Certified Agentforce Specialist Exam Questions and Answers (Page: 5)

QUESTION: 33

Universal Containers recently added a custom flow for processing returns and created a new Agent Action.
Which action should the company take to ensure the Agentforce Service Agent can run this new flow as part of the new Agent Action?

Recreate the flow using the Agentforce agent user.
Assign the Manage Users permission to the Agentforce Agent user.
Assign the Run Flows permission to the Agentforce Agent user.

Answer(s): C

Explanation:

UC has created a custom flow for processing returns and linked it to a new Agent Action for the Agentforce Service Agent, an AI-driven agent for customer service tasks. The agent must have the ability to execute this flow. Let's assess the options.

Option A: Recreate the flow using the Agentforce agent user.

Flows are authored by admins or developers, not "recreated" by specific users like the Agentforce agent user (a system user for agent operations). The issue isn't the flow's creation context but its execution permissions. This option is impractical and incorrect.

Option B: Assign the Manage Users permission to the Agentforce Agent user.

The "Manage Users" permission allows user management (e.g., creating or editing users), which is unrelated to running flows. This permission is excessive and irrelevant for the Service Agent's needs, making it incorrect.

Option C: Assign the Run Flows permission to the Agentforce Agent user.

The Agentforce Service Agent operates under a dedicated system user (e.g., "Agentforce Agent User") with a specific profile or permission set. To execute a flow as part of an Agent Action, this user must have the "Run Flows" permission, either via its profile or a permission set (e.g., Agentforce Service Permissions). This ensures the agent can invoke the custom flow for processing returns, aligning with Salesforce's security model and Agentforce setup requirements. This is the correct answer.

Why Option C is Correct:

Granting the "Run Flows" permission to the Agentforce Agent user is the standard, documented step to enable flow execution in Agent Actions, ensuring the Service Agent can process returns as intended.

Reference:

Salesforce Agentforce Documentation: Agent Builder > Custom Actions Requires "Run Flows" for flow-based actions.

Trailhead: Set Up Agentforce Service Agents Lists "Run Flows" in agent user permissions.

Salesforce Help: Agentforce Security > Permissions Confirms flow execution needs.

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QUESTION: 34

In a Knowledge-based data library configuration, what is the primary difference between the identifying fields and the content fields?

Identifying fields help locate the correct Knowledge article, while content fields enrich AI responses with detailed information.
Identifying fields categorize articles for indexing purposes, while content fields provide a brief summary for display.
Identifying fields highlight key terms for relevance scoring, while content fields store the full text of the article for retrieval.

Answer(s): A

Explanation:

In Agentforce, a Knowledge-based data library (e.g., via Salesforce Knowledge or Data Cloud grounding) uses identifying fields and content fields to support AI responses. Let's analyze their roles.

Option A: Identifying fields help locate the correct Knowledge article, while content fields enrich AI responses with detailed information.

In a Knowledge-based data library, identifying fields (e.g., Title, Article Number, or custom metadata) are used to search and pinpoint the relevant Knowledge article based on user input or context. Content fields (e.g., Article Body, Details) provide the substantive data that the AI uses to generate detailed, enriched responses. This distinction is critical for grounding Agentforce prompts and aligns with Salesforce's documentation on Knowledge integration, making it the correct answer.

Option B: Identifying fields categorize articles for indexing purposes, while content fields provide a brief summary for display.

Identifying fields do more than categorize--they actively locate articles, not just index them. Content fields aren't limited to summaries; they include full article content for response generation, not just display. This option underrepresents their roles and is incorrect.

Option C: Identifying fields highlight key terms for relevance scoring, while content fields store the full text of the article for retrieval.

While identifying fields contribute to relevance (e.g., via search terms), their primary role is locating articles, not just scoring. Content fields do store full text, but their purpose is to enrich responses, not merely enable retrieval. This option shifts focus inaccurately, making it incorrect.

Why Option A is Correct:

The primary difference--identifying fields for locating articles and content fields for enriching responses--reflects their roles in Knowledge-based grounding, as per official Agentforce documentation.

Reference:

Salesforce Agentforce Documentation: Grounding with Knowledge > Data Library Setup Defines identifying vs. content fields.

Trailhead: Ground Your Agentforce Prompts Explains field roles in Knowledge integration.

