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

# Context Precision

> Accesses if relevant nodes in the retrieved context are prioritized over irrelevant ones for a specific input.

> This evaluator uses weighted cumulative precision (WCP) which prioritizes the relevance of top-ranked context nodes and rewards correct ordering. This approach is critical because LLMs tend to focus more on earlier context nodes, and incorrect ranking can lead to hallucinations.

## Input

* **Required Inputs:**
  * **`input`**: The original user query
  * **`context`**:  List of context chunks retrieved for the response
  * **`expected_output`**: The expected response that should be generated

## Output

* **`Result`**: Value in the continuous range \[0, 1]
* **`Reasoning`**: Detailed explanation of precision assessment

## Interpretation

* **Higher score (closer to 1)**: Better precision - relevant context nodes are prioritized at the top of the retrieved context, and most statements in the expected output are justified by these nodes
* **Lower score (closer to 0)**: Poor precision - relevant context nodes are ranked lower than irrelevant ones, or few statements in the expected output are justified by the retrieved context

<Note>Higher scores indicate better precision, meaning the retrieved context contains more relevant information and less irrelevant content for generating the expected output.</Note>