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Trace and Eval Flywheel

Agent Patterns

Summary

The trace and eval flywheel is a continuous improvement loop for agent quality. Every agent execution is traced, graded against quality criteria, and failures are collected into a regression dataset. That dataset drives prompt and logic improvements, and the cycle repeats.

How it works

  1. Trace -- capture every agent invocation: input, output, tool calls, intermediate state, latency.
  2. Grade -- evaluate each trace against quality criteria using automated graders or human review.
  3. Collect failures -- aggregate failed or low-quality traces into a structured regression dataset.
  4. Improve -- analyze the dataset, update prompts or logic, and deploy the fix.
  5. Repeat -- the improved agent generates new traces, and the cycle continues.

Components

  • Tracer: Instrumentation layer that records every step of agent execution.
  • Grader: Automated evaluator (LLM-as-judge, metric computation, or rule-based checks).
  • Regression dataset: Versioned collection of failure cases used to prevent recurring issues.
  • Improvement engine: Tooling to analyze failures, suggest fixes, and validate improvements.

Metrics

  • Improvement rate: Percentage of regression cases that pass after each improvement cycle.
  • Regression count: Number of previously-passing cases that fail after a change.
  • Grade distribution: Breakdown of traces by quality score across the system.

Build This Pattern

Copy this prompt and paste it into Claude Code, OpenCode, Codex, or Cursor to implement this pattern.

Build me a trace and eval flywheel system. Architecture: capture traces of every agent interaction (inputs, outputs, tool calls, latencies). Grade traces against success criteria. Collect failures into a regression dataset. Use the dataset to improve prompts and re-run evals. Error handling: handle trace corruption, oversized traces. Edge cases: handle low-grade-volume periods, grading disagreement. Best practices: measure improvement rate across iterations. Testing: verify that the system correctly identifies and captures failures.