Agent Orchestration Improve Agent

This is a structured methodology for improving an existing agent when it's underperforming or failing in production. You get a four-phase workflow: baseline metrics and failure analysis, prompt engineering techniques like chain-of-thought and few-shot optimization, A/B testing with statistical validation, and controlled deployment with rollback. The real value is in the systematic approach, especially the failure mode classification and the specific testing framework with blind human evaluation. Use this when you have enough production data to diagnose what's actually broken. If you're just guessing at improvements without metrics or test cases, you're not ready for this workflow yet.

skills.sh installs: 572
GitHub stars: 43.1K
last updated: Jul 14, 2026

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Install

$ npx -y skills add sickn33/antigravity-awesome-skills --skill agent-orchestration-improve-agent --agent claude-code

Installs into .claude/skills of the current project.

Files

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.]