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Ci Cd Setup

Community
rshankras
ci-cd-setup

Generate CI/CD configuration for automated builds, tests, and distribution of iOS/macOS apps. Use when setting up GitHub Actions, Xcode Cloud, or fastlane for continuous integration, TestFlight, or App Store deployment.

Overview

Publisherrshankras
Repositoryclaude-code-apple-skills
Skill nameci-cd-setup
Stars
744
Forks
70
Bundled files
11
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.

  • 11 bundled files

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

  • Open source

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

Installation

Install the Ci Cd Setup 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/rshankras/claude-code-apple-skills.git /tmp/claude-code-apple-skills
mkdir -p .claude/skills
cp -r /tmp/claude-code-apple-skills/skills/generators/ci-cd-setup .claude/skills/ci-cd-setup
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Ci Cd Setup 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 Ci Cd Setup 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 Ci Cd Setup 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.

CI/CD Setup Generator

Generate CI/CD configuration for automated builds, tests, and distribution of iOS/macOS apps.

When This Skill Activates

  • User wants to automate their build and test process
  • User mentions GitHub Actions, Xcode Cloud, or fastlane
  • User wants to set up TestFlight or App Store deployment
  • User asks about continuous integration for their app

Pre-Generation Checks

Before generating, verify:

  1. Existing CI Configuration

    bash
    # Check for existing CI files
    ls -la .github/workflows/ 2>/dev/null
    ls -la ci_scripts/ 2>/dev/null
    ls -la fastlane/ 2>/dev/null
  2. Project Structure

    bash
    # Find Xcode project/workspace
    find . -name "*.xcodeproj" -o -name "*.xcworkspace" | head -5
  3. Package Manager

    bash
    # Check for SPM vs CocoaPods
    ls Package.swift 2>/dev/null
    ls Podfile 2>/dev/null

Configuration Questions

1. CI/CD Platform

  • GitHub Actions (Recommended) - Full control, extensive marketplace
  • Xcode Cloud - Native Apple integration, simpler setup
  • Both - GitHub for PRs/tests, Xcode Cloud for releases

2. Distribution Method

  • TestFlight - Beta testing via App Store Connect
  • App Store - Production releases
  • Direct (macOS only) - Notarized DMG/PKG distribution
  • All - Full pipeline from dev to production

3. Include fastlane?

  • Yes - Advanced automation, match for code signing
  • No - Simpler setup using xcodebuild directly

4. Code Signing Approach

  • Manual - Certificates in GitHub Secrets
  • match (fastlane) - Git-based certificate management
  • Xcode Cloud Managed - Apple handles signing

Generated Files

GitHub Actions

.github/workflows/
├── build-test.yml        # PR checks, unit tests
├── deploy-testflight.yml # TestFlight deployment
└── deploy-appstore.yml   # App Store submission

Xcode Cloud

ci_scripts/
├── ci_post_clone.sh      # Post-clone setup
└── ci_pre_xcodebuild.sh  # Pre-build configuration

fastlane

fastlane/
├── Fastfile              # Lane definitions
├── Appfile               # App configuration
└── Matchfile             # Code signing (if using match)

SwiftLint

.swiftlint.yml            # from templates/swiftlint/swiftlint.yml

Merging Skill Rule Fragments

Skills in this library may ship graduated enforcement as a rules/swiftlint.yml fragment (opt_in_rules + custom_rules) — prose rules turned into deterministic lint. When generating .swiftlint.yml:

  1. Start from templates/swiftlint/swiftlint.yml.
  2. For each skill the project actually uses, check for skills/<category>/<skill>/rules/swiftlint.yml; append its custom_rules entries and union its opt_in_rules.
  3. Respect fragment scoping comments — e.g. observable_object_legacy applies only to iOS 17+/macOS 14+ deployment targets, and xctest_in_unit_tests must keep its UITests exclusion (XCUITest legitimately requires XCTest).
  4. The generated build-test.yml runs the lint job automatically once .swiftlint.yml exists (if: hashFiles('.swiftlint.yml') != '').

Current fragments: security/ (hardcoded secrets), ios/coding-best-practices (print-in-production, legacy ObservableObject, force_unwrapping/force_try), testing/tdd-feature (XCTest scoped out of unit tests), swift/concurrency (@unchecked Sendable without justification).

Integration Steps

GitHub Actions Setup

  1. Add Repository Secrets (Settings > Secrets and variables > Actions):

    • APP_STORE_CONNECT_API_KEY_ID - API Key ID
    • APP_STORE_CONNECT_API_ISSUER_ID - Issuer ID
    • APP_STORE_CONNECT_API_KEY_CONTENT - Private key (.p8 content)
    • CERTIFICATE_P12 - Base64-encoded .p12 certificate
    • CERTIFICATE_PASSWORD - Certificate password
    • PROVISIONING_PROFILE - Base64-encoded provisioning profile
  2. Create App Store Connect API Key:

    • Go to App Store Connect > Users and Access > Keys
    • Generate API Key with "App Manager" role
    • Download the .p8 file (only available once)
  3. Export Certificate:

    bash
    # Export from Keychain as .p12, then base64 encode
    base64 -i certificate.p12 | pbcopy

Xcode Cloud Setup

  1. Enable Xcode Cloud in Xcode:

    • Product > Xcode Cloud > Create Workflow
    • Connect to App Store Connect
  2. Configure Workflow:

    • Set start conditions (branch, PR, tag)
    • Configure environment variables
    • Set up post-actions (TestFlight, App Store)
  3. Add ci_scripts to repository for customization

fastlane Setup

  1. Install fastlane:

    bash
    brew install fastlane
  2. Initialize (if starting fresh):

    bash
    fastlane init
  3. Set up match (optional, for code signing):

    bash
    fastlane match init
    fastlane match development
    fastlane match appstore

Best Practices

Caching

  • Cache Swift Package Manager dependencies
  • Cache DerivedData for faster builds
  • Use selective caching to avoid stale artifacts

Secrets Management

  • Never commit certificates or keys
  • Use environment variables for sensitive data
  • Rotate API keys periodically

Build Optimization

  • Use incremental builds where possible
  • Parallelize test execution
  • Skip unnecessary steps on draft PRs

Notifications

  • Slack/Discord integration for build status
  • Email notifications for failures
  • GitHub status checks for PRs

References

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 Ci Cd Setup AI skill do?

Generate CI/CD configuration for automated builds, tests, and distribution of iOS/macOS apps. Use when setting up GitHub Actions, Xcode Cloud, or fastlane for continuous integration, TestFlight, or App Store deployment.

Why use Ci Cd Setup on TypingMind?

Because you install it once and use it with any model. Ci Cd Setup 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 Ci Cd Setup in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/rshankras/claude-code-apple-skills/tree/main/skills/generators/ci-cd-setup. 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 Ci Cd Setup?

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 Ci Cd Setup?

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

Is the Ci Cd Setup AI skill free?

Yes. It is published on GitHub by rshankras 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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