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perfetto-sql

Translate natural language performance requests into validated Perfetto SQL queries.

Updated Jun 26, 2026
Search Tags:#sql#android#performance profiling#perfetto#trace analysis#trace_processor
One-click install
npx skills add https://github.com/yash-garg/pi-config --skill perfetto-sql-yash-garg
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: perfetto-sql
Source: https://github.com/yash-garg/pi-config/tree/main/skills/perfetto-sql
Command: npx skills add https://github.com/yash-garg/pi-config --skill perfetto-sql-yash-garg

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill helps developers analyze complex Android performance traces by translating natural language investigation goals into reliable Perfetto SQL queries, reducing the difficulty of manual trace exploration.

Core Features & Use Cases

  • Natural Language Query Generation: Converts performance analysis requests into syntactically valid Perfetto SQL while following trace analysis best practices.
  • Trace Data Analysis Guidance: Helps extract slice, thread, memory, CPU, and startup-related information from Android Perfetto traces using trace_processor.
  • SQL Validation Workflow: Applies schema research, query validation, idempotency rules, and execution checks to produce dependable trace analysis results.

Quick Start

Ask the perfetto-sql skill to analyze an Android trace and find the performance bottleneck related to a specific behavior.

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?▼

To analyze Android performance traces, you can translate natural language requests into validated Perfetto SQL queries targeting slices, threads, memory, CPU scheduling, and startup data using trace_processor.

How does natural language conversion work for trace_processor queries?▼

Natural language conversion works by translating performance analysis requests into syntactically valid Perfetto SQL, applying schema validation, idempotency rules, and execution checks to ensure reliable trace analysis results.

Can I analyze CPU scheduling and memory usage in Android Perfetto traces?▼

Yes, you can extract CPU scheduling, memory, thread, and startup information from Android Perfetto traces by generating and executing validated SQL queries through trace_processor.

What is the best way to find startup bottlenecks in Android trace data?▼

The best way to find startup bottlenecks is to translate your investigation goals into safe Perfetto SQL queries, allowing you to explore slices and thread execution data within the trace_processor.

Do I need to know SQL schema details to analyze Perfetto traces?▼

No, you do not need deep SQL schema knowledge beforehand, because the query generation process includes Perfetto schema research and validation to construct dependable queries automatically.

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