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

# Outputs

> Constructor options and outputs for evaluators using the Python SDK.

Once you've configured your evaluator, you can start evaluating text inputs for a grade level:

```python example.py theme={null}
from learning_commons_evaluators import (
    ConventionalityEvaluator,
    ConventionalityEvaluationInput,
    GooglePromptProviderConfig,
    create_config,
)

# Create evaluator config
# NOTE: Telemetry is not yet implemented in v0.1.0
config = create_config(
    google_llm_provider_config=GooglePromptProviderConfig(api_key="your-google-key"),
    telemetry_partner_id="your-learning-commons-api-key",
)

# Instantiate evaluator
evaluator = ConventionalityEvaluator(config)

# Evaluate text for a grade level
result = evaluator.evaluate(
    ConventionalityEvaluationInput(text="The cat's out of the bag now.", grade=5)
)
```

## Literacy evaluators

The literacy evaluators have the following output fields.

| Field         | Type                                                                                                                                                       | Description                                                                                                |
| :------------ | :--------------------------------------------------------------------------------------------------------------------------------------------------------- | :--------------------------------------------------------------------------------------------------------- |
| `answer`      | [`EvaluationAnswer`](https://github.com/learning-commons-org/evaluators/blob/main/sdks/python/src/learning_commons_evaluators/schemas/evaluator.py) ↗      | Complexity score returned by the evaluation                                                                |
| `explanation` | [`EvaluationExplanation`](https://github.com/learning-commons-org/evaluators/blob/main/sdks/python/src/learning_commons_evaluators/schemas/evaluator.py) ↗ | Reasoning for the complexity score and evaluator-specific fields (`explanation.details` – see table below) |
| `metadata`    | [`EvaluationMetadata`](https://github.com/learning-commons-org/evaluators/blob/main/sdks/python/src/learning_commons_evaluators/schemas/metadata.py) ↗     | Evaluation run metadata like timing, status, token usage, and per-step details                             |

The `explanation.details` field includes detailed internal analysis data specific to that evaluator.

| Evaluator                                                          | `explanation.details` description                                       | `explanation.details` type                                                                                                                                     |
| :----------------------------------------------------------------- | :---------------------------------------------------------------------- | :------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| [Vocabulary](/evaluators/literacy-evaluators/vocabulary)           | [Output fields](/evaluators/literacy-evaluators/vocabulary#output)      | [`VocabularyComplexityOutput`](https://github.com/learning-commons-org/evaluators/blob/main/sdks/python/src/learning_commons_evaluators/schemas/vocabulary.py) |
| [Conventionality](/evaluators/literacy-evaluators/conventionality) | [Output fields](/evaluators/literacy-evaluators/conventionality#output) | [`ConventionalityOutput`](https://github.com/learning-commons-org/evaluators/blob/main/sdks/python/src/learning_commons_evaluators/schemas/conventionality.py) |