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Developer Lists Five Agent Skill Packs for Swift and Xcode Projects

Install These Skills Before Codex Touches Your Xcode Project

iOS developer Paul Solt recommends installing community skill packs before letting Codex or Claude Code work on Xcode projects, citing deprecated code and compiler errors as common agent failures. The packs come from Paul Hudson, Antoine van der Lee, Thomas Ricouard and others, covering SwiftUI, concurrency, testing and build optimization.

Original post · 6 min read
X ArticleInstall These Skills Before Codex Touches Your Xcode Project
I've been building iOS and macOS apps with Codex and Claude Code since last year. One thing I've learned: agents need simple systems that produce reliable results.
Without the right skills, agents write deprecated code, create compiler errors, and waste your time debugging their mistakes. These 5 skill packs fix that. Each one comes from a developer who's been shipping real apps with agents.
1. Paul Hudson: The Swift Foundation

If you've learned Swift online, you've probably read Paul Hudson's work (@twostraws). His agent skills come from a decade of teaching Swift through Hacking with Swift — and his SwiftUI rules help correct common mistakes with agents.
I met Paul at try! Swift in NYC and we spent some time together in the SwiftUI labs at WWDC 2019. He's a prolific writer and digs in deep so you can understand what works.

These skills will jumpstart your agents:
SwiftUI Pro: modern SwiftUI APIs, view composition, state management
Swift Concurrency Pro: async/await, actors, Sendable, Swift 6 migration
Swift Testing Pro: Test macros, parameterized tests, XCTest migration
SwiftData Pro: models, queries, migrations, CloudKit sync
He also maintains the canonical directory of every community Swift skill.
2. Antoine van der Lee: SwiftLee

Antoine van der Lee (@twannl) runs SwiftLee — one of the most widely read Swift blogs. He has 5 skill repos, each with detailed reference docs. His Xcode Build Optimization skill stands out — 6 sub-skills for build settings and compilation times to make your code build faster.
SwiftUI Expert: state management, view composition, performance, Liquid Glass
Swift Concurrency: actors, Sendable, data race safety, Swift 6 migration
Swift Testing Expert: modern testing patterns, XCTest migration, parameterized tests
Core Data Expert: stack setup, fetch requests, background contexts, migrations
Xcode Build Optimization: 6 sub-skills for build settings, compilation times, project config
The Xcode Build Optimization skill is a powerful tool that can make both you and your agents more productive. And if you want a better workflow with the iOS Simulator, check out his developer app: @rocketsim_app
3. Thomas Ricouard: Codex Expert

Thomas Ricouard (@Dimillian) built Codex Monitor — the open source macOS app for managing multiple Codex agents — and then joined OpenAI's Developer Experience team.
His skills now ship as the official Codex Build iOS App and Build Mac App plugins. These automatically update with each new release of the Codex app or Codex CLI.
Build iOS Apps plugin
SwiftUI Liquid Glass: iOS 26+ Liquid Glass APIs, modifier ordering, fallbacks
SwiftUI UI Patterns: navigation, sheets, app wiring, reusable components
SwiftUI Performance Audit: invalidation storms, identity churn, layout thrash
SwiftUI View Refactor: smaller subviews, MV-style data flow, Observation
iOS Debugger Agent: simulator build/run/debug with XcodeBuildMCP
iOS App Intents: Siri, Shortcuts, widget integration
Build macOS Apps plugin adds AppKit interop, packaging/notarization, signing/entitlements, window management, and SwiftPM workflows.
You can dig into the source for both of these plugins at the Official OpenAI Plugins repo,
4. Krzysztof Zabłocki: Advanced Swift + Tooling