Salesforce Help: Knowledge in Agentforce Confirms locating and enriching functions.

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QUESTION: 35

Universal Containers' Agent Action includes several Apex classes for the new Agentforce Agent.
What is an important consideration when deploying Apex that is invoked by an Agent Action?

The Apex classes must have at least 75% code coverage from unit tests, and all dependencies must be in the deployment package.
Apex classes invoked by an Agent Action may be deployed with less than 75% test coverage as long as the agent is not activated in production.
The Apex classes may bypass the 75% code coverage requirement as long as they are only used by the agent.

Answer(s): A

Explanation:

Universal Containers (UC) is using Apex classes within an Agent Action for their Agentforce Agent. Deploying Apex in Salesforce has specific requirements, especially when tied to Agentforce functionality. Let's evaluate the options.

Option A: The Apex classes must have at least 75% code coverage from unit tests, and all dependencies must be in the deployment package.

Salesforce enforces a strict requirement that all Apex classes must achieve at least 75% code coverage from unit tests for deployment to production, regardless of their use case (e.g., Agentforce,
triggers, or web services). Additionally, when Apex is invoked by an Agent Action (e.g., via a Flow or direct invocation), all dependencies (e.g., referenced classes, objects) must be included in the deployment package to ensure functionality. This is a standard deployment consideration in Salesforce and applies to Agentforce, making this the correct answer.

Option B: Apex classes invoked by an Agent Action may be deployed with less than 75% test coverage as long as the agent is not activated in production.

Salesforce's 75% code coverage requirement is mandatory for production deployment, regardless of whether the agent is activated. There's no exemption based on activation status--coverage is enforced at the deployment stage. This option is incorrect and contradicts Salesforce's Apex deployment rules.

Option C: The Apex classes may bypass the 75% code coverage requirement as long as they are only used by the agent.

No such bypass exists in Salesforce. The 75% code coverage rule applies universally to all Apex in production, including classes used by Agentforce. Agent-specific usage doesn't waive this requirement, making this incorrect.

Why Option A is Correct:

The 75% code coverage requirement and inclusion of dependencies are fundamental Salesforce deployment rules, applicable to Apex in Agent Actions. This ensures reliability and functionality in production, as per official documentation.

Reference:

Salesforce Agentforce Documentation: Agent Builder > Custom Actions > Apex Notes standard Apex deployment rules apply.

Salesforce Developer Guide: Apex Testing Confirms 75% coverage requirement.

Trailhead: Deploy Apex Code Emphasizes coverage and dependencies for production.

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QUESTION: 36

How does an Agent respond when it can't understand the request or find any requested information?

With a preconfigured message, based on the action type.
With a general message asking the user to rephrase the request.
With a generated error message.

Answer(s): B

Explanation:

Agentforce Agents are designed to handle situations where they cannot interpret a request or retrieve requested data gracefully. Let's assess the options based on Agentforce behavior.

Option A: With a preconfigured message, based on the action type.

While Agentforce allows customization of responses, there's no specific mechanism tying preconfigured messages to action types for unhandled requests. Fallback responses are more general, not action-specific, making this incorrect.

Option B: With a general message asking the user to rephrase the request.

When an Agentforce Agent fails to understand a request or find information, it defaults to a general fallback response, typically asking the user to rephrase or clarify their input (e.g., "I didn't quite get that--could you try asking again?"). This is configurable in Agent Builder but defaults to a user- friendly prompt to encourage retry, aligning with Salesforce's focus on conversational UX. This is the correct answer per documentation.

Option C: With a generated error message.

Agentforce Agents prioritize user experience over technical error messages.
While errors might log internally (e.g., in Event Logs), the user-facing response avoids jargon and focuses on retry prompts, making this incorrect.

Why Option B is Correct:

The default behavior of asking users to rephrase aligns with Agentforce's conversational design principles, ensuring a helpful response when comprehension fails, as noted in official resources.

Reference:

Salesforce Agentforce Documentation: Agent Builder > Fallback Responses Describes general retry messages.

Trailhead: Build Agents with Agentforce Covers handling ununderstood requests.

Salesforce Help: Agentforce Interaction Design Confirms user-friendly fallback behavior.

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QUESTION: 37

What is the role of the large language model (LLM) in understanding intent and executing an Agent Action?

