performance-profiling

Profile codebase hotspots and generate measurable optimization plans.

3|Updated Mar 24, 2026

Search Tags:#performance #codebase #profiling #bottleneck #benchmark #optimize #measurement

Ready to run

npx skills add https://github.com/ldilov/harness-forge --skill performance-profiling-ldilov

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: performance-profiling
Source: https://github.com/ldilov/harness-forge/tree/main/skills/performance-profiling
Command: npx skills add https://github.com/ldilov/harness-forge --skill performance-profiling-ldilov

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Profiling hotspots in codebases and turning performance observations into actionable next steps to improve speed and efficiency.

Core Features & Use Cases

Identify hotspots across modules, functions, and call graphs with measurable signals.
Define repeatable experiments and an evidence-backed optimization plan.
Use cases include reducing latency in a web service, cutting memory usage, or improving startup time.

Quick Start

Run the profiler on your project to surface hotspots and turn findings into a concrete optimization plan.

Frequently Asked Questions about performance-profiling

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

FAQPage Schema

How do I identify performance bottlenecks in my codebase?▼

To identify performance bottlenecks, you profile hotspots across modules, functions, and call graphs to gather measurable signals. This process translates observations into actionable next steps for improving speed and efficiency.

What is the best way to reduce latency and memory usage in a web service?▼

The best way to reduce latency and memory usage is profiling hotspots to measure CPU time and memory across input scenarios. This generates an evidence-backed optimization plan with deterministic experiments and clear success criteria.

How do I create a measurable optimization plan from profiling data?▼

You create a measurable optimization plan by translating profiling observations into repeatable experiments. This approach guides deterministic optimization efforts with clear success criteria to drive measurable performance improvements.

Can I use this to measure CPU time and memory usage across different modules?▼

Yes, you can measure CPU time and memory usage across different modules. The profiler applies to development workflows where these metrics must be evaluated across functions and input scenarios to surface hotspots.

When do I need to profile hotspots in my development workflow?▼

You need to profile hotspots when your development workflow requires measuring latency, CPU time, or memory usage. It is essential for identifying bottlenecks and producing an evidence-backed plan to drive measurable performance improvements.