About the Exam

This exam validates foundational skills for collaborating with AI agents in process automation and is aimed at technical and non-technical roles such as citizen developers, business analysts, automation developers, and solution architects. It covers agentic AI concepts, discovery, blueprint design, context grounding, escalations, evaluations, prompt engineering, UiPath platform integrations, Maestro orchestration, and Autopilot for Everyone, and passing earns the UiPath Certified Professional Agentic Automation Associate credential.

Exam Topics

  • Requirements Gathering0%
  • Process Discovery0%
  • Process Analysis0%
  • Solution Design0%
  • UiPath Platform and Automation Components0%

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Last updated December 5, 2025 at 7:40 AM

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QuestionQ1

UiPath Platform and Automation Components

What is the main role of guardrails in tools?

  • A Guardrails are designed to apply only after tool execution, without influencing pre-execution conditions.
  • B Guardrails are used exclusively to automate all tool corrections without the possibility of triggering human intervention.
  • C Guardrails control unexpected behaviors within tool calls deterministically, allowing developers to configure conditions for human intervention and escalations.
  • D Guardrails only validate tool inputs during development and do not address unpredictable behaviors at runtime.
Explanation

Tool guardrails provide deterministic checks around custom function-tool calls, including validation or blocking before execution and handling results after execution. Tool calls can also be configured to require human approval, enabling intervention and escalation when needed.

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QuestionQ2

UiPath Platform and Automation Components

What is the role of Input Properties in an Action app’s schema when configuring it?

  • A They hold agent-context-derived values that are presented to the user and cannot be modified during review.
  • B Input Properties allow the user to design controls for dynamic data visualization across app outcomes.
  • C Input properties ensure schema validation for custom templates within FormWrapper.
  • D They provide additional values for agents to modify and return during review.
Explanation

Input properties are values derived from the agent context and presented to the user for a particular agent run. They cannot be changed during review; Input/Output properties are used when the reviewer must modify values, and Output properties hold additional values entered by the user and returned to the agent.

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QuestionQ3

Solution Design

According to naming best practices, which of the following is the most suitable name for a tool that creates summaries of PDF files?

  • A pdfSummary
  • B summarize.pdf@tool
  • C file_processor
  • D pdf_summary
Explanation

A clear, descriptive lowercase snake_case name makes a tool’s purpose easy to identify and follows a common function-naming convention. pdf_summary specifically conveys that the tool produces a PDF summary; file_processor is overly broad. Official Gemini function-calling documentation permits underscores or camelCase for function names, and its examples commonly use descriptive underscore-separated names.

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QuestionQ4

UiPath Platform and Automation Components

What is the main purpose of the ‘Start and wait for agent’ feature in UiPath Service Tasks?

  • A To initiate and wait for an external agent to complete its task before continuing the process.
  • B To execute a subprocess within the same project without waiting for completion.
  • C To trigger a timer event and pause the process until the timer expires.
  • D To initiate and wait for an agent to complete its task before continuing the process.
Explanation

The feature starts a UiPath agent and waits for that agent to finish execution before the process proceeds. UiPath documents external agents as a separate action, “Start and wait for external agent.”

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QuestionQ5

Solution Design

What is one key characteristic of zero-shot prompting?

  • A This is necessary for complex or nuanced scenarios.
  • B It ensures the model has been fine-tuned for all tasks it encounters.
  • C It requires at least one example in the prompt for efficient completion.
  • D The model performs tasks without prior examples or training specific to the request.
Explanation

Zero-shot prompting relies on a model’s existing pretrained capabilities to perform a requested task without task-specific examples or prior training for that particular request.

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