Agent skill

Automated Tracing

Automated Tracing & Performance Telemetry in Chromium using Perfetto and Telemetry benchmarks.

BSD-3-ClauseAuto-check passedDatabases

Install Automated Tracing

skills CLI

$ npx skills add nwjs/chromium.src --skill automated-tracing -a claude-code

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

GitHub CLI

$ gh skill install nwjs/chromium.src automated-tracing --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/nwjs/chromium.src.git skills-src && mkdir -p .claude/skills && cp -r skills-src/agents/skills/automated-tracing .claude/skills/automated-tracing && 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/

Paste into Claude Code

Install the "automated-tracing" agent skill from https://github.com/nwjs/chromium.src/tree/main/agents/skills/automated-tracing into .claude/skills/automated-tracing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "automated-tracing", then confirm the skill loads.

Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

$skill-installer

$skill-installer install https://github.com/nwjs/chromium.src/tree/main/agents/skills/automated-tracing

Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.

skills CLI

$ npx skills add nwjs/chromium.src --skill automated-tracing -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install nwjs/chromium.src automated-tracing --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/nwjs/chromium.src.git skills-src && mkdir -p .agents/skills && cp -r skills-src/agents/skills/automated-tracing .agents/skills/automated-tracing && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "automated-tracing" agent skill from https://github.com/nwjs/chromium.src/tree/main/agents/skills/automated-tracing into .agents/skills/automated-tracing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "automated-tracing", then confirm the skill loads.

Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add nwjs/chromium.src --skill automated-tracing -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install nwjs/chromium.src automated-tracing --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/nwjs/chromium.src.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/agents/skills/automated-tracing .cursor/skills/automated-tracing && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "automated-tracing" agent skill from https://github.com/nwjs/chromium.src/tree/main/agents/skills/automated-tracing into .cursor/skills/automated-tracing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "automated-tracing", then confirm the skill loads.

Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

gemini skills install

$ gemini skills install https://github.com/nwjs/chromium.src.git --path agents/skills/automated-tracing

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add nwjs/chromium.src --skill automated-tracing -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install nwjs/chromium.src automated-tracing --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/nwjs/chromium.src.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/agents/skills/automated-tracing .gemini/skills/automated-tracing && rm -rf skills-src

Use ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.

Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/

Paste into Gemini CLI

Install the "automated-tracing" agent skill from https://github.com/nwjs/chromium.src/tree/main/agents/skills/automated-tracing into .gemini/skills/automated-tracing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "automated-tracing", then confirm the skill loads.

Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

GitHub CLI

$ gh skill install nwjs/chromium.src automated-tracing

Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).

skills CLI

$ npx skills add nwjs/chromium.src --skill automated-tracing -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/nwjs/chromium.src.git skills-src && mkdir -p .github/skills && cp -r skills-src/agents/skills/automated-tracing .github/skills/automated-tracing && rm -rf skills-src

Use ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.

GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/

Paste into GitHub Copilot

Install the "automated-tracing" agent skill from https://github.com/nwjs/chromium.src/tree/main/agents/skills/automated-tracing into .github/skills/automated-tracing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "automated-tracing", then confirm the skill loads.

GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add nwjs/chromium.src --skill automated-tracing -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install nwjs/chromium.src automated-tracing --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/nwjs/chromium.src.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/agents/skills/automated-tracing .opencode/skills/automated-tracing && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "automated-tracing" agent skill from https://github.com/nwjs/chromium.src/tree/main/agents/skills/automated-tracing into .opencode/skills/automated-tracing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "automated-tracing", then confirm the skill loads.

OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

Facts

Skill name: automated-tracing
GitHub stars: 160
Token cost: ~1.5k tokens
SKILL.md length: 491 words
Files: 3 (incl. scripts)
Skills in repo: 64
Repo updated: Oct 3, 2026
First seen: Oct 8, 2026
Licence: BSD-3-Clause

At a glance

Automated Tracing & Performance Telemetry in Chromium using Perfetto and Telemetry benchmarks.

