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| Section | Weight | Objectives |
|---|---|---|
| Context Grounding and Escalations | 16% | - Retrieval strategies and ingestion management - Grounding source configuration and indexing - Human-in-the-loop escalation architecture - Context engineering best practices - Action Apps and escalation SLA/routing design |
| Agentic Discovery and Blueprint Design | 16% | - Agent story design and goal definition - Tool selection and evaluation criteria definition - Process assessment and agent opportunity identification - Prompt engineering and context specification |
| Advanced Agent Implementation and Platform Integration | 18% | - Coded Agents and conversational agents development - Studio Web tools and Integration Service configuration - Autopilot and AI-assisted development workflows - UI Agent and ScreenPlay implementation |
| Agentic Evaluations and Agent Management | 16% | - Evaluation dataset design and edge-case handling - Deterministic vs model-graded evaluation - Incident analysis and iterative improvement - Assertions, scoring, and trace analysis - Agent lifecycle management and deployment |
| Orchestration and Multi-Agent Processes | 17% | - API integration and external system connectivity - Human tasks, callbacks, and event handling - Multi-agent coordination and workflow control - UiPath Maestro process modeling and BPMN |
| Governance, Observability, and Reliability | 17% | - Compliance, security, and responsible AI - Guardrails, fallback logic, and risk controls - Monitoring, observability, and Agent Scores - Governance policies and AI Trust Layer |
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NEW QUESTION # 36
Once a coded MCP server is registered in UiPath's MCP Servers panel, what triggers the discovery of its tools?
Answer: C
Explanation:
Option B most accurately describes the tool discovery mechanism used for coded MCP servers in UiPath Orchestrator.
Model Context Protocol (MCP) provides a standardized mechanism for exposing external tools and capabilities to AI agents. UiPath Orchestrator supports managing MCP servers and discovering the tools they make available.
For coded MCP servers, discovery is initiated through the Discover action within the MCP server's Jobs tab.
When the administrator selects Discover, Orchestrator starts a job associated with that MCP server. The job executes the required discovery procedure and obtains the tools exposed by the server.
Administrators can monitor execution progress through the Jobs tab. After the discovery job finishes, the Tools tab refreshes to display the discovered capabilities.
This distinction is important because selecting Discover does not immediately guarantee that the tools are available. Successful completion of the associated job is required.
Option A is incomplete because it suggests an immediate manual refresh rather than the documented job- based discovery procedure. Options C and D describe automatic polling or heartbeat mechanisms that are not the specified discovery trigger.
The discovered tools can subsequently be exposed to supported AI agents according to the applicable platform permissions and configuration.
Official UiPath references/topics: Orchestrator - Managing MCP Servers - Discovering Tools and Jobs.
Technical qualification: Tool discovery qualification: Discover initiates a job; tools appear after the job completes.
NEW QUESTION # 37
Which of the following accurately describes the recommended workflow mapping exercise to complete before building an agent?
Answer: C
Explanation:
Option B most closely represents UiPath's recommended workflow mapping exercise before agent development.
UiPath emphasizes that effective agents should be embedded within existing business processes rather than designed as unrestricted replacements for complete workflows.
The first responsibility during workflow mapping is identifying the process's decision points and input/output formats. These characteristics establish where business information enters the process, what decisions must be made, and which results downstream components require.
The next activity is identifying processes with clear business objectives but variable or ambiguous inputs.
Ticket classification, compliance assessment, and document interpretation are suitable examples when decisions require contextual reasoning.
Predictable, rules-based execution steps should generally remain in conventional RPA workflows or deterministic orchestration components. Agents should be introduced where contextual interpretation, judgment, or adaptive planning adds value.
Finally, the design should preserve the surrounding workflow architecture. The agent operates as a specialized decision-making component, while conventional automation handles repeatable execution and process control.
Options A, C, and D introduce activities such as user training, interface design, and deployment planning.
Although these can be necessary elsewhere in the project lifecycle, they are not the core workflow mapping activities specified by UiPath.
Official UiPath references/topics: Agents - Best Practices for Building Agents - Design Agents for Real Workflows.
