perf-optimize

Profile and optimize Rust performance bottlenecks in kham-core with before/after benchmarks.

Updated Apr 15, 2026

Search Tags:#performance #optimization #profiling #rust #benchmark #kham-core

Ready to run

npx skills add https://github.com/preedep/kham --skill perf-optimize

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: perf-optimize
Source: https://github.com/preedep/kham/tree/main/.claude/skills/perf-optimize
Command: npx skills add https://github.com/preedep/kham --skill perf-optimize

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Optimizing Rust code for performance by profiling, tuning algorithms, and improving memory layout to reduce runtime, latency, and resource usage in kham-core.

Core Features & Use Cases

Profiling and benchmarking workflows to identify bottlenecks in kham-core.
Memory layout optimizations and algorithm tuning to speed up critical paths.
Reproducible improvement cycles using baselining and measurement.

Quick Start

Begin a baseline profile of the kham-core path, implement a single targeted optimization, and re-measure performance to confirm gains.

Frequently Asked Questions about perf-optimize

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

FAQPage Schema

How do I identify and optimize performance bottlenecks in Rust code?▼

To optimize Rust performance, profile the codebase to locate bottlenecks, apply targeted memory-layout improvements and algorithm tuning, then re-measure with a before/after benchmark to confirm runtime and throughput gains.

What's the best way to benchmark Rust runtime performance improvements?▼

The best way to benchmark Rust runtime improvements is establishing a baseline profile, implementing a single targeted optimization, and re-measuring to verify the performance gain through reproducible measurement cycles.

How does profiling help reduce latency and resource usage in Rust projects?▼

Profiling identifies critical execution paths causing high latency and resource usage, enabling targeted algorithm tuning and memory-layout optimizations to reduce runtime overhead in Rust projects.

Can I use this performance optimization workflow for compile-time builds and binary sizes?▼

Yes, the performance optimization workflow applies to compile-time builds, binary sizes, and runtime throughput, analyzing and improving memory layout and algorithms across all these dimensions.

When do I need to tune memory layout for Rust performance?▼

You need to tune memory layout for Rust performance when profiling reveals bottlenecks in critical paths, requiring algorithm tuning and memory restructuring to reduce runtime and improve throughput.

Do I need benchmark baselining to measure Rust code optimization results?▼

Yes, benchmark baselining is required to measure Rust code optimization results, providing a clear before/after comparison to confirm performance improvements and document changes effectively.