Xcode Compilation Analyzer

SkillAI & models

Your AI can find out why Xcode builds are slow and recommend specific code changes to speed them up. It analyzes build timing summaries and Swift compiler diagnostics to locate the code that takes the longest to compile. The result is a source-level optimization plan that leads with its top recommendations.

Available today. Use it from your connected AI after setup.

Add it, then ask your AI to analyze a slow Xcode build. Point it at your project's build timing summaries and Swift compiler diagnostics so it can pinpoint the hotspots and write up the optimization plan.

Then ask your AI: use the Xcode Compilation Analyzer skill

What your AI can do with it

  • Pinpoint which code slows down Swift and mixed-language compilation
  • Read build timing summaries to find the slowest compile phases
  • Use compiler diagnostics to explain type-checking slowdowns
  • Investigate slow builds, expensive clean builds, and type-checking warnings
  • Produce a recommend-first plan with source-level changes to speed up compilation

What this skill tells your AI

The instructions your AI receives, as published by avdlee/xcode-build-optimization-agent-skill in skills/xcode-compilation-analyzer/SKILL.md and read by ahel’s review.

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

Signals

GitHub stars
1k
Forks
48
Last commit
Aug 2026
Advanced
Catalog kind
skill
Gateway key
xcode-compilation-analyzer
Source
github.com/avdlee/xcode-build-optimization-agent-skill