skills.rest
antonykamp
antonykampCOMMUNITY
Explore all skills by this author →
WebsiteGitHub

deep-performance-investigation

Profile a hotspot with CPU sampler, warnings, deopt tracing, and IGV dumps.

Updated Aug 27, 2026
Search Tags:#performance#analysis#profiling#benchmark#graalvm#truffle#deoptimization
One-click install
npx skills add https://github.com/antonykamp/cc-truffle-performance-plugin --skill deep-performance-investigation
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: deep-performance-investigation
Source: https://github.com/antonykamp/cc-truffle-performance-plugin/tree/main/skills/deep-performance-investigation
Command: npx skills add https://github.com/antonykamp/cc-truffle-performance-plugin --skill deep-performance-investigation

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Targeted profiling to quantify the impact of uncertain performance findings in Truffle/GraalVM environments, enabling data-driven decisions rather than guesswork.

Core Features & Use Cases

  • Focused profiling of a single hotspot identified during broad-performance-investigation
  • Quantitative impact estimation with confidence levels to guide optimization priorities
  • Clear falsification path when data disproves a finding

Quick Start

Provide a specific low-confidence finding from broad-performance-investigation and run targeted profiling to estimate its impact.

Frequently Asked Questions about deep-performance-investigation

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

FAQPage Schema
How do I estimate the impact of uncertain performance findings in GraalVM?▼

Targeted profiling estimates the impact of uncertain performance findings in GraalVM by applying focused CPU samplers, performance warnings, deopt tracing, and IGV dumps with precise filters to gather evidence and quantify hotspot impact.

How do I profile a specific Truffle hotspot to quantify its performance impact?▼

Profiling a specific Truffle hotspot involves applying focused tools like CPU samplers and deopt tracing with precise filters to gather evidence, returning an impact estimate with confidence or a clear falsification based on results.

What is deoptimization tracing and when do I need it for performance analysis?▼

Deoptimization tracing is a focused profiling tool used during performance analysis to track when GraalVM reverts optimized code, needed to gather evidence on uncertain findings and estimate their impact with confidence.

Can I falsify a low-confidence performance finding during targeted profiling?▼

Yes, targeted profiling can falsify a low-confidence performance finding by applying precise filters to tools like CPU samplers and IGV dumps, providing a clear falsification if the data disproves the finding.

What is the best way to analyze deoptimization issues in a Truffle environment?▼

The best way to analyze deoptimization issues in a Truffle environment is applying deopt tracing and IGV dumps with precise filters to gather evidence, returning an impact estimate with confidence or a clear falsification.

Related Skills

Explore More Software Engineering Skills→
harleypigharleypig
3

perf-review

Profile code to identify runtime performance bottlenecks and ranked hotspots.

Community
Intermediate
jtvarisjtvaris

perf-profile

Profile CPU, memory, rendering, and I/O performance to identify bottlenecks and budget overruns.

Community
Advanced
charlesjones-devcharlesjones-dev
34

performance-auditing

Identify performance bottlenecks in software applications using profiling and benchmarks.

Community
Advanced
jg-chalk-iojg-chalk-io

moai-essentials-perf

Profile CPU and memory bottlenecks across Python, Node.js, and Go applications.

Community
Advanced