Works in 4 steps: Prerequisites → Safety & Sandbox Compliance (Zero-Grant… → Execution & Capture Workflow → …
You need to launch the browser binary
SKILL.md covers 1. Prerequisites, 2. Safety & Sandbox Compliance…, 3. Execution & Capture Workflow and 4. Output Contract
Runs Python scripts from its folder; calls python3 and adb

What it does

Automated Tracing is an agent skill from nwjs/chromium.src. Automated Tracing & Performance Telemetry in Chromium using Perfetto and Telemetry benchmarks. Use when you need to launch the browser binary, execute a specific scenario/story, and collect Perfetto traces. Don't use for trace analysis (use analyzing-sql-traces).

Its SKILL.md is about 1.5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 3 other files, including scripts (for example `scripts/migrate_profile.py` and `scripts/run_warm_benchmark.py`).

It sits in Databases. It works with SQL and Android. The repository describes itself as: Chromium codebase with NW.js modifications. Based on https://chromium.googlesource.com/chromium/src.git. The licence is BSD-3-Clause.

When your agent uses it

You need to launch the browser binary
Execute a specific scenario/story
Collect Perfetto traces
Trace analysis (use analyzing-sql-traces)

Example prompts

“/automated-tracing”

Requirements

Python 3

Workflow steps

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

Prerequisites
Safety & Sandbox Compliance (Zero-Grant Rule)
Execution & Capture Workflow
Output Contract

What it can do on your machine

Read from SKILL.md and the folder at commit a9e8946. 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
Ships 2 files in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
- python3
- adb
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

Automated Tracing loads about 1.5k tokens when it runs. Until then it costs about 70 tokens; SKILL.md has 491 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~70
When it runs · the whole SKILL.md, loaded when a task matches: ~1.5k

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); the scripts in this folder are not scanned.

SKILL.md

The full file from nwjs/chromium.src at commit a9e8946, republished under its BSD-3-Clause licence (© nwjs). 491 words, ~1,517 tokens.

Download SKILL.mdSave it as .claude/skills/automated-tracing/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.

name: automated-tracing
description: Automated Tracing & Performance Telemetry in Chromium using Perfetto and Telemetry benchmarks. Use when you need to launch the browser binary, execute a specific scenario/story, and collect Perfetto traces. Don't use for trace analysis (use analyzing-sql-traces).

Automated Tracing & Performance Telemetry

This skill guides the agent through the process of automated tracing in Chromium to capture performance profiles on Desktop or Android Device/Emulator.

1. Prerequisites

For Desktop (Linux/Mac/Windows)

A compiled Chrome executable (typically out/Default/chrome).
A targeted Scenario/Story (e.g., omnibox:search inside the desktop_ui benchmark).

For Android (Device/Emulator)

A compiled Chrome Android APK (typically out/emulator/apks/ChromePublic.apk).
A pre-connected Android device or running emulator.
A targeted Scenario/Story (e.g., system_health.common_mobile benchmark).

2. Safety & Sandbox Compliance (Zero-Grant Rule)

To prevent triggering user permission/access grant prompts during automated execution:

ALWAYS redirect Telemetry output artifacts to the parent E2E session's unified capture directory inside the workspace: out/e2e_nla_run_{parent_session_id}/capture/ (where {parent_session_id} is passed by the Orchestrator).
NEVER call command-line utilities like mkdir, ls, touch, or rm via shell commands.
NEVER run terminal verification commands (such as python3 -c "import os; ..." or ls -lh or test -f) to check file existence or size.
ALWAYS rely on standard python script APIs or built-in benchmark tool logic to create directories programmatically.
ALWAYS let down-stream tools (like the trace analyzer script) perform validation internally. If the trace is invalid or empty, the analyzer will fail loudly and safely.
NEVER let Telemetry write to the default tools/perf/artifacts/ workspace directory.

