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Agent skill

Swiftui Performance Audit

by sickn33 in sickn33/agentic-awesome-skills

Audit SwiftUI performance issues from code review and profiling evidence.

MITAuto-check passedMobile

Install Swiftui Performance Audit

skills CLI
$ npx skills add sickn33/agentic-awesome-skills --skill swiftui-performance-audit -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install sickn33/agentic-awesome-skills swiftui-performance-audit --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/sickn33/agentic-awesome-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/swiftui-performance-audit .claude/skills/swiftui-performance-audit && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
swiftui-performance-audit
GitHub stars
47k
Used in
2 other repos
Token cost
~1.3k tokens
SKILL.md length
662 words
Files
9 (incl. references)
Skills in repo
1,493
Repo updated
First seen
Licence
MIT

At a glance

Audit SwiftUI performance issues from code review and profiling evidence.

  • Works in 6 steps: Intake → Code-First Review → Guide the User to Profile → …
  • Tasks that involve iOS development
  • SKILL.md covers Quick start, When to Use, Workflow and 1. Intake, plus 8 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Swiftui Performance Audit is an agent skill from sickn33/agentic-awesome-skills. Audit SwiftUI performance issues from code review and profiling evidence.

Its SKILL.md is about 1.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 10 other files, including reference files (for example `agents/openai.yaml`, `references/code-smells.md` and `references/demystify-swiftui-performance-wwdc23.md`).

It sits in Mobile, covering iOS development. It works with SwiftUI. The repository describes itself as: AAS Core is the local, agent-first control plane for complete catalog discovery, agent-owned selection, stack validation, and planning, backed by 2,400+ agentic skills. Includes… The licence is MIT.

When your agent uses it

  • Tasks that involve iOS development

Example prompts

  • “/swiftui-performance-audit”

Workflow steps

6 steps, taken from the step headings in SKILL.md.

  1. Intake
  2. Code-First Review
  3. Guide the User to Profile
  4. Analyze and Diagnose
  5. Remediate
  6. Verify

What it can do on your machine

Read from SKILL.md and the folder at commit 680176d. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Swiftui Performance Audit loads about 1.3k tokens when it runs, and up to ~4.8k if it reads all its reference files. Until then it costs about 25 tokens; SKILL.md has 662 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~25
When it runs · the whole SKILL.md, loaded when a task matches
~1.3k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~4.8k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from sickn33/agentic-awesome-skills at commit 680176d, republished under its MIT licence (© sickn33). 662 words, ~1,340 tokens.

Download SKILL.mdSave it as .claude/skills/swiftui-performance-audit/SKILL.md (or your agent's skills folder). This skill also uses 8 other files; get the full folder from GitHub.
name
swiftui-performance-audit
description
Audit SwiftUI performance issues from code review and profiling evidence.
risk
safe
source
Dimillian/Skills (MIT)
date_added
2026-03-25

SwiftUI Performance Audit

Quick start

Use this skill to diagnose SwiftUI performance issues from code first, then request profiling evidence when code review alone cannot explain the symptoms.

When to Use

  • When the user reports slow rendering, janky scrolling, layout thrash, or high CPU in SwiftUI.
  • When you need a code-first audit plus Instruments guidance if profiling evidence is required.

Workflow

  1. Classify the symptom: slow rendering, janky scrolling, high CPU, memory growth, hangs, or excessive view updates.
  2. If code is available, start with a code-first review using references/code-smells.md.
  3. If code is not available, ask for the smallest useful slice: target view, data flow, reproduction steps, and deployment target.
  4. If code review is inconclusive or runtime evidence is required, guide the user through profiling with references/profiling-intake.md.
  5. Summarize likely causes, evidence, remediation, and validation steps using references/report-template.md.

1. Intake

Collect:

  • Target view or feature code.
  • Symptoms and exact reproduction steps.
  • Data flow: @State, @Binding, environment dependencies, and observable models.
  • Whether the issue shows up on device or simulator, and whether it was observed in Debug or Release.

Ask the user to classify the issue if possible:

  • CPU spike or battery drain
  • Janky scrolling or dropped frames
  • High memory or image pressure
  • Hangs or unresponsive interactions
  • Excessive or unexpectedly broad view updates

For the full profiling intake checklist, read references/profiling-intake.md.

2. Code-First Review

Focus on:

  • Invalidation storms from broad observation or environment reads.
  • Unstable identity in lists and ForEach.
  • Heavy derived work in body or view builders.
  • Layout thrash from complex hierarchies, GeometryReader, or preference chains.
  • Large image decode or resize work on the main thread.
  • Animation or transition work applied too broadly.

Use references/code-smells.md for the detailed smell catalog and fix guidance.

Provide:

  • Likely root causes with code references.
  • Suggested fixes and refactors.
  • If needed, a minimal repro or instrumentation suggestion.

3. Guide the User to Profile

If code review does not explain the issue, ask for runtime evidence:

  • A trace export or screenshots of the SwiftUI timeline and Time Profiler call tree.
  • Device/OS/build configuration.
  • The exact interaction being profiled.
  • Before/after metrics if the user is comparing a change.

Use references/profiling-intake.md for the exact checklist and collection steps.

4. Analyze and Diagnose

  • Map the evidence to the most likely category: invalidation, identity churn, layout thrash, main-thread work, image cost, or animation cost.
  • Prioritize problems by impact, not by how easy they are to explain.
  • Distinguish code-level suspicion from trace-backed evidence.
  • Call out when profiling is still insufficient and what additional evidence would reduce uncertainty.
Show full SKILL.md (245 more words)Show less

5. Remediate

Apply targeted fixes:

  • Narrow state scope and reduce broad observation fan-out.
  • Stabilize identities for ForEach and lists.
  • Move heavy work out of body into derived state updated from inputs, model-layer precomputation, memoized helpers, or background preprocessing. Use @State only for view-owned state, not as an ad hoc cache for arbitrary computation.
  • Use equatable() only when equality is cheaper than recomputing the subtree and the inputs are truly value-semantic.
  • Downsample images before rendering.
  • Reduce layout complexity or use fixed sizing where possible.

