Does it support CI/CD integration?

Absolutely. It can be integrated into GitHub Actions or other CI/CD pipelines to run analysis on every push and export results as JSON artifacts.

What types of bottlenecks can this skill detect?

It identifies bottlenecks in communication (delays, coordination), processing (utilization, task time), memory (cache hits, allocation), and network (API latency, MCP delays).

How does it improve multi-agent coordination?

It analyzes interaction patterns and suggests improvements like moving from mesh to hierarchical topologies to reduce coordination overhead.

Can this skill automatically fix performance issues?

Yes, using the --fix flag, it can apply automatic optimizations such as switching topologies, enabling smart caching, and adjusting agent priorities.

What report formats are available?

The skill generates detailed performance reports in HTML (for browser viewing), Markdown (for documentation), and JSON (for programmatic analysis).

Performance Analysis

Name: Performance Analysis
Author: whrit

bywhrit

Analíticas y Monitorización

Identifies performance bottlenecks and provides actionable optimization recommendations for Claude Flow agent swarms.

Acerca de

The Performance Analysis skill is a comprehensive suite designed to monitor and optimize the efficiency of Claude Flow swarms. It empowers developers to detect critical bottlenecks in communication, processing, memory, and networking while providing real-time profiling and historical analysis. By generating detailed reports in multiple formats and offering AI-powered 'Quick Fix' suggestions, this skill ensures that multi-agent workflows remain fast, resource-efficient, and scalable.

Características Principales

CI/CD integration for automated performance threshold monitoring
Automated 'Quick Fix' capabilities to apply topology and caching optimizations
Real-time bottleneck detection across communication, processing, and memory
Deep analysis of agent utilization and parallel execution efficiency
0 GitHub stars
Multi-format report generation including HTML, JSON, and Markdown

Casos de Uso

Reducing task completion times by identifying and parallelizing sequential agent operations
Generating automated weekly performance audits for production agent swarms
Optimizing high-latency communication between agents in complex swarm topologies

Acerca de

Características Principales

CI/CD integration for automated performance threshold monitoring
Automated 'Quick Fix' capabilities to apply topology and caching optimizations
Real-time bottleneck detection across communication, processing, and memory
Deep analysis of agent utilization and parallel execution efficiency
0 GitHub stars
Multi-format report generation including HTML, JSON, and Markdown

Casos de Uso

Reducing task completion times by identifying and parallelizing sequential agent operations
Generating automated weekly performance audits for production agent swarms
Optimizing high-latency communication between agents in complex swarm topologies