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Xcode Project Analyzer

CommunityPopular
AvdLee
xcode-project-analyzer

Audit Xcode project configuration, build settings, scheme behavior, and script phases to find build-time improvements with explicit approval gates. Use when a developer wants project-level build analysis, slow incremental builds, guidance on target dependencies, build settings review, run script phase analysis, parallelization improvements, or module-map and DEFINES_MODULE configuration.

Overview

PublisherAvdLee
RepositoryXcode-Build-Optimization-Agent-Skill
Skill namexcode-project-analyzer
Stars
1.2K
Forks
48
Bundled files
4
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 4 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by AvdLee on GitHub. Read the source before you install it.

Installation

Install the Xcode Project Analyzer AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/AvdLee/Xcode-Build-Optimization-Agent-Skill.git /tmp/Xcode-Build-Optimization-Agent-Skill
mkdir -p .claude/skills
cp -r /tmp/Xcode-Build-Optimization-Agent-Skill/skills/xcode-project-analyzer .claude/skills/xcode-project-analyzer
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Xcode Project Analyzer in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Xcode Project Analyzer on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Xcode Project Analyzer is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Xcode Project Analyzer

Use this skill for project- and target-level build inefficiencies that are unlikely to be solved by source edits alone.

Core Rules

  • Recommendation-first by default.
  • Require explicit approval before changing project files, schemes, or build settings.
  • Prefer measured findings tied to timing summaries, build logs, or project configuration evidence.
  • Distinguish debug-only pain from release-only pain.

What To Review

  • scheme build order and target dependencies
  • debug vs release build settings against the build settings best practices
  • run script phases and dependency-analysis settings
  • derived-data churn or obviously invalidating custom steps
  • opportunities for parallelization
  • explicit module dependency settings and module-map readiness
  • "Planning Swift module" time in the Build Timing Summary -- if it dominates incremental builds, suspect unexpected input modification or macro-related invalidation
  • asset catalog compilation time, especially in targets with large or numerous catalogs
  • ExtractAppIntentsMetadata time in the Build Timing Summary -- if this phase consumes significant time, record it as xcode-behavior (report the cost and impact, but do not suggest a repo-local optimization unless there is explicit Apple guidance)
  • zero-change build overhead -- if a no-op rebuild exceeds a few seconds, investigate fixed-cost phases (script execution, codesign, validation, CopySwiftLibs)
  • CocoaPods usage -- if a Podfile or Pods.xcodeproj exists, CocoaPods is deprecated; recommend migrating to SPM and do not attempt CocoaPods-specific optimizations (see project-audit-checks.md)
  • Task Backtraces (Xcode 16.4+: Scheme Editor > Build > Build Debugging) to diagnose why tasks re-run unexpectedly in incremental builds

Build Settings Best Practices Audit

Every project audit should include a build settings checklist comparing the project's Debug and Release configurations against the recommended values in build-settings-best-practices.md. Present results using checkmark/cross indicators ([x]/[ ]). The scope is strictly build performance -- do not flag language-migration settings like SWIFT_STRICT_CONCURRENCY or SWIFT_UPCOMING_FEATURE_*.

Apple-Derived Checks

Review these items in every audit:

  • target dependencies are accurate and not missing or inflated
  • schemes build in Dependency Order
  • run scripts declare inputs and outputs
  • .xcfilelist files are used when scripts have many inputs or outputs
  • DEFINES_MODULE is enabled where custom frameworks or libraries should expose module maps
  • headers are self-contained enough for module-map use
  • explicit module dependency settings are consistent for targets that should share modules

Typical Wins

  • skip debug-time scripts that only matter in release
  • add missing script guards or dependency-analysis metadata
  • remove accidental serial bottlenecks in schemes
  • align build settings that cause unnecessary module variants
  • fix stale project structure that forces broader rebuilds than necessary
  • identify linters or formatters that touch file timestamps without changing content, silently invalidating build inputs and forcing module replanning
  • split large asset catalogs into separate resource bundles across targets to parallelize compilation
  • use Task Backtraces to pinpoint the exact input change that triggers unnecessary incremental work

Reporting Format

For each issue, include:

  • evidence
  • likely scope
  • why it affects clean builds, incremental builds, or both
  • estimated impact
  • approval requirement

If the evidence points to package graph or build plugins, hand off to spm-build-analysis by reading its SKILL.md and applying its workflow to the same project context.

Additional Resources

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Xcode Project Analyzer AI skill do?

Audit Xcode project configuration, build settings, scheme behavior, and script phases to find build-time improvements with explicit approval gates. Use when a developer wants project-level build analysis, slow incremental builds, guidance on target dependencies, build settings review, run script phase analysis, parallelization improvements, or module-map and DEFINES_MODULE configuration.

Why use Xcode Project Analyzer on TypingMind?

Because you install it once and use it with any model. Xcode Project Analyzer is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Xcode Project Analyzer in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/AvdLee/Xcode-Build-Optimization-Agent-Skill/tree/main/skills/xcode-project-analyzer. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Xcode Project Analyzer?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Xcode Project Analyzer?

As many as you like. As long as a model supports skills, you can use Xcode Project Analyzer with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Xcode Project Analyzer AI skill free?

Yes. It is published on GitHub by AvdLee under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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