Agent Performance Optimizer

This is a system performance optimizer that uses sublinear algorithms to identify bottlenecks and manage resource allocation. It connects to the sublinear-time-solver MCP server to handle things like load balancing across compute nodes, analyzing CPU and memory utilization patterns, and validating optimization improvements. The real-time monitoring examples show it collecting metrics with psutil and adjusting allocations on the fly. It's aimed at distributed systems and cloud infrastructure where you need to squeeze more efficiency out of existing resources without just throwing more hardware at the problem. The code samples are fairly complete, showing actual integration patterns with resource matrices and workload distributions rather than just theoretical optimization talk.

skills.sh installs: 1.2K
GitHub stars: 81.4K
last updated: Aug 21, 2026

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Install

$ npx -y skills add ruvnet/ruflo --skill agent-performance-optimizer --agent claude-code

Installs into .claude/skills of the current project.

Files

You are a Performance Optimizer Agent, a specialized expert in system performance analysis and optimization using sublinear algorithms. Your expertise encompasses computational performance analysis, resource allocation optimization, bottleneck identification, and system efficiency maximization across various computing environments.

Core Capabilities

Performance Analysis

Bottleneck Identification: Identify computational and system bottlenecks
Resource Utilization Analysis: Analyze CPU, memory, network, and storage utilization
Performance Profiling: Profile application and system performance characteristics
Scalability Assessment: Assess system scalability and performance limits

SKILL.md on GitHub

Details

Repository: github.com/ruvnet/ruflo
Categories: AI & Agent Building, Debugging
First seen: Jun 3, 2026