3. Execution & Capture Workflow

Step A: Identify Target Android Device (Android Only)

Before running the benchmark on Android, identify the connected device/emulator:

Run adb devices to list the attached devices.
Select the target device serial based on the following rules:
- Zero devices found: Abort the execution and ask the user to connect a device or start an emulator.
- One device found: Automatically select this device serial.
- Multiple devices found:
  - If a specific device argument/serial is provided, match against it.
  - Otherwise, present the list of connected devices to the user and ask them to select one.

Show full SKILL.md (197 more words)Show less

Step B: Execute Telemetry Benchmark

Select either Cold Run (default) or Warm Run based on the investigation requirements.

1. For Cold Runs (Default)

No pre-warmup is needed. Telemetry will automatically start with a clean profile.

For Desktop: Run the run_benchmark command directly using the xvfb.py virtual display wrapper:

bash

./testing/xvfb.py vpython3 tools/perf/run_benchmark run desktop_ui \
  --story={story_name} \
  --browser=exact \
  --browser-executable={chrome_binary} \
  --extra-chrome-categories=omnibox,navigation,blink,cc,gpu,toplevel \
  --output-dir=out/e2e_nla_run_{parent_session_id}/capture/

For Android (Device/Emulator): Run the run_benchmark command with the --device argument set to the identified device serial:

bash

vpython3 tools/perf/run_benchmark run {benchmark_name} \
  --story={story_name} \
  --browser=exact \
  --browser-executable=out/emulator/apks/ChromePublic.apk \
  --device={device_serial} \
  --extra-chrome-categories=omnibox,navigation,blink,cc,gpu,toplevel,net,Java \
  --output-dir=out/e2e_nla_run_{parent_session_id}/capture/

2. For Warm Runs (GPU & HTTP Caches Warmed)

To capture a warm run (bypassing GPU shader compilation and static network loading), you should use the automated wrapper script run_warm_benchmark.py.

The script automatically coordinates the warmup run, profile migration/cleanup, final warm run, and temporary directory deletion.

For Android:

bash

vpython3 .agents/skills/automated-tracing/scripts/run_warm_benchmark.py \
  --benchmark={benchmark_name} \
  --story={story_name} \
  --browser-executable=out/emulator/apks/ChromePublic.apk \
  --device={device_serial} \
  --output-dir=out/e2e_nla_run_{parent_session_id}/capture/ \
  [--delete-state] \
  --extra-chrome-categories=omnibox,navigation,blink,cc,gpu,toplevel,net,Java \
  [extra_args...]

For Desktop:

bash

vpython3 .agents/skills/automated-tracing/scripts/run_warm_benchmark.py \
  --benchmark=desktop_ui \
  --story={story_name} \
  --browser-executable=out/Default/chrome \
  --output-dir=out/e2e_nla_run_{parent_session_id}/capture/ \
  [--delete-state] \
  --extra-chrome-categories=omnibox,navigation,blink,cc,gpu,toplevel,net \
  [extra_args...]

(Note: The script automatically detects if a display is present on Linux and wraps the desktop Chrome execution with xvfb.py if needed. Any unrecognized extra arguments [extra_args...] are forwarded directly to the underlying run_benchmark commands.)

Step C: Locate the Captured Trace

Once the benchmark completes successfully, find the Perfetto trace file inside the redirected folder. The path structure is: out/e2e_nla_run_{parent_session_id}/capture/artifacts/run_{timestamp}/{story_sanitized}_1/trace/trace.pb

Verify the trace exists and is non-empty.

4. Output Contract

Report back to the caller with the absolute path of the captured trace:

json

{
  "status": "SUCCESS",
  "trace_file_path": "out/e2e_nla_run_{parent_session_id}/capture/artifacts/run_{timestamp}/{story_sanitized}_1/trace/trace.pb",
  "build_dir": "out/emulator/"
}

Files

SKILL.md and 2 other files (scripts) in agents/skills/automated-tracing of nwjs/chromium.src.

SKILL.md
scripts/migrate_profile.py
scripts/run_warm_benchmark.py

Open the folder on GitHubat commit a9e8946

Compare with similar skills

Automated Tracing 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.