Find similar requested topics and provide the actions that need to be executed.
Identify the best matching topic and actions and correct order of execution.
Determine a user's topic access and sort actions by priority to be executed.

Answer(s): B

Explanation:

In Agentforce, the large language model (LLM), powered by the Atlas Reasoning Engine, interprets user requests and drives Agent Actions. Let's evaluate its role.

Option A: Find similar requested topics and provide the actions that need to be executed.

While the LLM can identify similar topics, its role extends beyond merely finding them--it matches intents to specific topics and determines execution. This option understates the LLM's responsibility for ordering actions, making it incomplete and incorrect.

Option B: Identify the best matching topic and actions and correct order of execution.

The LLM analyzes user input to understand intent, matches it to the best-fitting topic (configured in Agent Builder), and selects associated actions. It also determines the correct sequence of execution based on the agent's plan (e.g., retrieve data before updating a record). This end-to-end process-- from intent recognition to action orchestration--is the LLM's core role in Agentforce, making this the correct answer.

Option C: Determine a user's topic access and sort actions by priority to be executed.

Topic access is governed by Salesforce permissions (e.g., user profiles), not the LLM.
While the LLM prioritizes actions within its plan, its primary role is intent matching and execution ordering, not access control, making this incorrect.

Why Option B is Correct:

The LLM's role in identifying topics, selecting actions, and ordering execution is central to

Agentforce's autonomous functionality, as detailed in Salesforce documentation.

Reference:

Salesforce Agentforce Documentation: Atlas Reasoning Engine Outlines LLM's intent and action handling.

Trailhead: Understand Agentforce Technology Explains topic matching and execution.

Salesforce Help: Agentforce Actions Confirms LLM's role in orchestrating responses.

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QUESTION: 38

Universal Containers (UC) has configured an Agentforce Data Library using Knowledge articles.
When testing in Agent Builder and the Experience Cloud site, the agent is not responding with grounded Knowledge article information. However, when tested in Prompt Builder, the response returns correctly.
What should UC do to troubleshoot the issue?

Create a new permission set that assigns "Manage Knowledge" and assign it to the Agentforce Service Agent User.
Ensure the assigned User permission set includes access to the prompt template used to access the Knowledge articles.
Ensure the Data Cloud User permission set has been assigned to the Agentforce Service Agent User.

Answer(s): C

Explanation:

UC has set up an Agentforce Data Library with Knowledge articles, and while Prompt Builder retrieves the data correctly, the agent fails to do so in Agent Builder and Experience Cloud. Let's troubleshoot the issue.

Option A: Create a new permission set that assigns "Manage Knowledge" and assign it to the Agentforce Service Agent User.

The "Manage Knowledge" permission is for authoring and managing Knowledge articles, not for reading or retrieving them in an agent context. The Agentforce Service Agent User (a system user) needs read access to Knowledge, not management rights. This option is excessive and irrelevant to the grounding issue, making it incorrect.

Option B: Ensure the assigned User permission set includes access to the prompt template used to access the Knowledge articles.

Prompt templates in Prompt Builder don't require specific permissions beyond general Einstein Generative AI access. Since the Prompt Builder test works, the template and its grounding are accessible to the testing user. The issue lies with the agent's runtime access, not the template itself, making this incorrect.

Option C: Ensure the Data Cloud User permission set has been assigned to the Agentforce Service Agent User.

When Knowledge articles are grounded via an Agentforce Data Library, they are often ingested into Data Cloud for indexing and retrieval. The Agentforce Service Agent User, which runs the agent, needs the "Data Cloud User" permission set (or equivalent) to access Data Cloud resources, including the Data Library. If this permission is missing, the agent cannot retrieve Knowledge article data during runtime (e.g., in Agent Builder or Experience Cloud), even though Prompt Builder (running under a different user context) succeeds. This is a common setup oversight and aligns with the symptoms, making it the correct answer.

Why Option C is Correct:

The Agentforce Service Agent User's lack of Data Cloud access explains the failure in agent-driven contexts while Prompt Builder (likely run by an admin with broader permissions) succeeds. Assigning the "Data Cloud User" permission set resolves this, per Salesforce documentation.

Reference:

Salesforce Agentforce Documentation: Data Library Setup > Permissions Requires Data Cloud access for agents.

Trailhead: Ground Your Agentforce Prompts Notes Data Cloud User permission for Knowledge grounding.

