries, node utilization, and other critical metrics. This enables developers to make informed decisions about optimizing their build configurations.
This skill is particularly useful after establishing initial performance baselines with the build-perf-baseline tool. It is not intended for fixing incremental build issues or tuning parallelism, making it a focused solution for diagnosing performance problems in MSBuild. By addressing the identified bottlenecks, teams can significantly reduce build times and improve overall development efficiency.
When to use it
Use this tool when you have established performance baselines and need to identify specific issues causing slow builds in MSBuild.
When not to use it
Avoid using this skill for establishing initial baselines, fixing incremental build issues, or tuning parallelism as those require different tools.
What you can build with it
Diagnosing Slow Builds
After noticing prolonged build times, a developer uses this skill to analyze the binary log and identify specific tasks causing delays.
Optimizing Build Performance
A team establishes performance baselines and employs this skill to diagnose and address bottlenecks, improving overall build efficiency.
Analyzing Build Metrics
Using the skill, a developer examines key metrics such as node utilization and task performance to optimize their MSBuild configurations.
How to install Build Performance Diagnostics
View source1. Install with the skills CLI
npx skills add dotnet/skills/build-perf-diagnostics --agent claude-code2. Or install it manually
Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.
Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs
Inside SKILL.md
Written by dotnetPerformance Analysis Methodology
- Generate a binlog:
dotnet build /bl:{} -m - Use the binlog MCP server (
Microsoft.AITools.BinlogMcp, exposed under thebinlogMCP namespace) which is bundled with this plugin
Alternate flow when MCP is unavailable: binlog replay to text logs
- Generate a binlog:
dotnet build /bl:{} -m - Replay to diagnostic log with performance summary:
dotnet msbuild build.binlog -noconlog -fl -flp:v=diag;logfile=full.log;performancesummary - Read the performance summary (at the end of
full.log):grep "Target Performance Summary\|Task Performance Summary" -A 50 full.log - Find expensive targets and tasks: The PerformanceSummary section lists all targets/tasks sorted by cumulative time
- Check for node utilization: grep for scheduling and node messages
grep -i "node.*assigned\|building with\|scheduler" full.log | head -30 - 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). UseReferenceOutputAssembly="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
- Conditionally disable in dev:
- Key principle: Preserve analyzer enforcement in CI. Never just "remove" analyzers — configure them conditionally.
- GlobalPackageReference: Analyzers added via
GlobalPackageReferenceinDirectory.Packages.propsapply to ALL projects. Consider if test projects need the same analyzer set as production code. - EnforceCodeStyleInBuild: When set to
trueinDirectory.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-performanceskill for detailed guidance
6. NuGet Restore in Build
- Symptoms: restore runs every build even when unnecessary
- Fixes:
- Separate restore from build:
dotnet restorethendotnet 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)
- Separate restore from build:
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
/graphmode 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:
- Replay with performance summary:
dotnet msbuild build.binlog -noconlog -fl -flp:v=diag;logfile=full.log;performancesummary - Read target/task performance summaries (at the end of
full.log):
This shows all targets and tasks sorted by cumulative time — equivalent to finding expensive targets/tasks.grep "Target Performance Summary\|Task Performance Summary" -A 50 full.log - Find per-project build times:
grep "done building project\|Project Performance Summary" full.log - Check parallelism (multi-node scheduling):
grep -i "node.*assigned\|RequiresLeadingNewline\|Building with" full.log | head -30 - Check analyzer overhead:
grep -i "Total analyzer execution time\|analyzer.*elapsed\|CompilerAnalyzerDriver" full.log - 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 restorethendotnet 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-buildskill) - Check for bin/obj clashes (see
check-bin-obj-clashskill) - 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)
Frequently asked questions about Build Performance Diagnostics
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