docs:punctuation-V2

blog/tags.yml

@@ -2,3 +2,7 @@ release:
   description: 'Blog posts about new Industrial Experience design system releases'
 merging:
   description: 'Merging activities from other design systems at Siemens'
+ux:
+  description: 'Posts about user experience and UX writing topics'
+development:
+  description: 'Posts about implementation, tooling and development workflows'

docs/components/input-date-time/code.mdx

@@ -1,6 +1,7 @@
 ---
 doc-type: 'tab-item'
 formReady: true
+description: 'Code examples for date time input, including states, validation, slots and min/max dates.'
 ---
 import DatetimeInputPlayground from '@site/docs/autogenerated/playground/datetime-input.mdx';
 import DatetimeInputDisabledPlayground from '@site/docs/autogenerated/playground/datetime-input-disabled.mdx';

docs/guidelines/conversational-design/designing-conversations/ad-hoc-conversations.md

@@ -6,7 +6,7 @@ hide_table_of_contents: false
 doc-type: 'banner'
 component-tabs: ['']
 no_single_tab: true
-description: "Even in industrial scenarios, users test and play with chatbots. Some ad hoc interactions can be fun and build relationships between your users and chatbots, however some can be undesirable and damaging for your brand. To mitigate this risk, it’s important to implement filters and set up clear guidelines. Companies and projects can decide if they need to implement more than a basic response and give, for example, a warning message. Either way, most chatbots respond in the same way when it comes to offensive or inappropriate user queries."
+description: "Ad hoc chatbot interactions can strengthen user trust, but offensive or off-topic input can harm your brand. Use filters and response rules to keep interactions safe and on track."
 ---
 
 #

docs/guidelines/conversational-design/designing-conversations/ending-conversations.md

@@ -6,7 +6,7 @@ hide_table_of_contents: false
 doc-type: 'banner'
 component-tabs: ['']
 no_single_tab: true
-description: "As with any human to human interaction, there’s always an ending to give participants closure and end on a positive note. This is the same for every chatbot interaction, including industrial chatbots. Although it seems an easy communicative function, ending interactions well can achieve multiple goals that help users, chatbot teams and chatbots. It’s an opportunity to get useful feedback to train your chatbot, create a clear signal that the interaction is complete, and set the tone for the next interaction interactions."
+description: "End chatbot interactions with clear closure and a positive tone. Well-designed endings confirm completion, support feedback collection and improve future interactions."
 ---
 
 # 

docs/guidelines/conversational-design/designing-conversations/handling-errors.md

@@ -6,7 +6,7 @@ hide_table_of_contents: false
 doc-type: 'banner'
 component-tabs: ['']
 no_single_tab: true
-description: "When talking about chatbots and the mistakes they make, it’s always talked about handling them ‘gracefully’. However, in industrial situations, they must also be handled quickly so users can move on and possibly get another support source. There are often time-sensitive actions within industrial situations that require chatbots and workers to move quickly to find solutions. If a chatbot response is inaccurate or the chatbot cannot give users the solution they need, it can be consequential and even costly."
+description: "In industrial contexts, chatbot errors must be handled clearly and quickly. Give users immediate feedback, explain limits and guide them to an alternative path."
 ---
 
 #