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Swift Testing Expert

Community
AvdLee
swift-testing-expert

Expert guidance for Swift Testing: test structure, #expect/#require macros, traits and tags, parameterized tests, test plans, parallel execution, async waiting patterns, and XCTest migration. Use when writing new Swift tests, modernizing XCTest suites, debugging flaky tests, or improving test quality and maintainability in Apple-platform or Swift server projects.

Overview

PublisherAvdLee
RepositorySwift-Testing-Agent-Skill
Skill nameswift-testing-expert
Stars
476
Forks
20
Bundled files
10
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.

  • 10 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 Swift Testing Expert 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.
    https://github.com/AvdLee/Swift-Testing-Agent-Skill/tree/main/swift-testing-expert
  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/Swift-Testing-Agent-Skill.git /tmp/Swift-Testing-Agent-Skill
mkdir -p .claude/skills
cp -r /tmp/Swift-Testing-Agent-Skill/swift-testing-expert .claude/skills/swift-testing-expert
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Swift Testing Expert 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 Swift Testing Expert 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 Swift Testing Expert 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.

Swift Testing

Overview

Use this skill to write, review, migrate, and debug Swift tests with modern Swift Testing APIs. Prioritize readable tests, robust parallel execution, clear diagnostics, and incremental migration from XCTest where needed.

Agent behavior contract (follow these rules)

  1. Prefer Swift Testing for Swift unit and integration tests, but keep XCTest for UI automation (XCUIApplication), performance metrics (XCTMetric), and Objective-C-only test code.
  2. Treat #expect as the default assertion and use #require when subsequent lines depend on a prerequisite value.
  3. Default to parallel-safe guidance. If tests are not isolated, first propose fixing shared state before applying .serialized.
  4. Prefer traits for behavior and metadata (.enabled, .disabled, .timeLimit, .bug, tags) over naming conventions or ad-hoc comments.
  5. Recommend parameterized tests when multiple tests share logic and differ only in input values.
  6. Use @available on test functions for OS-gated behavior instead of runtime #available checks inside test bodies; never annotate suite types with @available.
  7. Keep migration advice incremental: convert assertions first, then organize suites, then introduce parameterization/traits.
  8. Only import Testing in test targets, never in app/library/binary targets.

First 60 seconds (triage template)

  • Clarify the goal: new tests, migration, flaky failures, performance, CI filtering, or async waiting.
  • Collect minimal facts:
    • Xcode/Swift version and platform targets
    • Whether tests currently use XCTest, Swift Testing, or both
    • Whether failures are deterministic or flaky
    • Whether tests access shared resources (database, files, network, global state)
  • Branch quickly:
    • repetitive tests -> parameterized tests
    • noisy or flaky failures -> known issue handling and test isolation
    • migration questions -> XCTest mapping and coexistence strategy
    • async callback complexity -> continuation/await patterns

Routing map (read the right reference fast)

  • Test building blocks and suite organization -> references/fundamentals.md
  • #expect, #require, and throw expectations -> references/expectations.md
  • Traits, tags, and Xcode test-plan filtering -> references/traits-and-tags.md
  • Parameterized test design and combinatorics -> references/parameterized-testing.md
  • Default parallel execution, .serialized, isolation strategy -> references/parallelization-and-isolation.md
  • Test speed, determinism, and flakiness prevention -> references/performance-and-best-practices.md
  • Async waiting and callback bridging -> references/async-testing-and-waiting.md
  • XCTest coexistence and migration workflow -> references/migration-from-xctest.md
  • Test navigator/report workflows and diagnostics -> references/xcode-workflows.md
  • Index and quick navigation -> references/_index.md

Common pitfalls -> next best move

  • Repetitive testFooCaseA/testFooCaseB/... methods -> replace with one parameterized @Test(arguments:).
  • Failing optional preconditions hidden in later assertions -> try #require(...) then assert on unwrapped value.
  • Flaky integration tests on shared database -> isolate dependencies or in-memory repositories; use .serialized only as a transition step.
  • Disabled tests that silently rot -> prefer withKnownIssue for temporary known failures to preserve signal.
  • Unclear failure values for complex types -> conform type to CustomTestStringConvertible for focused test diagnostics.
  • Test-plan include/exclude by names -> use tags and tag-based filters instead.

Verification checklist

  • Confirm each test has a single clear behavior and expressive display name when needed.
  • Confirm prerequisites use #require where failure should stop the test.
  • Confirm repeated logic is parameterized instead of duplicated.
  • Confirm tests are parallel-safe or intentionally serialized with rationale.
  • Confirm async code is awaited and callback APIs are bridged safely.
  • Confirm migration keeps unsupported XCTest-only scenarios on XCTest.

References

  • references/_index.md
  • references/fundamentals.md
  • references/expectations.md
  • references/traits-and-tags.md
  • references/parameterized-testing.md
  • references/parallelization-and-isolation.md
  • references/performance-and-best-practices.md
  • references/async-testing-and-waiting.md
  • references/migration-from-xctest.md
  • references/xcode-workflows.md

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 Swift Testing Expert AI skill do?

Expert guidance for Swift Testing: test structure, #expect/#require macros, traits and tags, parameterized tests, test plans, parallel execution, async waiting patterns, and XCTest migration. Use when writing new Swift tests, modernizing XCTest suites, debugging flaky tests, or improving test quality and maintainability in Apple-platform or Swift server projects.

Why use Swift Testing Expert on TypingMind?

Because you install it once and use it with any model. Swift Testing Expert 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 Swift Testing Expert in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/AvdLee/Swift-Testing-Agent-Skill/tree/main/swift-testing-expert. 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 Swift Testing Expert?

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 Swift Testing Expert?

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

Is the Swift Testing Expert 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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