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# notScorable()

Declares that the current run has nothing for this scorer to evaluate. Return it from a scorer function step, typically `preprocess`. Remaining steps are skipped, so the judge is never called and averages, gates, and thresholds only include runs this scorer actually evaluated.

Use `notScorable()` when whether a run qualifies depends on the run's own input or output, such as whether a specific tool was called. Use an [eligibility filter](https://mastra.ai/docs/evals/overview) instead when the condition can be expressed from request context or entity metadata. See [Custom scorers: skipping runs](https://mastra.ai/docs/evals/custom-scorers) for a walkthrough.

## Usage example

The following scorer judges refund handling with an LLM. Runs that never called `refundCustomer` are declared not scorable before the judge is asked anything:

```typescript
import { createScorer, notScorable } from '@mastra/core/evals'
import { extractToolCalls } from '@mastra/evals/scorers/utils'

export const refundJudge = createScorer({
  id: 'refund-judge',
  description: 'Judges how well refund requests were handled',
  type: 'agent',
  judge: {
    model: 'openai/gpt-5-mini',
    instructions: 'You are a strict QA reviewer for customer-support refund handling.',
  },
})
  .preprocess(({ run }) => {
    const { tools } = extractToolCalls(run.output)
    return tools.includes('refundCustomer')
      ? { tools }
      : notScorable('refundCustomer was not called')
  })
  .generateScore({
    description: 'Score the refund handling from 0 to 1',
    createPrompt: ({ run }) =>
      `Rate this refund handling from 0 to 1:\n${JSON.stringify(run.output)}`,
  })
```

## Parameters

**reason** (`string`): Why the run is not scorable. Surfaced on the run result and experiment results.

**Returns:** `NotScorable`. An opaque value recognized by the scorer pipeline. Return it directly from the step. Don't wrap it in another object.

## Behavior

- Accepted from any function step: `preprocess`, `analyze`, `generateScore`, or `generateReason`. Prompt-object steps can't return it because their output is produced by the model.
- Steps that already completed keep their results.
- `scorer.run()` resolves with `notScorable: { step, reason? }` and no `score` key. See [`MastraScorer`](https://mastra.ai/reference/evals/mastra-scorer).
- Live scoring stores no score row. [`runEvals()`](https://mastra.ai/reference/evals/run-evals) leaves the run out of averages, gates, thresholds, and the verdict, and counts it in `summary.notScorable`. Experiments set `score: null`, `error: null`, and `notScorable`.

## Related

- [`createScorer()`](https://mastra.ai/reference/evals/create-scorer)
- [`filterRun()`](https://mastra.ai/reference/evals/filter-run) trims what a scorer sees. It still produces a score.
- [Custom scorers: skipping runs](https://mastra.ai/docs/evals/custom-scorers)