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Found 26 Skills
Deep-dive diagnosis of how your AI agent behaves in production. Explores LangWatch analytics and traces end to end to map failure patterns, dissatisfied users, token cost hotspots, edge cases, behavior changes, and outliers, then delivers an HTML report where every finding links to real example traces. Use when you want to truly understand what your agent is doing in production.
Agent skill for performance-monitor - invoke with $agent-performance-monitor
Agent skill for performance-analyzer - invoke with $agent-performance-analyzer
Agent skill for performance-optimizer - invoke with $agent-performance-optimizer
Agent skill for performance-benchmarker - invoke with $agent-performance-benchmarker
Expert performance engineer specializing in system optimization, bottleneck identification, and scalability engineering. Masters performance testing, profiling, and tuning across applications, databases, and infrastructure with focus on achieving optimal response times and resource efficiency.
Agent harness performance system for Claude Code and other AI coding agents — skills, instincts, memory, hooks, commands, and security scanning
Expert in observing, benchmarking, and optimizing AI agents. Specializes in token usage tracking, latency analysis, and quality evaluation metrics. Use when optimizing agent costs, measuring performance, or implementing evals. Triggers include "agent performance", "token usage", "latency optimization", "eval", "agent metrics", "cost optimization", "agent benchmarking".
Use this when you need to EVALUATE OR IMPROVE or OPTIMIZE an existing LLM agent's output quality - including improving tool selection accuracy, answer quality, reducing costs, or fixing issues where the agent gives wrong/incomplete responses. Evaluates agents systematically using MLflow evaluation with datasets, scorers, and tracing. Covers end-to-end evaluation workflow or individual components (tracing setup, dataset creation, scorer definition, evaluation execution).
Agent skill for v3-performance-engineer - invoke with $agent-v3-performance-engineer
Use this skill when the user's Copilot Studio agent evaluations have come back and they need to interpret scores, diagnose root causes of underperforming test cases, find remediation steps, or analyze patterns to improve their agent. Always use this skill when the user mentions: "eval failed", "why did this fail", "triage", "diagnose failure", "low pass rate", "fix evaluation results", "not passing", "failing test cases", "evaluation results", "improve my eval scores", or any situation where eval scores need interpretation and action.
Paired benchmark orchestration for comparing coding-agent performance with recursive-mode off and on. Use when the user wants to benchmark recursive-mode, compare recursive vs non-recursive execution on the same project, generate disposable benchmark repos, capture timing/build-test logs, or write a benchmark report.