evaluate-and-improve-agent

What problem does it solve?

Diagnose and improve underperforming AI agents through a disciplined, measurement-focused workflow that prevents guesswork and ensures data-driven decisions.

Core Features & Use Cases

• Baseline evaluation: establish objective scores across relevant dimensions to anchor improvements.
• Root-cause diagnosis: identify whether issues arise from task-model fit, data leakage, context management, tooling, or architecture.
• Redesign pathways: propose architecture adjustments (single-agent improvements or multi-agent patterns) and memory enhancements when needed.
• Re-evaluation: compare post-change results against the baseline to prove measurable gains and justify shipping.

Quick Start

Initiate the evaluation and improvement workflow on an existing agent by establishing a baseline, diagnosing root causes, and iterating with measurable improvements.