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Ios performance debugging

Skill sarveshsea/design-skills/skills/ios-performance-debugging

Practical design judgment for AI coding agents: 78 installable skills for craft, research, generation, Figma, and Memoire.

Install
npx -y skills add sarveshsea/design-skills --skill ios-performance-debugging

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

  • 6 stars6 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

Diagnose SwiftUI rendering, launch, responsiveness, concurrency, memory, energy, and simulator failures using reproducible traces and before-after evidence.

SKILL.md

1.3 KB, 235 tokens by cl100k_base, as published. Nobody here has run it

iOS Performance Debugging

Workflow

  1. Define one reproducible user flow and one metric before changing code.
  2. Capture device, OS, build configuration, commit, data fixture, and baseline trace.
  3. Use the narrowest instrument: SwiftUI updates and hitches, Time Profiler, Allocations/Leaks, Network, Energy, or concurrency analysis.
  4. Correlate the trace to source. Do not optimize from intuition alone.
  5. Change one ownership, identity, layout, allocation, or scheduling cause at a time.
  6. Repeat the same flow and compare the same metric.
  7. Keep the trace, command, and before-after result in the handoff.

SwiftUI checks

  • Stable identity in collections.
  • Observation scoped to data the view actually reads.
  • No expensive formatting, filtering, I/O, or object creation in body.
  • Lazy containers used only where they fit the layout.
  • Image decoding and resizing moved off the render-critical path.
  • Navigation and sheet state represented by one source of truth.

Read references/trace-receipt.md before claiming a performance improvement.

What ships with it: 2 files

1.9 KB alongside SKILL.md

references/

Gives 1 of the 12 instructions most debug triage skills give in 235 tokens

Counted across 839 of the 1,149 authors here whose files we hold, read 2026-08-07

  • investigate root cause before proposing any fixin 102 of 839, across 67 files
  • read error messages completelyin 89 of 839, across 49 files
  • create a failing test case before fixingin 84 of 839, across 46 files
  • reproduce the issue consistentlyin 82 of 839, across 41 files
  • change one variable at a timehere, and in 82 of 839, across 42 files
  • check recent changesin 74 of 839, across 36 files
  • write the regression test before fixingin 74 of 839, across 40 files
  • fix the root cause not the symptomin 60 of 839, across 45 files
  • implement a single fix at a timein 59 of 839, across 20 files
  • trace data flow backward to the sourcein 50 of 839, across 20 files
  • remove all debug instrumentationin 49 of 839, across 13 files
  • form a single hypothesisin 48 of 839, across 18 files

Said here and by no other author read

  • define one reproducible flow and one metric before changing code
  • capture device, OS, build, commit, and baseline trace
  • use the narrowest profiling instrument available
  • correlate the trace to the source code
  • repeat the same flow and compare the same metric
  • check stable identity in collections

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.

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