perfetto-trace-analysis

Analyze Perfetto trace files to diagnose Android latency, memory pressure, or UI jank.

Updated May 22, 2026
One-click install
npx skills add https://github.com/ekawijayasusilo/kmp_template --skill perfetto-trace-analysis-ekawijayasusilo
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: perfetto-trace-analysis
Source: https://github.com/ekawijayasusilo/kmp_template/tree/main/.claude/skills/perfetto-trace-analysis
Command: npx skills add https://github.com/ekawijayasusilo/kmp_template --skill perfetto-trace-analysis-ekawijayasusilo

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill helps you diagnose Android performance problems by analyzing Perfetto trace data to identify the root cause of latency, memory issues, or UI jank.

Core Features & Use Cases

  • Trace-driven root-cause analysis: Uses a structured, evidence-first workflow to iteratively form hypotheses, collect metrics, and drill down to verified causes.
  • Domain-aware investigation: Applies expert-vetted techniques across CPU, Graphics, I/O, IPC, Memory, and Power via Domain Hints.
  • Safe Perfetto SQL generation: Requires reading the SQL reference and follows its Execution Protocol for correct schemas, modules, idempotency, and overlap-safe time filtering.

Quick Start

Ask the AI to analyze your Perfetto trace file and explain the likely root cause of the latency or jank you are seeing, using the provided trace analysis workflow.

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 UI jank using a Perfetto trace?

Android UI jank root cause analysis uses Perfetto trace files to identify latency, memory pressure, or rendering issues. The Skill applies an evidence-first workflow to iteratively form hypotheses, collect metrics, and drill down to verified causes across app and system activity.

Can I use SQL queries to debug Android performance issues in Perfetto traces?

SQL queries debug Android performance in Perfetto traces by validating schemas, ensuring idempotency, and applying overlap-safe time filtering. The Skill reads the SQL reference and follows its Execution Protocol to connect symptoms to thread and process states.

What's the best way to diagnose memory pressure and latency in Android apps?

Diagnosing memory pressure and latency in Android apps requires analyzing Perfetto trace data across CPU, Graphics, I/O, IPC, Memory, and Power domains. The Skill applies expert-vetted techniques and domain-aware investigation to isolate package-specific performance problems.

How does Perfetto trace analysis connect UI jank symptoms to specific thread states?

Perfetto trace analysis connects UI jank symptoms to thread states through a chain-of-evidence scratchpad and schema-validated SQL queries. It requires overlap-correct time filtering to accurately map dependencies between process states and performance bottlenecks.

Do I need a specific trace format to investigate Android app slowness with Perfetto?

Investigating Android app slowness with Perfetto requires a Perfetto trace file containing app and system activity data. The Skill analyzes this trace input to answer broad questions about app performance or perform targeted, package-specific diagnoses.

Why does my Perfetto SQL query return incorrect data during trace analysis?

Perfetto SQL queries return incorrect data during trace analysis when they lack schema validation or overlap-safe time filtering. The Skill enforces strict compliance with the SQL reference Execution Protocol to ensure correct schemas, modules, and idempotency in query results.