add context to qs intros

Author: PatrickFarley

articles/ai-services/content-safety/quickstart-custom-categories.md

@@ -15,6 +15,8 @@ ms.author: pafarley
 
 Follow this guide to use Azure AI Content Safety Custom category REST API to create your own content categories for your use case and train Azure AI Content Safety to detect them in new text content.
 
+For more information on Custom categories, see the [Custom categories concept page](./concepts/custom-categories.md). For API input limits, see the [Input requirements](./overview.md#input-requirements) section of the Overview. 
+
 > [!IMPORTANT]
 > This feature is only available in certain Azure regions. See [Region availability](./overview.md#region-availability).
 

articles/ai-services/content-safety/quickstart-groundedness.md

@@ -15,6 +15,8 @@ ms.author: pafarley
 
 Follow this guide to use Azure AI Content Safety Groundedness detection to check whether the text responses of large language models (LLMs) are grounded in the source materials provided by the users.
 
+For more information on Groundedness detection, see the [Groundedness detection concept page](./concepts/groundedness.md). For API input limits, see the [Input requirements](./overview.md#input-requirements) section of the Overview. 
+
 ## Prerequisites
 
 * An Azure subscription - [Create one for free](https://azure.microsoft.com/free/cognitive-services/) 

articles/ai-services/content-safety/quickstart-image.md

@@ -17,6 +17,8 @@ zone_pivot_groups: programming-languages-content-safety
 
 Get started with the Content Studio, REST API, or client SDKs to do basic image moderation. The Azure AI Content Safety service provides you with AI algorithms for flagging objectionable content. Follow these steps to try it out.
 
+For more information on image moderation, see the [Harm categories concept page](./concepts/harm-categories.md). For API input limits, see the [Input requirements](./overview.md#input-requirements) section of the Overview. 
+
 > [!NOTE]
 > 
 > The sample data and code may contain offensive content. User discretion is advised.

articles/ai-services/content-safety/quickstart-jailbreak.md

@@ -15,6 +15,8 @@ ms.author: pafarley
 
 Follow this guide to use Azure AI Content Safety Prompt Shields to check your large language model (LLM) inputs for both User Prompt and Document attacks.
 
+For more information on Prompt Shields, see the [Prompt Shields concept page](./concepts/jailbreak-detection.md). For API input limits, see the [Input requirements](./overview.md#input-requirements) section of the Overview. 
+
 ## Prerequisites
 
 * An Azure subscription - [Create one for free](https://azure.microsoft.com/free/cognitive-services/) 

articles/ai-services/content-safety/quickstart-protected-material.md

@@ -15,6 +15,9 @@ ms.author: pafarley
 
 Protected material text describes language that matches known text content (for example, song lyrics, articles, recipes, selected web content). This feature can be used to identify and block known text content from being displayed in language model output (English content only). For more information, see [Protected material concepts](./concepts/protected-material.md).
 
+For more information on protected material detection, see the [Protected material detection concept page](./concepts/protected-material.md). For API input limits, see the [Input requirements](./overview.md#input-requirements) section of the Overview. 
+
+
 ## Prerequisites
 
 * An Azure subscription - [Create one for free](https://azure.microsoft.com/free/cognitive-services/) 

articles/ai-services/content-safety/quickstart-text.md

@@ -17,6 +17,9 @@ zone_pivot_groups: programming-languages-content-safety
 
 Get started with the Content Safety Studio, REST API, or client SDKs to do basic text moderation. The Azure AI Content Safety service provides you with AI algorithms for flagging objectionable content. Follow these steps to try it out.
 
+For more information on text moderation, see the [Harm categories concept page](./concepts/harm-categories.md). For API input limits, see the [Input requirements](./overview.md#input-requirements) section of the Overview. 
+
+
 > [!NOTE]
 > 
 > The sample data and code may contain offensive content. User discretion is advised.