performance-analysis

Detect performance bottlenecks in Claude Flow swarm operations.

6|3|Updated Dec 3, 2025

Search Tags:#performance #analysis #profiling #bottlenecks

Ready to run

npx skills add https://github.com/pacphi/ampel --skill performance-analysis-pacphi

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: performance-analysis
Source: https://github.com/pacphi/ampel/tree/main/.claude/skills/performance-analysis
Command: npx skills add https://github.com/pacphi/ampel --skill performance-analysis-pacphi

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Provides end-to-end performance analysis for Claude Flow swarms, bottleneck detection, and optimization recommendations.

Core Features & Use Cases

Bottleneck Detection: Identify delays in communication, work, memory, and network
Profiling: Real-time and historical performance metrics
Reporting: Multi-format reports and AI-driven optimization suggestions
MCP Integration: Tie performance results into MCP workflows

Quick Start

npx claude-flow bottleneck detect

Frequently Asked Questions about performance-analysis

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

FAQPage Schema

How do I detect performance bottlenecks in Claude Flow swarms?▼

Bottleneck detection identifies delays across communication, processing, memory, and network layers in multi-swarm deployments. Run `npx claude-flow bottleneck detect` with optional swarm-id and time-range parameters to pinpoint performance constraints and receive optimization recommendations.

Can I analyze historical performance metrics for Claude Flow operations?▼

Historical performance analysis retrieves and compares metrics across defined time ranges for swarm operations. Use the analysis command with time-range and compare options to track performance trends, export results in multiple formats, and identify recurring bottlenecks.

What performance data does profiling capture in multi-swarm deployments?▼

Real-time and historical profiling captures communication delays, work processing times, memory allocation patterns, and network latency across all swarms. Output includes structured metrics suitable for reporting, threshold-based alerting, and integration with MCP workflows.

How do I generate performance reports with optimization suggestions?▼

Performance reports combine profiling data with AI-driven recommendations using the performance-report command. Specify sections, output format, and export options to produce multi-format reports highlighting identified bottlenecks and suggested fixes.

Does performance analysis work with existing Claude Flow CLI commands?▼

Performance analysis integrates with Claude Flow operations through dedicated CLI commands—bottleneck detect, analysis, and performance-report—supporting standard options like swarm-id, threshold, format, and export for seamless workflow integration.

What scale of swarm deployments can this performance analysis handle?▼

Performance analysis applies to multi-swarm deployments across communication, processing, memory, and network layers. Threshold and include-metrics options allow filtering and focusing analysis on deployments of varying complexity and scale.