Krzysztof Zabłocki (@merowing_) created Sourcery — the Swift metaprogramming tool used by 40,000+ apps including Airbnb and The New York Times. His open source tools power over 80,000 apps total.
His approach to agent skills is completely different. Instead of individual skill files, he built a rules-based system over 3 years of daily LLM use — 12 domain-specific rule files with a smart loader that uses LLM self-reflection to decide which rules to apply based on context. The system is tool-agnostic: same rules work in Cursor, Claude Code, and Codex.
What I like about his approach: he has a progressive documentation reading CLI tool to offload search and make it agent-friendly. He also created Inject for hot Swift reloading — useful for fast prototyping when you want to see UI changes without rebuilding.
Read his guide: Stop Getting Average Code from Your LLM
You can grab two agent friendly files that follow his coding philosophy:
general.md: primary directive and coding standards
rule-loading.md: smart loader that selects rules by context
The full 12-file set covering dependency injection, SwiftUI architecture, ViewModel coordination, and Swift Testing is part of his Swifty Stack course.
5. AppCreator: Agent-Friendly Build Tools
None of the skills above matter if your agent can't build and test your code.
Xcode build output is verbose. Test output is worse. We're juggling XCTest and Swift Testing with two different build systems. Agents choke on this.
I built AppCreator to solve that problem. It scaffolds Xcode projects with agent-friendly defaults. I created it to quickly prototype new app ideas that used the same workflow as my existing projects.
Adopt the skill for your existing apps and it will help your agent make a build … continue on X ↗
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More in Agents & Dev Tools

Developer Rebuilds Seven Adobe Apps in Rust Using Opus 5.5

Peter Yang highlights a developer who reimplemented seven Adobe apps, including Photoshop, Premiere and Lightroom, in Rust with Claude Opus 5.5 and open-sourced them. The developer believes they can match Adobe's features within months, against Adobe's $840 yearly all-apps plan.

Original post · 1 min read
It's insane to watch AI blow apart closed source software and games.

4 examples from the past month:

1. 7 of Adobe's biggest apps, including Photoshop, Premiere, and Lightroom, have been partially rebuilt in Rust with Opus 5.5 and open sourced. It's still early, but the developer thinks they can match Adobe's features within months. Adobe's all-apps plan costs $840/year.
Miguel Ángel Durán @midudev
Todos los productos de Adobe reimplementados desde cero, gratuitos y de código abierto

→ getartcraft.com/apps
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Vercel's Guillermo Rauch Explains Turborepo's Migration From Go to Rust

Guillermo Rauch says Vercel moved Turborepo from Go to Rust, a migration that was controversial internally due to human costs. He argues that with AI agents the calculus has changed, so what is best for humans is no longer necessarily best for business.

Original post · 1 min read
DHH is fundamentally right about Rust. For context, Vercel has been undergoing a Rust-ification (carcinization, technically 🦀) for a while.

One of the first projects we migrated was Turborepo, from Go to Rust¹. The migration completed, but the RoI was actually quite controversial internally.

While Rust was in our eyes better for low-level OS access, something crucial for a build system like Turbo, the human migration costs were very sustantive.

Go is very fast. It's beautifully designed. It's easy to iterate on. We were very conflicted about the migration, because it was *humans* writing the code, *even if we knew Rust was a better choice*.

The calculus has now changed. What's "best for humans" is no longer necessarily "best for business".

FWIW, it's also quite unlikely that Rust is the end-all-be-all toolchain. I'm quite certain there's greener pasture ahead, because Rust itself was designed before the 'supersonic tsunami' of agents hit.

¹ https​://vercel.com/blog/how-turborepo-is-porting-from-go-to-rust
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Integer Multiplication Algorithm Bound Tightened Repeatedly With Astra

A post reports that a user running ChatGPT Astra in a loop is repeatedly breaking records for integer multiplication algorithms. It quotes an update to OpenAI problem #109 that tightens the constant from 2^-182 to 2^-59, a roughly 500,000-fold improvement over the previous result.

Original post · 1 min read
This guy has 6.1 Astra running in a loop and is breaking the record for integer multiplication algorithms every few hours lmaooooo.
Doug Colkitt @0xdoug
We are publishing an update to OpenAI problem #109 Integer multiplication) with another substantial further tightening:

κ = 2⁻⁵⁹ (from OpenAI’s original κ = 2⁻¹⁸²)

Approximately 500 thousand fold improvement over our previous result and a 2¹²³ fold improvement over the original OAI result.

