> ## Documentation Index
> Fetch the complete documentation index at: https://docs.obversa.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# When Should an Agent Eval Loop Stop?

> When enough reviewers accept, or when the limit you set runs out. Never when the model says it is done.

When enough reviewers accept, or when the limit you set runs out, and not
before or after. A loop that runs until a model says it is done never
stops on its own. Here the loop has a quorum and a cap: a draft goes
through a done check and independent reviewers, a repair step takes the
findings, and the loop ends when the quorum accepts or `maxIterations` is
spent. In the feature team, the feedback loop allows two returns and then
the failed verdict stands. This loop is not a benchmark eval; it decides
what happens next on this run.

## In Obversa

The limits are part of the definition, not a prompt:

```ts examples/review-loop.ts (excerpt) {5-8} theme={null}
const definition: ConvergenceDefinition = {
  id: 'release-review',
  definitionVersion: 1,
  data: {
    maxIterations: 2,
    maxReviewRestarts: 1,
    quorum: 2,
    requireDiversity: true,
    skippableSeats: [],
    seatConcurrency: 2,
    retryCapPerNode: 0,
  },
```

`quorum` is how many seats must accept, `requireDiversity` refuses two
seats from one family, and `maxIterations` ends the loop whatever the
seats say.

## LLM as judge

The seats in the loop are judges. What a judge may and may not decide is
on [Can an LLM judge replace a person?](/glossary/llm-as-judge).

## Next steps

* [Review loop](/reviewing/review-loop): the mechanics, the records and the failure codes.
* [Feedback loops](/concepts/feedback-loops): the umbrella, and the three shapes under it.