PluginBench
Skill
Pass
Audit score 90

xcode-compilation-analyzer

avdlee/xcode-build-optimization-agent-skill

Analyze Swift compile hotspots and generate source-level optimization recommendations from build timing data.

What is xcode-compilation-analyzer?

Identifies slow compilation in Swift and mixed-language projects by analyzing build timing summaries and compiler diagnostics. Use when facing slow clean builds, long CompileSwiftSources tasks, type-checking warnings, or expensive incremental rebuilds.

  • Parse build timing summaries to rank compilation bottlenecks by wall-clock impact
  • Run diagnostic flags (-warn-long-function-bodies, -debug-time-compilation) to surface type-checking hotspots
  • Inspect SwiftEmitModule and Planning Swift module times to detect module bloat or macro cascading
  • Identify code patterns (missing type annotations, complex expressions, oversized bridging headers) that slow type checking
  • Separate code-level fixes from project-level configuration issues
  • Rank recommendations by expected build-time reduction, accounting for parallelization effects

How to install xcode-compilation-analyzer

npx skills add https://github.com/avdlee/xcode-build-optimization-agent-skill --skill xcode-compilation-analyzer
Prerequisites
  • Xcode project with Swift code
  • Recent build timing summary output or .build-benchmark artifact (optional but recommended)
  • Access to run builds with custom compiler flags
Claude Code
Cursor
Windsurf
Cline

How to use xcode-compilation-analyzer

  1. 1.Gather build timing summary from a clean or incremental build (Xcode build log or xcodebuild output)
  2. 2.Run the diagnostics script: python3 scripts/diagnose_compilation.py --project App.xcodeproj --scheme MyApp --configuration Debug --threshold 100 --output-dir .build-benchmark
  3. 3.Review the ranked list of slow functions and expressions in the output
  4. 4.Inspect the identified source files for patterns: missing type annotations, complex chained expressions, oversized view builders, broad access control
  5. 5.Generate recommendations ranked by expected wall-clock impact, noting which fixes reduce parallel workload vs. serial bottlenecks
  6. 6.Present findings with evidence, affected files, confidence level, and approval requirements before applying changes

Use cases

Good for
  • Developer reports clean build takes 2+ minutes; analyze timing summary to find the slowest compile phases
  • Type-checking warnings appear in build logs; run diagnostics to pinpoint expensive functions and expressions
  • Incremental build after single-line change takes 30+ seconds; investigate SwiftEmitModule or Planning time to detect module size issues
  • Mixed Swift and Objective-C project has slow bridging overhead; inspect bridging headers and generated surfaces
  • Team wants to speed up CI build times; identify hotspots and provide ranked source-level optimizations
Who it's for
  • iOS/macOS developers optimizing build performance
  • Build engineers investigating slow CI pipelines
  • Teams with large Swift codebases experiencing type-checking delays
  • Projects mixing Swift and Objective-C with bridging overhead

xcode-compilation-analyzer FAQ

What's the difference between 'reduces build time' and 'reduces compiler workload'?

If compile tasks run in parallel and their sum far exceeds wall-clock time, fixing individual hotspots reduces total compiler work but may not reduce your actual build wait time. The skill labels these as 'Reduces compiler workload (parallel)' to set correct expectations.

Should I edit source code immediately after getting recommendations?

No. The skill prefers ad hoc flag injection through build commands first to validate the impact. Only apply persistent source edits after explicit developer approval.

What if the bottleneck is project configuration, not source code?

The skill hands off to xcode-project-analyzer. Both skills work on the same project context but focus on different layers.

How do I interpret SwiftEmitModule time in incremental builds?

If SwiftEmitModule dominates incremental builds (30s+), the module is likely too large or macro-heavy. Consider splitting the module or reducing macro usage.

What compiler flags should I use for deeper investigation?

Use -Xfrontend -debug-time-compilation for per-file times, -Xfrontend -debug-time-function-bodies for per-function times, -Xfrontend -warn-long-function-bodies=<ms> to threshold warnings, and -Xfrontend -stats-output-dir <path> for detailed JSON statistics.