Automated Tracing compared with similar skills
Skill	Stars	Used in	Tokens	Auto-check	Licence	Repo updated
Automated Tracing this skillnwjs/chromium.src	160	—	~1.5k	Automated safety check: Pass	BSD-3-Clause	5 days ago
Perfetto SQLjameshnsears/QuoteUnquote	100	2 repos	~2.7k	Automated safety check: Pass	Apache-2.0	1 mo ago
Android Profilerarindamxd/camerax-android	132	2 repos	~493	Automated safety check: Pass	Apache-2.0	7 days ago
Clickhouse Logs Queriessupabase/supabase	111k	—	~2.4k	Automated safety check: Pass	Apache-2.0	today
Django Filter Benchmarksaleor/saleor	23k	—	~2.3k	Automated safety check: Pass	BSD-3-Clause	today
Citus Check Style Reindentcitusdata/citus	13k	—	~1.5k	Automated safety check: Notes	AGPL-3.0	today

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Works with

Questions about Automated Tracing

What does Automated Tracing do?

Automated Tracing & Performance Telemetry in Chromium using Perfetto and Telemetry benchmarks. src. Automated Tracing & Performance Telemetry in Chromium using Perfetto and Telemetry benchmarks.

When should I use Automated Tracing?

Automated Tracing fits situations like: you need to launch the browser binary; execute a specific scenario/story; collect Perfetto traces; trace analysis (use analyzing-sql-traces).

How do I install Automated Tracing in Claude Code?

Run `npx skills add nwjs/chromium.src --skill automated-tracing -a claude-code`. Or copy the skill folder (agents/skills/automated-tracing in nwjs/chromium.src) into .claude/skills/automated-tracing in your project. Claude Code loads it when a task matches its description.

How do I install Automated Tracing in Codex?

Run `npx skills add nwjs/chromium.src --skill automated-tracing -a codex`. Or copy the skill folder (agents/skills/automated-tracing in nwjs/chromium.src) into .agents/skills/automated-tracing in your project. Codex loads it when a task matches its description.

Can I use Automated Tracing 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 nwjs/chromium.src --skill automated-tracing -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/automated-tracing, .gemini/skills/automated-tracing, .github/skills/automated-tracing and .opencode/skills/automated-tracing in your project.

What does Automated Tracing need to run?

Going by SKILL.md and its folder, Automated Tracing needs Python for the scripts in its folder and the command-line tools its instructions call (python3 and adb). Our summary lists: Python 3.

Does Automated Tracing 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 Automated Tracing 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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Automated Tracing use?

Automated Tracing is published under the BSD-3-Clause licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Automated Tracing use?

About 1.5k tokens (SKILL.md is roughly 6.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Automated Tracing?

Skills that share tags, products or a category with Automated Tracing: Perfetto SQL (jameshnsears/QuoteUnquote, 100 stars), Android Profiler (arindamxd/camerax-android, 132 stars), Clickhouse Logs Queries (supabase/supabase, 111k stars) and Django Filter Benchmark (saleor/saleor, 23k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Automated Tracing?

nwjs (a GitHub organization) maintains it in nwjs/chromium.src, which has 160 GitHub stars. The repository holds 64 skills in this directory. The repository was last updated on October 3, 2026.

Source: nwjs/chromium.src on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Install Automated Tracing

Facts

At a glance

What it does

When your agent uses it

Example prompts

Requirements

Workflow steps

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

Automated Tracing & Performance Telemetry

1. Prerequisites

For Desktop (Linux/Mac/Windows)

For Android (Device/Emulator)

2. Safety & Sandbox Compliance (Zero-Grant Rule)

3. Execution & Capture Workflow

Step A: Identify Target Android Device (Android Only)

Step B: Execute Telemetry Benchmark

1. For Cold Runs (Default)

2. For Warm Runs (GPU & HTTP Caches Warmed)

Step C: Locate the Captured Trace

4. Output Contract

Files

Compare with similar skills

Similar skills

More from nwjs/chromium.src

Related

Questions about Automated Tracing