Add documentation on providing a description when pausing a flow run

docs/guides/creating-interactive-workflows.md

@@ -135,6 +135,50 @@ async def greet_user():
 
 When a user sees the form for this input, the name field will contain "anonymous" as the default.
 
+### Providing a description with runtime data
+
+You can provide a dynamic, markdown description that will appear in the Prefect UI when the flow run pauses. This feature enables context-specific prompts, enhancing clarity and user interaction. Building on the example above:
+
+```python
+from datetime import datetime
+from prefect import flow, pause_flow_run, get_run_logger
+from prefect.input import RunInput
+
+
+class UserInput(RunInput):
+    name: str
+    age: int
+
+
+@flow
+async def greet_user():
+    logger = get_run_logger()
+    current_date = datetime.now().strftime("%B %d, %Y")
+
+    description_md = f"""
+**Welcome to the User Greeting Flow!**
+Today's Date: {current_date}
+
+Please enter your details below:
+- **Name**: What should we call you?
+- **Age**: Just a number, nothing more.
+"""
+
+    user_input = await pause_flow_run(
+        wait_for_input=UserInput.with_initial_data(
+            description=description_md, name="anonymous"
+        )
+    )
+
+    if user_input.name == "anonymous":
+        logger.info("Hello, stranger!")
+    else:
+        logger.info(f"Hello, {user_input.name}!")
+```
+
+When a user sees the form for this input, the given markdown will appear above the input fields.
+
+
 ### Handling custom validation
 
 Prefect uses the fields and type hints on your `RunInput` or `BaseModel` class to validate the general structure of input your flow receives, but you might require more complex validation. If you do, you can use Pydantic [validators](https://docs.pydantic.dev/1.10/usage/validators/).