Chrome Trace logo

Chrome Trace

Organization
layoutit
chrome-trace

Capture and analyze Chrome/Chromium performance traces with Playwright around a concrete browser interaction. Use when Codex needs to answer where frame time is spent during an update, drag, rotation, scroll, animation, camera movement, light movement, DOM/CSS render change, or other performance-sensitive UI action; especially when the right answer requires per-frame Chrome trace evidence instead of FPS-only guesses.

Overview

Publisherlayoutit
Repositorypolycss
Skill namechrome-trace
Stars
768
Forks
22
Bundled files
5
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.

  • 5 bundled files

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

  • Open source

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

Installation

Install the Chrome Trace 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.
    https://github.com/layoutit/polycss/tree/main/.agents/skills/chrome-trace
  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/layoutit/polycss.git /tmp/polycss
mkdir -p .claude/skills
cp -r /tmp/polycss/.agents/skills/chrome-trace .claude/skills/chrome-trace
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Chrome Trace 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 Chrome Trace 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 Chrome Trace 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.

Chrome Trace

Core Workflow

Use Playwright with Chromium and the Chrome DevTools Protocol Tracing domain to capture the exact interaction under investigation.

  1. Start from a reproducible page and action.
  2. Warm up the page until app-specific readiness is true.
  3. Start Chrome tracing and a requestAnimationFrame sampler immediately before the action.
  4. Mark the action window with performance.mark() and console.timeStamp().
  5. Perform the action with real Playwright input when the user is asking about input-driven behavior.
  6. Stop tracing after a short settle window.
  7. Align trace event timestamps to performance.now() using the start/end marks.
  8. Report where time went: Scripting, Style, Layout, PrePaint, Paint, compositor main-thread work, compositor impl-thread work, raster, GPU/viz events, and the slowest frame windows.

Do not draw conclusions from FPS alone. Use FPS/frame-time summaries only as the symptom; use trace groups and top events as the explanation.

PolyCSS Trace Runners

Use scripts/trace.mjs as the front door:

bash
pnpm bench:build
node .agents/skills/chrome-trace/scripts/trace.mjs motion --page nonvoxel --mesh glb:Elephant.glb --variant baseline --dom-samples --label elephant-baseline
node .agents/skills/chrome-trace/scripts/trace.mjs motion --page nonvoxel --mesh teapot --variant baseline --dom-samples --frame-details --layer-details --gpu-details --trace-out bench/results/teapot.trace.json --label teapot-enriched --report
node .agents/skills/chrome-trace/scripts/trace.mjs motion --page nonvoxel --mesh teapot --variant baseline --gpu-details full --trace-out bench/results/teapot-full-gpu.trace.json --label teapot-full-gpu
node .agents/skills/chrome-trace/scripts/trace.mjs drag --mesh teapot --mode baked --frame-details --label teapot-drag
node .agents/skills/chrome-trace/scripts/trace.mjs motion --mesh garden --report --markdown-out bench/results/garden-trace.md
node .agents/skills/chrome-trace/scripts/trace.mjs compare bench/results/before.json bench/results/after.json --markdown-out bench/results/trace-compare.md

Use trace.mjs motion for steady bench motion across perf and nonvoxel pages, cadence buckets, DOM samples, render stats, and tag counts.

Add --frame-details to motion traces when you need slowest/fastest frame attribution instead of only bucket averages. On nonvoxel pages this also enables page-work samples for camera.update, scene.applyCamera, and input/control callbacks when available. Add --layer-details when compositor/layer shape is part of the question; it records LayerTree counts, layer aggregates by DOM tag/class (leaf:b, leaf:u, polycss-camera, etc.), largest layers, and compositing reasons. Add --trace-out when the raw Chrome trace should be preserved for DevTools.

Add --gpu-details when render pass timing is the current question and the trace still needs to stay reasonably sized. Light mode keeps the normal GPU/viz timeline categories and adds only disabled-by-default-viz.gpu_composite_time; render-pass attribution still comes from base events such as DirectRenderer::DrawFrame and DirectRenderer::DrawRenderPass. It intentionally avoids per-quad, Skia command, and GPU service spam.

Use --deep-gpu or --gpu-details full only for rare forensic runs that truly need per-quad/Skia/overdraw detail. Full mode also enables disabled-by-default-viz.quads, disabled-by-default-viz.triangles, disabled-by-default-viz.overdraw, disabled-by-default-gpu.debug, and disabled-by-default-skia.gpu; raw traces can become hundreds of MB and timing can be heavily perturbed.

Use trace.mjs drag for real PolyOrbitControls pointer-drag traces on nonvoxel-vanilla.html. This runner knows the non-voxel readiness hooks, camera state, interaction stats, and per-frame page-work samples.

