broad-performance-investigation

Analyze Truffle language implementations to prioritize performance theories from benchmarks and profiling.

Updated Aug 27, 2026

Search Tags:#graalvm #performance-analysis #truffle #cpu-sampler #broad-performance #igv-analysis

Ready to run

npx skills add https://github.com/antonykamp/cc-truffle-performance-plugin --skill broad-performance-investigation

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: broad-performance-investigation
Source: https://github.com/antonykamp/cc-truffle-performance-plugin/tree/main/skills/broad-performance-investigation
Command: npx skills add https://github.com/antonykamp/cc-truffle-performance-plugin --skill broad-performance-investigation

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Systematic analysis of Truffle language implementations to identify and prioritize performance opportunities, delivering actionable optimization theories.

Core Features & Use Cases

Loads BENCHMARK_BASELINE.md and timing data to establish current performance baselines.
Coordinates four mandatory analysis steps (code analysis, CPU sampler, memory profiler, IGV analysis) to surface findings with equal weight.
Generates tier-specific performance theories and orchestrates deep-performance-investigation when findings are uncertain, enabling a ready-to-implement plan.

Quick Start

Run broad-performance-investigation against your Truffle language implementation to generate a prioritized set of performance theories for the current tier.

Frequently Asked Questions about broad-performance-investigation

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

FAQPage Schema

How do I identify performance optimization opportunities in a Truffle language implementation?▼

To identify performance optimization opportunities in a Truffle language implementation, you need systematic analysis across benchmarking, code analysis, CPU sampling, memory profiling, and IGV inspection to generate actionable theories.

What is the best way to analyze GraalVM CPU sampler data for performance bottlenecks?▼

Analyzing GraalVM CPU sampler data requires coordinating findings with code analysis, memory profiling, and IGV inspection to ensure equal weight, generating tier-specific theories ready for implementing performance fixes.

Do I need benchmark baseline data before starting Truffle performance analysis?▼

Yes, Truffle performance analysis requires a BENCHMARK_BASELINE.md file and timing data as mandatory inputs to establish current performance baselines and produce prioritized optimization theories.

How does IGV analysis contribute to uncovering Truffle performance optimizations?▼

IGV analysis contributes to uncovering Truffle performance optimizations by acting as one of four mandatory analysis steps, inspecting compiler graphs to surface findings that form actionable performance theories.

What should I do when Truffle performance investigation findings are uncertain?▼

When Truffle performance investigation findings are uncertain, the process orchestrates a deep-performance-investigation to resolve ambiguities and deliver a ready-to-implement plan for the current severity tier.

Are there limitations to using a broad performance investigation approach for GraalVM?▼

A broad performance investigation for GraalVM is limited to producing tier-specific PERFORMANCE_THEORIES.md, meaning it identifies opportunities but requires a subsequent implementing-performance-fixes step to execute changes.