minor update

Author: changliu2

articles/ai-studio/how-to/develop/evaluate-sdk.md

@@ -217,7 +217,7 @@ For NLP evaluators, only a score is given in the `{metric_name}` key.
 
 Like 6 other AI-assisted evaluators, `GroundednessEvaluator` is a prompt-based evaluator that outputs a score on a 5-point scale (the higher the score, the more grounded the result is). On the other hand, `GroundednessProEvaluator` invokes our backend evaluation service powered by Azure AI Content Safety and outputs `True` if all content is grounded, or `False` if any ungrounded content is detected. 
 
-We open-source the prompts of our quality evaluators except for `GroundednessProEvaluator` (powered by Azure AI Content Safety) for transparency. These prompts serve as instructions for a language model to perform their evaluation task, which requires a human-friendly definition of the metric and its associated scoring rubrics (what the 5 levels of quality means for the metric). We highly recommend that users customize the definitions and grading rubrics to their scenario specifics. 
+We open-source the prompts of our quality evaluators except for `GroundednessProEvaluator` (powered by Azure AI Content Safety) for transparency. These prompts serve as instructions for a language model to perform their evaluation task, which requires a human-friendly definition of the metric and its associated scoring rubrics (what the 5 levels of quality means for the metric). We highly recommend that users customize the definitions and grading rubrics to their scenario specifics. See details in [Custom Evaluators](#custom-evaluators).
 
 For conversation mode, here is an example for `GroundednessEvaluator`: