Evaluator-Optimizer

Generate. Judge. Revise. Stop when good enough.

Goal

• Produce stronger output through controlled iteration.
• Keep evaluator strict.
• Stop before cost or drift grows.

Rules

• Define rubric before generating.
• Separate generator and evaluator roles.
• Evaluator returns score, reasons, and fix hints.
• Set max rounds.
• Stop on pass, budget, or plateau.
• Save failing examples for rubric tuning.

Good eval signals

• Schema validity.
• Test pass rate.
• Grounding to source facts.
• Style compliance.
• Policy compliance.
• Ranking score.

Flow

1. Define pass/fail rubric.
2. Generate candidate.
3. Evaluate against rubric.
4. If pass, return candidate.
5. If fail, revise using feedback.
6. Repeat until stop condition.

Failure modes

• Evaluator too soft.
• Evaluator and generator share blind spots.
• Feedback not actionable.
• Loop overfits rubric.
• No stop rule.
• No human review path for high-risk output.

Output

## Result
- Status: pass | fail | stopped
- Rounds: [n]
- Score: [score]

## Final Output
[candidate]

## Evaluation Notes
- [reason]
- [remaining risk]