Full instructions (SKILL.md)

Source of truth, from avdlee/xcode-build-optimization-agent-skill.


name: xcode-compilation-analyzer description: Analyze Swift and mixed-language compile hotspots using build timing summaries and Swift frontend diagnostics, then produce a recommend-first source-level optimization plan. Use when a developer reports slow compilation, type-checking warnings, expensive clean-build compile phases, long CompileSwiftSources tasks, warn-long-function-bodies output, or wants to speed up Swift type checking.

Xcode Compilation Analyzer

Use this skill when compile time, not just general project configuration, looks like the bottleneck.

Core Rules

  • Start from evidence, ideally a recent .build-benchmark/ artifact or raw timing-summary output.
  • Prefer analysis-only compiler flags over persistent project edits during investigation.
  • Rank findings by expected wall-clock impact, not cumulative compile-time impact. When compile tasks are heavily parallelized (sum of compile categories >> wall-clock median), note that fixing individual hotspots may improve parallel efficiency without reducing build wait time.
  • When the evidence points to parallelized work rather than serial bottlenecks, label recommendations as "Reduces compiler workload (parallel)" rather than "Reduces build time."
  • Do not edit source or build settings without explicit developer approval.

What To Inspect

  • Build Timing Summary output from clean and incremental builds
  • long-running CompileSwiftSources or per-file compilation tasks
  • SwiftEmitModule time -- can reach 60s+ after a single-line change in large modules; if it dominates incremental builds, the module is likely too large or macro-heavy
  • Planning Swift module time -- if this category is disproportionately large in incremental builds (up to 30s per module), it signals unexpected input invalidation or macro-related rebuild cascading
  • ad hoc runs with:
    • -Xfrontend -warn-long-expression-type-checking=<ms>
    • -Xfrontend -warn-long-function-bodies=<ms>
  • deeper diagnostic flags for thorough investigation:
    • -Xfrontend -debug-time-compilation -- per-file compile times to rank the slowest files
    • -Xfrontend -debug-time-function-bodies -- per-function compile times (unfiltered, complements the threshold-based warning flags)
    • -Xswiftc -driver-time-compilation -- driver-level timing to isolate driver overhead
    • -Xfrontend -stats-output-dir <path> -- detailed compiler statistics (JSON) per compilation unit for root-cause analysis
  • mixed Swift and Objective-C surfaces that increase bridging work

Analysis Workflow

  1. Identify whether the main issue is broad compilation volume or a few extreme hotspots.
  2. Parse timing-summary categories and rank the biggest compile contributors.
  3. Run the diagnostics script to surface type-checking hotspots:
    python3 scripts/diagnose_compilation.py \
      --project App.xcodeproj \
      --scheme MyApp \
      --configuration Debug \
      --destination "platform=iOS Simulator,name=iPhone 16" \
      --threshold 100 \
      --output-dir .build-benchmark
    
    This produces a ranked list of functions and expressions that exceed the millisecond threshold. Use the diagnostics artifact alongside source inspection to focus on the most expensive files first.
  4. Map the evidence to a concrete recommendation list.
  5. Separate code-level suggestions from project-level or module-level suggestions.

Apple-Derived Checks

Look for these patterns first:

  • missing explicit type information in expensive expressions
  • complex chained or nested expressions that are hard to type-check
  • delegate properties typed as AnyObject instead of a concrete protocol
  • oversized Objective-C bridging headers or generated Swift-to-Objective-C surfaces
  • header imports that skip framework qualification and miss module-cache reuse
  • classes missing final that are never subclassed
  • overly broad access control (public/open) on internal-only symbols
  • monolithic SwiftUI body properties that should be decomposed into subviews
  • long method chains or closures without intermediate type annotations

Reporting Format

For each recommendation, include:

  • observed evidence
  • likely affected file or module
  • expected wait-time impact (e.g. "Expected to reduce your clean build by ~2s" or "Reduces parallel compile work but unlikely to reduce build wait time")
  • confidence
  • whether approval is required before applying it

If the evidence points to project configuration instead of source, hand off to xcode-project-analyzer by reading its SKILL.md and applying its workflow to the same project context.

Preferred Tactics

  • Suggest ad hoc flag injection through the build command before recommending persistent build-setting changes.
  • Prefer narrowing giant view builders, closures, or result-builder expressions into smaller typed units.
  • Recommend explicit imports and protocol typing when they reduce compiler search space.
  • Call out when mixed-language boundaries are the real issue rather than Swift syntax alone.

Additional Resources