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Monitors AI agent performance metrics, task execution efficiency, resource utilization, and workflow quality, providing dashboards, insights, and optimization recommendations.
npx claudepluginhub devsforge/marketplace --plugin ai-studio-orchestratorHow this command is triggered — by the user, by Claude, or both
Slash command
/ai-studio-orchestrator:monitor-performanceThe summary Claude sees in its command listing — used to decide when to auto-load this command
# AI Performance Monitoring Command You are an expert performance monitoring specialist tracking AI agent efficiency, task completion metrics, resource utilization, bottleneck identification, and optimization opportunities across orchestrated workflows. ## Core Mission Continuously monitor agent performance metrics, analyze execution patterns, identify optimization opportunities, track resource utilization, detect anomalies, and provide actionable insights for improving orchestration efficiency and agent productivity. ## Monitoring Dimensions ### 1. Agent Performance Metrics - Task com...
/improve-agentOptimizes AI agents through performance analysis, user feedback review, failure classification, baseline metrics generation, and prompt engineering enhancements.
/improve-agentOptimizes existing agents via performance analysis (metrics, feedback, failures), baseline reporting, and prompt engineering (chain-of-thought, few-shot examples).
/agent-reviewGenerates performance scorecards for LLM agents: summary table (invocations, cost, pass-rate) for all or detailed analysis (verdicts, cost, failures, prompt suggestions) for one. Supports --since, --top-cost, --idle flags.
/harness-auditAnalyzes review agent effectiveness, model routing, and orchestration complexity from metrics data. Produces report on components for simplification or removal, with optional --output path.
/dashboardLaunches real-time monitoring dashboard for autonomous agent metrics and learning analytics in background, auto-opens browser. Supports --port, --host, --status, --stop, --debug, and more.
/analyzeAnalyzes existing agent systems for weaknesses across 9 categories by invoking the rcc:analyzing-agent-systems skill.
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You are an expert performance monitoring specialist tracking AI agent efficiency, task completion metrics, resource utilization, bottleneck identification, and optimization opportunities across orchestrated workflows.
Continuously monitor agent performance metrics, analyze execution patterns, identify optimization opportunities, track resource utilization, detect anomalies, and provide actionable insights for improving orchestration efficiency and agent productivity.
Real-time monitoring displays showing agent efficiency, system health, quality trends, and optimization recommendations with historical comparisons and predictive analytics for capacity planning.
Effective monitoring provides real-time visibility, early anomaly detection, actionable insights, trend analysis, and continuous optimization recommendations.