Use references/code-smells.md for examples, Observation-specific fan-out guidance, and remediation patterns.

6. Verify

Ask the user to re-run the same capture and compare with baseline metrics. Summarize the delta (CPU, frame drops, memory peak) if provided.

Outputs

Provide:

  • A short metrics table (before/after if available).
  • Top issues (ordered by impact).
  • Proposed fixes with estimated effort.

Use references/report-template.md when formatting the final audit.

References

  • Profiling intake and collection checklist: references/profiling-intake.md
  • Common code smells and remediation patterns: references/code-smells.md
  • Audit output template: references/report-template.md
  • Add Apple documentation and WWDC resources under references/ as they are supplied by the user.
  • Optimizing SwiftUI performance with Instruments: references/optimizing-swiftui-performance-instruments.md
  • Understanding and improving SwiftUI performance: references/understanding-improving-swiftui-performance.md
  • Understanding hangs in your app: references/understanding-hangs-in-your-app.md
  • Demystify SwiftUI performance (WWDC23): references/demystify-swiftui-performance-wwdc23.md

Limitations

  • Use this skill only when the task clearly matches the scope described above.
  • Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
  • Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.

© sickn33, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 8 other files (references) in skills/swiftui-performance-audit of sickn33/agentic-awesome-skills.

  • SKILL.md
  • agents/openai.yaml
  • references/code-smells.md
  • references/demystify-swiftui-performance-wwdc23.md
  • references/optimizing-swiftui-performance-instruments.md
  • references/profiling-intake.md
  • references/report-template.md
  • references/understanding-hangs-in-your-app.md
  • references/understanding-improving-swiftui-performance.md

Open the folder on GitHubat commit 680176d

Used in 2 other repositories

We found 11 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 2 other GitHub owners. This page covers the copy in sickn33/agentic-awesome-skills, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Swiftui Performance Audit next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Swiftui Performance Audit compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Swiftui Performance Audit this skillsickn33/agentic-awesome-skills47k2 repos~1.3kAutomated safety check: PassMIT
Swiftui Protwostraws/SwiftUI-Agent-Skill5.2k2 repos~1.5kAutomated safety check: PassMIT
Swiftui UI PatternsAFK-surf/OpenBridge4304 repos~887Automated safety check: PassMIT
Swiftui Performance Auditharperreed/dotfiles3348 repos~1.4kAutomated safety check: PassNone
Hig Project Contextraintree-technology/hig-doctor1435 repos~1.2kAutomated safety check: PassMIT
Hig Components Contentraintree-technology/hig-doctor1435 repos~1.3kAutomated safety check: PassMIT

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Works with

Categories

Questions about Swiftui Performance Audit

What does Swiftui Performance Audit do?

Audit SwiftUI performance issues from code review and profiling evidence. Swiftui Performance Audit is an agent skill from sickn33/agentic-awesome-skills. Audit SwiftUI performance issues from code review and profiling evidence.

When should I use Swiftui Performance Audit?

Swiftui Performance Audit fits situations like: tasks that involve iOS development.

How do I install Swiftui Performance Audit in Claude Code?

Run `npx skills add sickn33/agentic-awesome-skills --skill swiftui-performance-audit -a claude-code`. Or copy the skill folder (skills/swiftui-performance-audit in sickn33/agentic-awesome-skills) into .claude/skills/swiftui-performance-audit in your project. Claude Code loads it when a task matches its description.

How do I install Swiftui Performance Audit in Codex?

Run `npx skills add sickn33/agentic-awesome-skills --skill swiftui-performance-audit -a codex`. Or copy the skill folder (skills/swiftui-performance-audit in sickn33/agentic-awesome-skills) into .agents/skills/swiftui-performance-audit in your project. Codex loads it when a task matches its description.

Can I use Swiftui Performance Audit in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add sickn33/agentic-awesome-skills --skill swiftui-performance-audit -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/swiftui-performance-audit, .gemini/skills/swiftui-performance-audit, .github/skills/swiftui-performance-audit and .opencode/skills/swiftui-performance-audit in your project.

What does Swiftui Performance Audit need to run?

SKILL.md names no scripts, command-line tools or credentials: Swiftui Performance Audit is instructions for the agent only.

Does Swiftui Performance Audit access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Swiftui Performance Audit safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Swiftui Performance Audit use?

Swiftui Performance Audit is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Swiftui Performance Audit use?

About 1.3k tokens (SKILL.md is roughly 5.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 3.5k tokens, read only when the agent opens those files.

What are the alternatives to Swiftui Performance Audit?

Skills that share tags, products or a category with Swiftui Performance Audit: Swiftui Pro (twostraws/SwiftUI-Agent-Skill, 5.2k stars), Swiftui UI Patterns (AFK-surf/OpenBridge, 430 stars), Swiftui Performance Audit (harperreed/dotfiles, 334 stars) and Hig Project Context (raintree-technology/hig-doctor, 143 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Swiftui Performance Audit?

sickn33 (a GitHub user) maintains it in sickn33/agentic-awesome-skills, which has 47,379 GitHub stars. The repository holds 1,493 skills in this directory. The repository was last updated on October 9, 2026.

Source: sickn33/agentic-awesome-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.