Use trace.mjs generic for arbitrary pages and interactions that are not covered by a polycss bench page.

When interpreting PolyCSS traces, map the result back to the render model:

  • FunctionCall, EventDispatch, FireAnimationFrame: JS/input work. Unexpected sustained per-frame work is suspicious outside imported skeletal animation.
  • UpdateLayoutTree, RecalculateStyles: style recalculation, often CSS variable or selector invalidation cost.
  • Layout: layout; should stay low for transform/CSS-var-driven motion.
  • PrePaint, Paint, PaintArtifactCompositor::Update, Layerize: paint/compositing setup.
  • LayerTreeImpl::UpdateDrawProperties, draw_property_utils::ComputeDrawPropertiesOfVisibleLayers, LayerTreeHostImpl::PrepareToDraw, MainFrame.Draw, SubmitCompositorFrame: compositor-side cost.
  • Graphics.Pipeline, DisplayScheduler::DrawAndSwap, DirectRenderer::DrawFrame, DirectRenderer::DrawRenderPass: GPU/viz drawing pipeline. Treat these as browser output work, and compare them against layer details before changing app JS.
  • gpuVizRenderPass, gpuVizTiles, gpuVizGpuService: opt-in --gpu-details attribution buckets for render pass, coarse tile/raster playback, and GPU service events.
  • gpuVizQuads and gpuVizSkia: usually require --gpu-details full / --deep-gpu; treat them as high-overhead forensic signals.
  • RasterTask, image decode events: raster/bitmap work, usually atlas or tile work.

Trace event durations are inclusive and often nested, especially GPU/viz and scheduler events. Use group ms/frame as attribution evidence and for before/after deltas, not as exclusive slices that must add up to frame time.

Generic Capture

For arbitrary pages, use trace.mjs generic:

bash
node .agents/skills/chrome-trace/scripts/trace.mjs generic \
  --url http://127.0.0.1:3000 \
  --ready-js "window.appReady === true" \
  --action drag \
  --selector "#viewport" \
  --drag "480,0" \
  --duration 1200 \
  --steps 90 \
  --summary-out trace-summary.json \
  --trace-out trace.json

Useful alternatives:

bash
node .agents/skills/chrome-trace/scripts/trace.mjs generic --url http://127.0.0.1:3000 --action wait --sample 3000
node .agents/skills/chrome-trace/scripts/trace.mjs generic --url http://127.0.0.1:3000 --action eval --eval "window.rotateScene?.(Math.PI / 2)"
node .agents/skills/chrome-trace/scripts/trace.mjs generic --url http://127.0.0.1:3000 --action scroll --scroll "0,900"

Comparing Runs

Use --report on a runner to generate a Markdown report after capture, or use trace.mjs report on an existing summary JSON:

bash
node .agents/skills/chrome-trace/scripts/trace.mjs report bench/results/garden.json --markdown-out bench/results/garden.md

Use trace.mjs compare on summary JSON files from any runner:

bash
node .agents/skills/chrome-trace/scripts/trace.mjs compare before.json after.json --markdown-out trace-compare.md

Read positive deltas in frame_time_*_ms and trace group ms/frame as more expensive after the change. Read positive FPS deltas as better. Reports include a Quick Read section that calls out p95 frame time and the dominant trace group.

Reporting

Keep the report evidence-led and compact:

  • State the exact command, page, viewport, action, warmup, and sample/settle windows.
  • Include frame-time p50/p95/p99 and slowest-frame count.
  • Identify the dominant trace groups in the action window.
  • Name the top Chrome events, not only broad categories.
  • For polycss, explicitly say whether the trace supports or violates the "no JS in the render loop" expectation.
  • Mention artifacts written, especially the raw trace JSON that can be opened in Chrome DevTools Performance.

If trace markers are missing, say that alignment is weaker and rerun with marks before making a firm claim.

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 Chrome Trace AI skill do?

Capture and analyze Chrome/Chromium performance traces with Playwright around a concrete browser interaction. Use when Codex needs to answer where frame time is spent during an update, drag, rotation, scroll, animation, camera movement, light movement, DOM/CSS render change, or other performance-sensitive UI action; especially when the right answer requires per-frame Chrome trace evidence instead of FPS-only guesses.

Why use Chrome Trace on TypingMind?

Because you install it once and use it with any model. Chrome Trace 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 Chrome Trace in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/layoutit/polycss/tree/main/.agents/skills/chrome-trace. 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 Chrome Trace?

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 Chrome Trace?

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

Is the Chrome Trace AI skill free?

Yes. It is published on GitHub by layoutit 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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