# Concepts
Scorable is built on a few core concepts that help you organize your evaluation strategy.
**Objective** defines *what* you want to achieve (e.g., "Ensure the bot is polite").
[**Evaluator**](https://docs.scorable.ai/usage/usage/evaluators) is a specific check that scores a piece of text (0-1) based on that objective. Think of it as a **unit test for semantics**.
[**Judge**](https://docs.scorable.ai/usage/usage/judges) is a collection of evaluators bundled together for a specific use case. It represents your **definition of quality** for a specific task.
[**Model**](https://docs.scorable.ai/usage/usage/models) is the AI model such as an LLM that provides the semantic processing of the inputs. Notably, the list contains both API-based models such as OpenAI and Anthropic models, and open source models such as Llama and Mistral models. Finally, you can add your own locally running models to the list [with ease](/concepts-and-examples/cookbooks/connect-a-model.md). The organization Admin controls the availability of models enabled in your organization.
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# Agent Instructions: Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.
Perform an HTTP GET request on the current page URL with the `ask` query parameter:
```
GET https://docs.scorable.ai/overview/concepts.md?ask=
```
The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.
Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.