Salesforce Help: Agentforce Security > Agent User Setup Lists required permission sets.

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QUESTION: 39

Universal Containers' service team wants to customize the standard case summary response from Agentforce.
What should the Agentforce Specialist do to achieve this?

Create a custom Record Summary prompt template for the Case object.
Summarize the Case with a standard Agent action.
Customize the standard Record Summary template for the Case object.

Answer(s): A

Explanation:

UC's service team seeks to customize the standard case summary response provided by Agentforce.

Let's assess the options for tailoring this output.

Option A: Create a custom Record Summary prompt template for the Case object.

In Prompt Builder, the standard Record Summary prompt template generates summaries for objects like Case. To customize it, the Agentforce Specialist can create a new custom prompt template, specifying the Case object as the source, and adjust the instructions (e.g., tone, fields included) to meet UC's needs. This new template can then be invoked by an agent or flow, providing a tailored summary. This approach offers full control and aligns with Salesforce's customization process, making it the correct answer.

Option B: Summarize the Case with a standard Agent action.

Standard Agent actions (e.g., "Answer Questions") don't specifically target case summarization-- they're broader in scope. There's no out-of-the-box "Summarize Case" action that allows customization of the response format, making this insufficient and incorrect.

Option C: Customize the standard Record Summary template for the Case object.

Standard prompt templates in Prompt Builder (e.g., Record Summary) are read-only and cannot be directly edited. Customization requires cloning or creating a new template, not modifying the standard one, making this incorrect.

Why Option A is Correct:

Creating a custom Record Summary prompt template allows full customization of the case summary, leveraging Prompt Builder's flexibility, as per Salesforce best practices.

Reference:

Salesforce Agentforce Documentation: Prompt Builder > Custom Templates Details creating custom summaries.

Trailhead: Build Prompt Templates in Agentforce Explains customizing standard outputs.

Salesforce Help: Record Summaries with AI Recommends custom templates for tailored results.

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QUESTION: 40

Universal Containers (UC) wants to limit an agent's access to Knowledge articles while deploying the "Answer Questions with Knowledge" action. How should UC achieve this?

Define scope instructions to the agent specifying a list of allowed article titles or IDs.
Update the Data Library Retriever to filter on a custom field on the Knowledge article.
Assign Data Categories to Knowledge articles, and define Data Category filters in the Agentforce Data Library.

Answer(s): C

Explanation:

UC wants to restrict the "Answer Questions with Knowledge" action to a subset of Knowledge articles. Let's evaluate the options for scoping agent access.

Option A: Define scope instructions to the agent specifying a list of allowed article titles or IDs.

Agent instructions in Agent Builder guide behavior but cannot enforce granular data access restrictions like a specific list of article titles or IDs. This approach is impractical and bypasses Salesforce's security model, making it incorrect.

Option B: Update the Data Library Retriever to filter on a custom field on the Knowledge article.

While Data Library Retrievers in Data Cloud can filter data, this requires custom development (e.g., modifying indexing logic) and assumes articles are ingested with a custom field for filtering. This is less straightforward than native Knowledge features and not a standard option, making it incorrect.

Option C: Assign Data Categories to Knowledge articles, and define Data Category filters in the Agentforce Data Library.

Salesforce Knowledge uses Data Categories to organize articles (e.g., by topic or type). In Agentforce, when configuring a Data Library with Knowledge, you can apply Data Category filters to limit which articles the agent accesses. For the "Answer Questions with Knowledge" action, this ensures the agent only retrieves articles within the specified categories, aligning with UC's goal. This is a native, documented solution, making it the correct answer.

Why Option C is Correct:

Using Data Categories and filters in the Data Library is the recommended, scalable way to limit Knowledge article access for agent actions, as per Salesforce documentation.

Reference:

Salesforce Agentforce Documentation: Data Library > Knowledge Filters Describes Data Category filtering.

Trailhead: Ground Your Agentforce Prompts Covers limiting Knowledge scope.

Salesforce Help: Knowledge in Agentforce Recommends categories for access control.

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Salesforce Certified Agentforce Specialist Exam (page: 5) Salesforce Certified Agentforce Specialist Updated on: 25-Dec-2025

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Salesforce Certified Agentforce Specialist Exam (page: 5)
Salesforce Certified Agentforce Specialist
Updated on: 25-Dec-2025