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[General] UiPath-AAAv1 Real Exam - UiPath-AAAv1 Torrent Vce & UiPath-AAAv1 Valid Quest

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【General】 UiPath-AAAv1 Real Exam - UiPath-AAAv1 Torrent Vce & UiPath-AAAv1 Valid Quest

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UiPath Certified Professional Agentic Automation Associate (UiAAA) Sample Questions (Q11-Q16):NEW QUESTION # 11
What type of agents can be invoked using the 'Start and wait for external agent' feature in UiPath Maestro?
  • A. Agents that do not require any input or output variables.
  • B. External agents like Salesforce or ServiceNow.
  • C. Only UiPath Orchestrator robots.
  • D. Agents configured exclusively within the same project.
Answer: D
Explanation:
Cis the correct answer - the"Start and wait for external agent"feature in UiPath Maestro is used toinvoke another agentthat has been configured within thesame project or automation environment.
This enables:
* Agent-to-agent chaining
* Modular designwhere complex tasks are offloaded to specialized agents
* Return of results or outputs, once the external agent completes its task Agents must be:
* Properly configured
* Input/output ready
* Available within the orchestration context of the same solution
Option A is incorrect - this feature is about agents, not robots.
B is wrong - external platforms like Salesforce are accessed via connectors,not as agents.
D is false - input/output parameters can and often should be used between agents.

NEW QUESTION # 12
In a UiPath Agent, which statement best captures the essential purpose of a system prompt?
  • A. It declares the agent's role, overall goal, and operating constraints, and tells the agent when to invoke tools or escalate tasks to a human reviewer.
  • B. It is used only to preload enterprise context and never influences the agent's decision to call tools.
  • C. It mainly lists output-formatting tags the agent must include, leaving role and goal definition to the user prompt.
  • D. It must enumerate every possible dialogue path the agent could encounter so the model can simply pick a preset answer.
Answer: A
Explanation:
Ais correct - in UiPath's agent framework, asystem promptserves as the agent'score grounding mechanism. It is responsible for:
* Defining the agent's identity("You are an IT support assistant...")
* Outlining its goal("Your job is to classify, triage, and resolve tickets...")
* Setting operational boundaries and behaviors
* Specifying when to escalate to a humanor use tools
This aligns with UiPath'sContext Grounding strategy, which separatessystem prompts,user prompts, and tools orchestration. The system prompt providespersistent context, guiding the LLM's behavior consistently across user interactions and actions.
Option B downplays its influence - which is critical.
C reduces it to output formatting, which is only a small part.
D is unrealistic - LLMs generalize; they don't require enumerating every path.
Correct system prompting ensuressafe, consistent, goal-aligned behaviorfrom the agent across dynamic scenarios.

NEW QUESTION # 13
Which of the following best describes how agents handle dynamic environments?
  • A. Agents adapt to changing conditions by learning.
  • B. Agents rely solely on static rules without contextual learning.
  • C. Agents fail to execute tasks when information or processes change.
  • D. Agents require complete human assistance whenever processes change.
Answer: A
Explanation:
Bis correct - one of the defining strengths ofUiPath's agentic automationis the ability for agents toadapt to dynamic environmentsusingLLMs and contextual grounding.
Agents differ from traditional RPA bots in that they:
* Interpret natural language
* Reason across structured and unstructured data
* Adjust outputs based onreal-time context, grounding, and updated knowledge When processes change - such as updates to escalation rules, variations in incoming requests, or new product names - agents can adjust without reprogramming, thanks to:
* Flexible prompts
* Grounded context from indexes or memory
* Few-shot or zero-shot inference capabilities
This adaptability makes agents ideal for scenarios likeemail triage,customer service, orknowledge work, where inputs and conditions vary.
Option A and D falsely suggest agents are rigid or fully dependent on human intervention.
Option C applies to classic RPA bots - not LLM-powered agents.
While agents don't"learn"in the ML retraining sense during execution, theydynamically interpret and adapt within the context of each session - a key feature enabled by UiPath's Autopilot™, Context Grounding, and agent memory frameworks.
This flexibility is foundational to deploying agents in environments whererules evolve, data flows shift, or human-like understanding is needed.

NEW QUESTION # 14
How does adjusting the "Number of results" setting affect the agent's use of context from indexes?
  • A. It changes the number of chunks returned, impacting both the size of the grounding payload and the filtering of relevant information.
  • B. It makes the agent ignore all context completely, resulting in outputs that are entirely disconnected from the indexed data, regardless of its relevance to the query or prompt provided.
  • C. It selects which Orchestrator folder to use, determining the location of stored workflows and deciding which set of predefined rules will apply during data retrieval and processing.
  • D. It modifies the similarity threshold for chunk retrieval and lowers the number of tokens used.
Answer: A
Explanation:
The correct answer isC. In UiPath'sContext Groundingconfiguration, the"Number of results"setting directly affects how manychunks of indexed knowledgeare retrieved and passed to the LLM at runtime.
These chunks come from preprocessed documents and are used to build thegrounding payload- the content added to the agent's prompt for context-aware generation.
By increasing the number of results:
* The LLM has access tomore context, which can improve response quality if the added information is relevant.
* However, it alsoincreases the token load, which can reduce prompt space or introduce irrelevant noise if poorly tuned.
Reducing the number of results leads tomore focused prompts, with only top-ranked relevant chunks (based oncosine similarity) included. This is crucial when using large indexes or when LLM context windows are limited.
Option A confuses this setting with similarity threshold tuning, which is a separate parameter.
Option B is false - the agent doesnot ignore contextunless context grounding is disabled.
Option D misrepresents the function - Orchestrator folder selection is unrelated to this retrieval setting.
In summary, the "Number of results" setting allows fine-tuning ofhow much supporting context is retrieved and passed to the model. It is a key control in optimizing performance, precision, and relevance of grounded agent responses.

NEW QUESTION # 15
You want your agent to call an existing UiPath process by adding it in the Tools # Processes. Which prerequisite must be met before the process becomes selectable?
  • A. The process only appears if it exposes at least one String input argument, regardless of where it is deployed, otherwise the Agent tool would be irrelevant for the Agent.
  • B. The process must already be published and deployed to a shared Orchestrator folder that you (and the agent) have permission to access.
  • C. Any process published anywhere in the tenant automatically appears in the list without additional deployment or permissions.
  • D. The process only appears if it exposes at least one String output argument, regardless of where it is deployed, otherwise the Agent tool would be irrelevant for the Agent.
Answer: B
Explanation:
Bis the correct answer - in UiPath'sAgent Builder (Studio Web), when you want to invoke an existing UiPath process from an agent (viaTools # Processes), that process must meettwo key prerequisites:
* It must be published and deployed to a shared Orchestrator folder
* You - and the agent - must have access to that folder
This ensures that:
* The agent canlocate and run the processat execution time
* Role-based access control (RBAC) is respected
* Input/output arguments, execution logs, and exceptions are properly managed within the correct environment This aligns with UiPath'sOrchestrator-integrated agent orchestration model, where security and deployment visibility are tightly governed. It also allows agent authors toreuse existing RPA logicinside dynamic agent flows without duplicating automation work.
Option A and D incorrectly imply that argument types affect process visibility - that's false. Agents can invoke processes withany argument signature, as long as mapping is defined.
Option C is incorrect - publishing alone is not enough.Deployment and permissionsare required for the process to appear in the tool selector.
This model ensures that agents can call any compliant UiPath processsecurely, reliably, and in line with enterprise governance.

NEW QUESTION # 16
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