Technical qualification: Wording qualification: UiPath emphasizes processes with variable or ambiguous inputs; the term "predictable flows" is imprecise.
NEW QUESTION # 38
In an agent run's trace view, what information does hovering over a node typically reveal?
Answer: B
Explanation:
Option D accurately describes the information presented when inspecting nodes in UiPath Agent execution traces.
UiPath provides visual execution traces that record the activities performed during an agent run, including model calls, tool invocations, intermediate operations, and final outputs.
Each node represents a particular execution step. The visualization allows developers and administrators to investigate how the agent processed inputs and reached its final result.
Hovering over a trace node displays a concise preview containing its execution status, start and end timestamps, and input/output snippets.
The status helps identify whether an operation succeeded, failed, or was retried. Timestamps support performance analysis by identifying execution delays and unusually slow operations.
Input/output previews help developers determine whether the agent supplied appropriate tool arguments and received the expected responses.
For more detailed investigation, selecting a node exposes additional information, including complete JSON payloads, logs, errors, and runtime metrics where supported.
Option A describes agent configuration rather than execution metadata. Option B incorrectly focuses on feedback scoring. Option C lists information that is not the standard node-hover summary.
Trace analysis is essential for troubleshooting agent behavior, verifying tool interactions, investigating execution failures, and supporting audit requirements.
Official UiPath references/topics: Agents - Agent Traces - Trace Visualization and Inspecting Trace Nodes.
NEW QUESTION # 39
How do execution traces help identify the root cause of failed evaluations?
Answer: D
Explanation:
Option A describes the principal diagnostic value of execution traces in UiPath Agents.
An evaluation score identifies whether the agent satisfied the expected assessment criteria, but it does not necessarily explain why a particular execution succeeded or failed.
Execution traces provide a chronological record of agent behavior, including intermediate decisions, model interactions, tool calls, input arguments, returned outputs, execution timestamps, and associated errors.
This information allows developers to investigate the sequence of events leading to an incorrect response.
For example, an invoice validation agent may fail an evaluation because it selected an inappropriate tool, supplied an invalid invoice identifier, or misinterpreted a correctly returned payment status.
The final evaluation result may indicate failure without identifying which of these conditions occurred.
By inspecting the trace, the developer can distinguish prompt interpretation errors from incorrect tool invocation, unexpected external responses, or downstream processing defects.
Option B describes evaluation summaries rather than execution diagnostics. Option C introduces automatic evaluator modification, which is not the function of tracing. Option D concerns evaluation-set management rather than root-cause analysis.
UiPath provides both agent-run traces and evaluation-run traces, supporting development troubleshooting, production monitoring, performance analysis, and auditing.
Official UiPath references/topics: Agents - Agent Traces.
NEW QUESTION # 40
Before publishing an agent to Orchestrator, which combination of checks ensures the agent meets enterprise readiness standards?
Answer: C
Explanation:
Option B most closely matches UiPath's documented validation benchmarks for publishing and deploying agents to Orchestrator.
UiPath recommends completing at least 30 interactive tests covering normal scenarios, boundary conditions, malformed inputs, and other representative variations.
These tests allow developers to inspect agent behavior directly and identify problems involving prompts, tool selection, contextual information, and execution outcomes.
In addition, UiPath recommends creating at least 30 curated evaluation cases and achieving an evaluation score of 70% or higher without regressions.
Evaluation results should remain consistent when prompts, tools, or model configurations change.
Option A introduces an unsupported minimum of 50 interactive tests. Option C incorrectly postpones smoke testing and treats optional guardrail logging as the primary readiness control. Option D incorrectly suggests that high evaluation accuracy eliminates the need for interactive testing.
However, the checks in B are not sufficient by themselves to guarantee enterprise readiness.
UiPath also recommends finalizing prompts, validating tool schemas, configuring necessary guardrails, confirming context sources, verifying credentials and access permissions, and testing downstream integrations.
For high-risk operations, the organization should establish stricter acceptance criteria appropriate to the business consequences of failure.
Official UiPath references/topics: Agents - Best Practices for Publishing and Deploying Agents.
Technical qualification: B omits the separate recommendation for 30 curated evaluations and absence of regressions.
NEW QUESTION # 41
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