Benchmarking & Optimization

Profile and optimize LiquidIL render performance across VM and compiled backends.

1|1|Updated Jan 7, 2026
One-click install
npx skills add https://github.com/tobi/liquid-il --skill benchmarking-optimization
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: Benchmarking & Optimization
Source: https://github.com/tobi/liquid-il/tree/main/.claude/skills/benchmarking
Command: npx skills add https://github.com/tobi/liquid-il --skill benchmarking-optimization

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Benchmark and optimize LiquidIL render performance to reduce render time and resource consumption across VM and compiled backends, enabling faster templates.

Core Features & Use Cases

  • Official Benchmark Suite (Primary): Run rake bench to compare render times across liquid_ruby, liquid_il (VM), liquid_il_compiled, and liquid_il_optimized_compiled.
  • Microbenchmarking & Profiling: Measure allocations and per-render costs for targeted components with bench_partials and profile_render workflows.
  • Visualization & Analysis: Generate and interpret flamegraphs and stackprof reports to identify hot paths and optimization opportunities.

Quick Start

Run the official benchmark suite with rake bench to compare render performance across engines.

Frequently Asked Questions about Benchmarking & Optimization

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

FAQPage Schema
How do I profile LiquidIL render performance to identify slow templates?

You can profile LiquidIL render performance using stackprof and benchmark scripts to generate flamegraphs and stackprof reports, which identify hot paths and optimization opportunities across VM and compiled backends.

What is the best way to benchmark LiquidIL against standard liquid_ruby?

The best way to benchmark LiquidIL against liquid_ruby is running the official benchmark suite with rake bench, which directly compares render times across liquid_ruby, liquid_il (VM), and compiled backends.

Can I measure memory allocations and per-render costs for specific LiquidIL components?

Yes, you can measure memory allocations and per-render costs for targeted LiquidIL components using the bench_partials and profile_render workflows provided for microbenchmarking and profiling.

Does LiquidIL optimization work for both VM interpreter and compiled backends in CI?

LiquidIL optimization applies to both VM interpreter and compiled backends in development and CI environments, addressing measurement, profiling, and performance improvement workflows across these configurations.

Why should I use flamegraphs for LiquidIL performance tuning?

Flamegraphs are used for LiquidIL performance tuning because they visualize stackprof reports to pinpoint hot paths and optimization opportunities, reducing render time and resource consumption.

What are the limitations of profiling LiquidIL render performance?

Profiling LiquidIL render performance requires tools like stackprof and benchmark scripts to measure CPU and memory, but limitations depend on interpreting flamegraphs accurately to identify true hot paths across backends.