Loading...
Loading...
Found 21 Skills
Agent skill for performance-monitor - invoke with $agent-performance-monitor
Agent skill for performance-optimizer - invoke with $agent-performance-optimizer
Agent skill for performance-analyzer - invoke with $agent-performance-analyzer
Agent skill for performance-benchmarker - invoke with $agent-performance-benchmarker
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.
Audits Claude Code context window consumption across agents, skills, MCP servers, and rules. Identifies bloat, redundant components, and produces prioritized token-savings recommendations.
Apply optimization techniques to extend effective context capacity. Use when context limits constrain agent performance, when optimizing for cost or latency, or when implementing long-running agent systems.
Expert data analysis and manipulation for customer support operations using pandas
Expert prompt optimization for LLMs and AI systems. Use PROACTIVELY when building AI features, improving agent performance, or crafting system prompts. Masters prompt patterns and techniques.
Agent harness performance system for Claude Code and other AI coding agents — skills, instincts, memory, hooks, commands, and security scanning
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).
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.