UiPath UiPath-AAAv1 試験概要:

UiPath UiPath-AAAv1 試験シラバストピック:

UiPath Certified Professional Agentic Automation Associate (UiAAA) 認定 UiPath-AAAv1 試験問題：

問題 #1
A company is integrating an Agent into its customer support workflow to detect sentiment and classify complaints (e.g., "Billing issue", "Product defect"). However, the Agent's responses often miss subtle emotional cues like frustration or urgency. What change to the prompt design would most improve the quality of sentiment detection?

A. Include explicit context explaining the goal of sentiment analysis and define constraints for identifying urgency.
B. Remove detailed task instructions to give the Agent more freedom in interpreting customer messages.
C. Focus only on complaint categorization and rely on post-processing to handle emotional nuance.
D. Provide vague constraints in an emotional tone.

問題 #2
Which of the following best describes a challenge faced by traditional automation in complex business processes?

A. Limited ability to automate unstructured tasks that require judgment and contextual awareness
B. Over-reliance on AI-powered agents for all types of automation tasks
C. Inability to perform repetitive, structured tasks efficiently and reliably
D. Excessive flexibility in handling varied workflows across different systems like CRM and ERP

問題 #3
Four draft system prompts are shown for an invoice-approval agent. Based on UiPath guidance for context, instruments, and output format constraints, which draft is the most robust choice?

A. You are an invoice-approval agent who deals only with supplier invoices and rejects any other request.
Extract invoice_ID from the email text.
When an invoice_ID is found, run the LookupInvoice tool to retrieve invoice amount and supplier name.
If the total # $10,000, escalate the case to Finance in Action Center, sending invoice_ID, amount, and supplier.
If the total > $10,000, approve the invoice.
Return a reply wrapped inside invoice_status: tags: use <approved> or <awaiting_review> as appropriate.
Follow a concise, professional tone and refuse tasks outside invoice approval.
B. You are an invoice-approval agent who deals only with supplier invoices and rejects any other request.
Extract {{invoice_ID}} from the email text.
When an {{invoice_ID}} is found, run the LookupInvoice tool to retrieve invoice amount and supplier name.
If the total # $10,000, escalate the case to Finance in Action Center, sending {{invoice_ID}}, amount, and supplier.
If the total > $10,000, approve the invoice.
Return a reply wrapped inside invoice_status: tags: use <approved> or <awaiting_review> as appropriate.
Follow a concise, professional tone and refuse tasks outside invoice approval.
C. You are an invoice approver. After processing, output exactly the following JSON template:
{ "id": "ABC-123", "status": "approved", "amount": 9999.9 }
Extract {{invoice_ID}} from the email text.
When an {{invoice_ID}} is found, run the LookupInvoice tool to retrieve invoice amount and supplier name.
If the total # $10,000, escalate the case to Finance in Action Center, sending {{invoice_ID}}, amount, and supplier.
If the total > $10,000, approve the invoice.
Populate the fields above with real data.
D. You are an invoice approver. After processing, output exactly the following JSON template:
{ "id": "ABC-123", "status": "approved", "amount": 9999.9 }
Extract the {{invoice_ID}} from the email text.
Use LookupInvoice to get the invoice amount and supplier name.
Escalate to Finance if amount # $10,000.
If amount > $10,000, approve the invoice.
Populate the fields above with real data.

問題 #4
For what primary reason should you supply a description for every input and output argument in an agent?

A. Clear descriptions help the agent understand how to use each argument effectively while generating or returning results.
B. Argument descriptions are required only for input arguments; output arguments are inherently self- explanatory and do not benefit from them.
C. Adding descriptions forces Studio Web to treat all arguments as mandatory fields that block deployment if left empty.
D. Descriptions cause Orchestrator triggers to pre-populate the arguments automatically, eliminating manual mapping.

問題 #5
What are the primary benefits of Context Grounding when querying data across multiple documents?

A. Context Grounding only extracts random sentences without contextual understanding.
B. Context Grounding requires manual intervention for identifying connections between data points across documents.
C. Context Grounding understands relationships between data points across documents, enabling tasks like summarization, data comparison, and retrieval of highly relevant information.
D. Context Grounding is limited to querying within a single document at a time.

解説：