agent-orchestration-improve-agentlisted

# Agent Performance Optimization Workflow Systematic improvement of existing agents through performance analysis, prompt engineering, and continuous iteration. [Extended thinking: Agent optimization requires a data-driven approach combining performance metrics, user feedback analysis, and advanced prompt engineering techniques. Success depends on systematic evaluation, targeted improvements, and rigorous testing with rollback capabilities for production safety.] ## Use this skill when - Improving an existing agent's performance or reliability - Analyzing failure modes, prompt quality, or tool usage - Running structured A/B tests or evaluation suites - Designing iterative optimization workflows for agents ## Do not use this skill when - You are building a brand-new agent from scratch - There are no metrics, feedback, or test cases available - The task is unrelated to agent performance or prompt quality ## Instructions 1. Establish baseline metrics and collect representative examples. 2. Identify failure modes and prioritize high-impact fixes. 3. Apply prompt and workflow improvements with measurable goals. 4. Validate with tests and roll out changes in controlled stages. ## Safety - Avoid deploying prompt changes without regression testing. - Roll back quickly if quality or safety metrics regress. ## Phase 1: Performance Analysis and Baseline Metrics Comprehensive analysis of agent performance using context-manager for historical data collection. ### 1.1 Gather Pe