[MLOB-4557] Update the External Evaluations doc

content/en/llm_observability/evaluations/external_evaluations.md

@@ -19,7 +19,13 @@
 ## Overview
 
 In the context of LLM applications, it's important to track user feedback and evaluate the quality of your LLM application's responses.
-While LLM Observability provides a few out-of-the-box evaluations for your traces, you can submit your own evaluations to LLM Observability in two ways: with Datadog's [SDK](#submitting-evaluations-with-the-sdk), or with the [LLM Observability API](#submitting-evaluations-with-the-api). See [Naming custom metrics][1] for guidelines on how to choose an appropriate label for your evaluations.
+While LLM Observability provides a few out-of-the-box evaluations for your traces, you can submit your own evaluations to LLM Observability in two ways: with Datadog's [SDK](#submitting-evaluations-with-the-sdk), or with the [LLM Observability API](#submitting-evaluations-with-the-api). Use this naming convention for the evaluation label:
+
+* Evaluation labels must start with a letter.
+* Evaluation labels must only contain ASCII alphanumerics or underscores.
+  * Other characters, including spaces, are converted to underscores.
+  * Unicode is not supported.
+* Evaluation labels must not exceed 200 characters. Fewer than 100 is preferred from a UI perspective.
 
 <div class="alert alert-info">Evaluation labels must be unique for a given LLM application (<code>ml_app</code>) and organization.</div>