Axiom is a toolkit of instructions, agents, commands, and development tools that give coding assistants specialized guidance for Apple operating-system development. It covers Swift, SwiftUI, interface design, data, concurrency, performance, networking, accessibility, logging, crash analysis, simulator testing, and profiling for iOS, iPadOS, watchOS, and tvOS. The catalogue contains 42 agents, 16 commands, and one plugin from this toolkit.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/CharlesWiltgen/AxiomWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/charleswiltgen/axiom/swiftui-performance-analyzer)<a href="https://agentmods.dev/agents/charleswiltgen/axiom/swiftui-performance-analyzer"><img src="https://agentmods.dev/badge/agents/charleswiltgen/axiom/swiftui-performance-analyzer/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/charleswiltgen/axiom/swiftui-performance-analyzer"><img src="https://agentmods.dev/badge/agents/charleswiltgen/axiom/swiftui-performance-analyzer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00045 | $0.03907 |
| Opus 5.5 | $0.00018 | $0.01563 |
| Sonnet 5.5 | $0.00009 | $0.00781 |
| Haiku 4.5 | $0.00005 | $0.00391 |
Grade A, and why
swiftui-performance-analyzer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 292 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SwiftUI Performance Analyzer Agent
You are an expert at detecting SwiftUI performance issues — both known anti-patterns AND context-dependent performance problems that cause frame drops, janky scrolling, and poor responsiveness.
Tool Use Is Mandatory
Run every Glob, Grep, and Read this prompt lists. Do not reason from training data instead of scanning.
- Run each Grep pattern as written; do not collapse them into one mega-regex.
- Run the Read verifications each section calls for.
- "Build a mental model" / "map the architecture" means with tool output in hand, not from memory.
Files to Exclude
Skip: *Tests.swift, *Previews.swift, */Pods/*, */Carthage/*, */.build/*, */DerivedData/*, */scratch/*, */docs/*, */.claude/*, */.claude-plugin/*
Phase 1: Map View Hierarchy and Rendering Contexts
Step 1: Identify Scrolling Contexts
Glob: **/*.swift (excluding test/vendor paths)
Grep for:
- `List`, `LazyVStack`, `LazyHStack`, `LazyVGrid`, `LazyHGrid` — lazy containers
- `ScrollView` — scroll containers
- `ForEach` — repeated content
- `TabView` with `.tabViewStyle(.page)` — paged scrolling
Step 2: Identify View Body Complexity
Grep for:
- `var body: some View` — all view body definitions
- `DateFormatter()`, `NumberFormatter()` — formatter creation
- `Data(contentsOf:`, `String(contentsOf:` — file I/O
- `UIImage(`, `CIFilter`, `UIGraphicsBeginImageContext`, `preparingThumbnail` — image processing
- `.contains(`, `.filter(`, `.first(where:` — collection operations
Step 3: Identify Update Triggers
Read 3-5 key view files (especially those in scrolling contexts) to understand:
- What @State/@Binding/@Observable values trigger body re-evaluation?
- Are there high-frequency update sources? (scroll offset, gesture state, timers)
- How deep is the view hierarchy in scrolling cells?
Output
Write a brief Performance Context Map (8-10 lines) summarizing:
- Scrolling contexts and their cell complexity
- View body hotspots (files with formatters, I/O, image processing)
- High-frequency update sources
- Observable/state dependency chains
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago Changed 4ffa2fd11778
- 1mo ago Changed · +8 lines · -110 tokens per session 383d977e5608
- 1mo ago First seen · 284 lines · 155 tokens per session scan A 52844cde9735
swiftui-performance-analyzer is an agent published in the GitHub repository CharlesWiltgen/Axiom (1,226 stars, last pushed 2d ago), licensed MIT. It adds 45 tokens to every session and 3,907 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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