| name | performance-analysis |
| version | 1.1.0 |
| description | Performance analysis, bottleneck detection, and optimisation for Claude Flow swarms. Use when profiling swarm performance, diagnosing slow agents, or tuning topology and resource allocation. |
| category | monitoring |
| tags | ["performance","bottleneck","optimisation","profiling","metrics","analysis"] |
| author | Claude Flow Team |
Performance Analysis Skill
Identify bottlenecks, profile swarm operations, generate performance reports, and
apply optimisation recommendations for Claude Flow swarms.
When To Use
- Profiling swarm performance or diagnosing slow agents
- Detecting communication / processing / memory / network bottlenecks
- Generating performance reports (json/html/markdown) for review or CI/CD
- Tuning topology, concurrency, caching, and resource allocation
When Not To Use
- CUDA GPU kernel profiling → use the cuda skill
- Full dev pipelines with quality gates and testing → use build-with-quality
- Truth scoring and automatic rollback of bad changes → use verification-quality
- General swarm orchestration without a performance focus → use swarm-advanced
- AgentDB vector-search performance tuning → use agentdb-vector-search
Quick Start
npx claude-flow bottleneck detect
npx claude-flow analysis performance-report --format html --include-metrics
npx claude-flow bottleneck detect --fix --threshold 15
From Claude Code (MCP):
mcp__claude-flow__bottleneck_analyze({ timeRange: "1h", threshold: 20, autoFix: false })
Core Capabilities
- Bottleneck detection — communication, processing, memory, and network,
with real-time profiling and severity-ranked output.
- Report generation — executive summary, metrics, bottleneck analysis, and
prioritized recommendations in json/html/markdown.
- Optimisation —
--fix applies topology, caching, concurrency, priority,
and resource optimisations; review before applying.
References
Load these on demand for the full detail:
references/bottleneck-detection.md —
bottleneck detect options, the metric taxonomy, output format, common
patterns, and MCP integration (JSON result shapes).references/reporting.md —
analysis performance-report formats, sections, examples, and a sample report.references/optimisation-and-operations.md —
--fix catalog, expected performance impact, continuous monitoring, CI/CD
integration, custom scripts, best practices, and troubleshooting recipes.
Related
npx claude-flow swarm monitor — real-time monitoringnpx claude-flow token usage — token optimisation analysisnpx claude-flow cache manage — cache optimisationnpx claude-flow agent metrics — agent performance metrics- Swarm Monitoring · Memory Management
Version: 1.1.0 · Last Updated: 2026-07-28 · Maintainer: Claude Flow Team