The latest redesigned the finite network to share intermediate computations and scratch space, then tightened the recursion and Gaussian estimates.
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Boris Cherny Says Prompting Claude Should Feel Like Talking to a Coworker

Boris Cherny explains his approach to prompting Claude, advising users to give clear goals, specify effort level and verification steps rather than relying on heavy scaffolding.

Original post · 1 min read
I am surprised that people are surprised this is how I prompt Claude.

Talk to Claude the way you would a coworker. There's no secret to prompting. There's no need to be overly scaffolded or prescriptive for most tasks -- give Claude a goal, and it will figure it out.

Back in the Sonnet 3.5 days, your prompt mattered a lot. Nowadays, it's much more important to communicate to the model:

1. What you want it to do
2. How much effort you want it to spend
3. How it should verify that it did the right thing
Boris Cherny @bcherny
Prompt
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Eric Raymond Highlights Open-Source Rust Clone of Photoshop Built via LLM

Eric S. Raymond shares the photocraft GitHub project, a clean-room open-source reimplementation of Photoshop that he says was likely generated by decompiling the app, converting it to a spec and prompting an LLM for Rust. He argues this threatens closed-source software.

Original post · 1 min read
This is the doom I predicted a few days ago, coming for Photoshop. A clean-room open-source reimplementation.

No prizes for guessing that they decompiled Photoshop to source code, processed that to some kind of non-code specification language, then fed the spec to an LLM with an instruction to generate Rust.

Adobe just got nuked. And closed source is dead, dead, dead.

github.com/storytold/photocraft
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Nat Eliason Details Fourteen Ways His Bot Setup Automates Work

Nat Eliason lists fourteen functions of his bot setup, including a chief-of-staff agent that drafts emails, specialist agents per work lane, and cloud coding agents that open pull requests from Linear issues. He notes GrokBot as a substantial improvement over his previous OpenClaw setup.

Original post · 2 min read
Things my @bot setup does that still blow my mind:

1. A Chief of Staff who opens the day pulling open loops from email & tasks and suggesting things it can knock out before 7am.

2. After every meeting, decisions get folded into Notion, Linear, and Todoist — not left rotting in Granola

3. Every email starts as a draft. The CoS bot scans my email every ~2hr and drafts replies to nearly everything — including checking my cal for availability and finding requested attachments / links

4. A specialist for each lane: curriculum, engineering, coaching, hiring, content, ops, and one for every single piece of software

5. Routines that keep running while I’m offline (e.g. monitoring Sentry errors in our apps and proactively fixing things)

6. Group rooms where 2–4 bots share one project thread instead of me copy-pasting context

7. Cloud coding agents that pick up Linear issues and open PRs after running the list of open work by me EoD — then squash-merge to main when it’s done

8. Meeting prep briefs pulled from Granola + Notion before I walk in

9. A growing shareable knowledge base in Notion + a GitHub repo that we update daily based on what happens at school

10. Student progress look-up across Expertise, Followers, and CoFounder without inventing numbers — chat anytime to see where a student is on their business work

11. Mentor Mind that coaches me on how to hold the bar without inventing doctrine

12. Todoist as a central task list where it logs things it’s blocked on for me, or from meetings / emails — and I can paste links into chat to direct it how to solve them

13. Engineering work is automatically tracked in Linear so my and the product teams’ bots don’t collide with each other

14. Presentations spun up in Gamma / Claude Design without me opening a slide tool

15. Plaud / live capture → notes the bots can actually act on

Probably more but these were the immediate ones we thought of.
Nat Eliason @nateliason
GrokBot feels like absolute magic at this point, a meaningful leg up on my previous OpenClaw etc. setups.

And with how easy it is to setup, there's really no excuse now.
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