perfetto-trace-analysis

Analyze Perfetto trace files to identify Android performance issue root causes.

Updated Jul 6, 2026
One-click install
npx skills add https://github.com/shirulot/codex-skill --skill perfetto-trace-analysis-shirulot
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: perfetto-trace-analysis
Source: https://github.com/shirulot/codex-skill/tree/main/perfetto-trace-analysis
Command: npx skills add https://github.com/shirulot/codex-skill --skill perfetto-trace-analysis-shirulot

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill resolves complex Android performance issues like latency, jank, and memory pressure by providing a rigorous, evidence-based framework for analyzing Perfetto trace files.

Core Features & Use Cases

  • Iterative Investigation: Uses expert-vetted domain hints to systematically isolate bottlenecks across CPU, Graphics, I/O, IPC, Memory, and Power subsystems.
  • Chain of Evidence: Maintains a strict, verifiable scratchpad of findings to ensure conclusions are backed by data rather than assumptions.
  • Use Case: When an application experiences intermittent UI jank, this Skill identifies the root cause by correlating frame timeline deviations with thread states, binder transactions, and kernel-level scheduling delays.

Quick Start

Analyze the provided trace file named trace_001.perfetto-trace to identify the root cause of the reported application latency.

Frequently Asked Questions about perfetto-trace-analysis

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I find the root cause of Android jank using a Perfetto trace?

To analyze memory pressure in Android with Perfetto, you execute iterative SQL queries across system subsystems. This isolates bottlenecks and verifies hypotheses using a strict scratchpad of findings, ensuring conclusions about memory issues are backed by data.

What is the best way to profile Android app latency with SQL?

The best way to profile Android app latency with SQL is using iterative SQL-based investigations across CPU, Graphics, I/O, IPC, Memory, and Power subsystems. This systematically isolates bottlenecks and verifies hypotheses to establish a verifiable chain of evidence.

Can I use SQL to correlate binder transactions with UI frame drops in Android profiling?

Yes, you can use SQL to correlate binder transactions with UI frame drops in Android profiling. By querying Perfetto trace files, you can identify root causes of intermittent UI jank by correlating frame timeline deviations with binder transactions and thread states.

Does Perfetto trace analysis support debugging kernel-level scheduling delays?

Yes, Perfetto trace analysis supports debugging kernel-level scheduling delays. It isolates bottlenecks across system subsystems including CPU and Power, allowing you to correlate kernel-level scheduling delays with frame timeline deviations to resolve application latency.

What are the limitations of assumptions when debugging Android performance issues with Perfetto?

When debugging Android performance issues with Perfetto, limitations of assumptions are mitigated by maintaining a strict, verifiable scratchpad of findings. This ensures conclusions regarding latency and memory pressure are rigorously backed by data rather than guesswork.