perfetto-sql

Name: perfetto-sql
Availability: InStock
Author: mymx2

Translate natural language intents into Perfetto SQL queries for Android trace analysis.

4|Updated Jun 10, 2026

Search Tags:#performance #profiling #sql #trace #android #perfetto

Ready to run

npx skills add https://github.com/mymx2/foreman --skill perfetto-sql-mymx2

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: perfetto-sql
Source: https://github.com/mymx2/foreman/tree/main/.qoder/skills.collected/skills/perfetto-sql
Command: npx skills add https://github.com/mymx2/foreman --skill perfetto-sql-mymx2

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This skill bridges the gap between complex Android performance trace data and actionable insights by automating the generation and execution of Perfetto SQL queries.

Core Features & Use Cases

Natural Language to SQL: Converts high-level performance questions into precise, syntactically correct Perfetto SQL queries.
Standard Library Integration: Leverages the Perfetto Standard Library to ensure queries use optimized, pre-computed views for CPU, scheduling, and memory analysis.
Use Case: Quickly identify the root cause of app startup jank or excessive CPU usage by querying trace events without manually navigating the complex Perfetto schema.

Quick Start

Use the perfetto-sql skill to analyze the provided trace file and calculate the total duration of all slices matching the name pattern RenderThread.

Frequently Asked Questions about perfetto-sql

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

FAQPage Schema

How do I write Perfetto SQL queries for Android trace analysis without knowing the schema?▼

Perfetto SQL queries can be generated automatically from natural language. This skill translates high-level performance questions into syntactically correct SQL, leveraging the Perfetto Standard Library to navigate complex trace schemas for you.

Can I analyze Android performance trace files locally using natural language?▼

Yes, you can analyze local Android trace files by translating natural language intents into Perfetto SQL. The skill executes generated queries using the trace_processor wrapper to extract slice, thread, and memory performance metrics directly.

What is the best way to identify app startup jank or CPU usage from an Android trace?▼

The best way to identify startup jank or CPU usage is querying trace events with Perfetto SQL. This skill converts your performance questions into optimized queries against pre-computed views for CPU, scheduling, and memory analysis.

Does Perfetto SQL generation work with the Perfetto Standard Library for schema validation?▼

Yes, Perfetto SQL generation works directly with the Perfetto Standard Library. The skill adheres to strict schema validation, idempotency, and performance best practices, ensuring queries use optimized, pre-computed views for accurate trace analysis.

How do I calculate the total duration of specific slices like RenderThread in an Android trace?▼

To calculate total duration for slices like RenderThread, ask a natural language question about your trace file. The skill generates and executes a Perfetto SQL query against the local trace data to return the precise performance metric.