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Salesforce Agentforce-Specialist Exam Questions

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Salesforce Certified Agentforce Specialist (AI-201) Spring 26 Update

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Salesforce Agentforce-Specialist Sample Questions – Free Practice Test & Real Exam Prep

Question #1

Universal Containers is deploying two agents simultaneously: an internal Sales Productivity Agent for employees and a customer-facing Service Agent on its Experience Cloud site. An Agentforce Specialist is configuring permissions and needs to understand the correct security context for each. Which statement accurately describes the execution model? 

  • A. The customer-facing Service Agent inherits the security context of the Experience Cloud site’s guest user profile by default, requiring guest profile object permissions to be configured for all actions the agent executes. 
  • B. The internal Sales Productivity Agent executes actions using the authenticated Salesforce employee’s own permissions, while the customer-facing Service Agent executes actions as a dedicated Einstein Service Agent User with its own permission set. 
  • C. Both the internal Sales Productivity Agent and the customer-facing Service Agent execute actions as a dedicated Einstein Service Agent User with its own permission set that is configured as required for the agent.
Answer: B
Explanation: Employee (internal) agents run actions in the context of the logged-in employee, using that user's permissions and sharing. Customer-facing Service Agents run as a dedicated Einstein Service Agent User with its own permission set, which admins configure. Option A is wrong because the service agent does not run as the guest user, and option C is wrong because internal agents do not use a service agent user. 
Question #2

Universal Containers wants to use an existing prompt template inside Flow as part of automation.

  • A. Invocable Apex 
  • B. Einstein for Flow 
  • C. Flow action 
Answer: C
Explanation: A prompt template can be used in Flow by adding an Action element and selecting the prompt template. The flow passes inputs and uses the generated output in later automation steps. Invocable Apex (A) is unnecessary, and Einstein for Flow (B) creates flows from natural language rather than calling templates.
Question #3

Universal Containers needs to bring individual customer warranties from an external system into Data Cloud. They want Agentforce to return warranty-related responses only for accounts whose warranty status is active. Which search approach should the Agentforce Specialist configure to ensure warrantyrelated information is retrieved correctly? 

  • A. Depend on Agentforce instructions to enforce warranty constraints and include only WarrantyStatus = Active results. 
  • B. Store the account's warranty status in an Agentforce custom variable to dynamically filter warranties during retrieval. 
  • C. Use Hybrid Search and apply pre-filtering in a new custom retriever for matching accounts and where the WarrantyStatus = Active field,
Answer: C
Explanation: A custom retriever with pre-filtering on the account and WarrantyStatus = Active ensures that only relevant, active warranty records are searched. Hybrid search then combines keyword and semantic matching for accurate retrieval. Instructions (A) are not deterministic, and a custom variable alone (B) does not perform retrieval filtering without a retriever configured for it.
Question #4

A service manager wants to use Salesforce Prompt Builder to help agents summarize customer case notes after a support call. The summary should: Capture the customer’s issue, troubleshooting steps taken, and next actions. Be no longer than five sentences. Use plain language with no technical jargon. If no next action is identified, the summary should explicitly state “No next action required.” Which key prompt constructs meet this requirement?

  • A. Role, Task, LLM Clarity Score, and Format 
  • B. Role, Task, Token Size Limit, and Format 
  • C. Task, Context, Constraints, and Format 
Answer: C
Explanation: Effective prompts state the Task (summarize case notes), give Context (issue, troubleshooting steps, next actions), list Constraints (five sentences maximum, plain language, the fallback phrase), and define the Format. This structure covers every requirement. 'LLM Clarity Score' (A) and 'Token Size Limit' (B) are not prompt constructs.
Question #5

Universal Containers (UC) is deploying several prompt templates to assist its support agents using Salesforce’s standard foundation models. Leadership requires the generated responses to consistently reflect an empathetic and highly professional tone. UC only permits the use of standard foundational large language models (LLMs). What is the most effective prompt engineering technique the Agentforce Specialist should implement in Prompt Builder to fulfill this requirement? 

  • A. Configure the prompt template tone with a dataset of past interactions using different writing styles, intensifiers, and punctuation to permanently alter the LLM default tone. 
  • B. Include a direct instruction asking the LLM to role-play as a specific character, for example, “Act as an empathetic customer support agent,” to provide context and establish the tone. 
  • C. Include multiple-choice picklist questions within the prompt template to systematically test and correct the LLM’s understanding of the desired context before generating the output. 
Answer: B
Explanation: Role prompting, such as 'Act as an empathetic, professional customer support agent', gives the LLM clear context and sets the tone of the response. It works with standard foundation models and requires no training. Permanently changing a model's tone with a dataset (A) is fine-tuning, which UC does not allow. Picklist questions (C) are not a prompt technique for tone.
Question #6

Universal Containers has set up a Service Agent to allow customers to look up their order status. The topic setup includes: Name: Order Inquiry Classification Description: Handles user requests to look up order status, including tracking details and delivery estimates for orders placed within the last 90 days. Scope: Your job is only to assist authenticated users in looking up the status of their orders placed within the last 90 days. If the order is pending delivery, provide the tracking number and estimated delivery date. Do not handle inquiries for orders older than 90 days. Which information will be used by the Agentforce reasoning engine to choose this topic? 

  • A. Topic Name and Classification Description 
  • B. Topic Name and Scope 
  • C. Classification Description and Scope 
Answer: A
Explanation: The reasoning engine selects a topic by comparing the user's utterance with each topic's name and classification description. The scope and instructions guide the agent's behavior after the topic has been selected, not the selection itself. Options B and C wrongly include scope as a classification input.
Question #7

Coral Cloud Resorts (CCR) wants to configure its agent so that booking actions are only available when a customer's membership tier is “Premium” or “Elite”. This business rule must be enforced deterministically. What should CCR implement?

  • A. Set up custom validation rules on the underlying booking objects to prevent non-eligible customers from completing bookings. 
  • B. Configure topic instructions that clearly state booking actions should only be used for Premium or Elite customers and include examples. 
  • C. Create a context variable mapped to the customer's membership tier field, then add a conditional filter on MembershipTier. 
Answer: C
Explanation: A context or custom variable holding the customer's membership tier, combined with a conditional filter on the booking actions (MembershipTier is Premium or Elite), makes those actions unavailable otherwise. This enforces the rule deterministically. Validation rules (A) block the save after the agent tries, which creates errors, and instructions (B) are not guaranteed.
Question #8

A Service Agent at Universal Containers (UC) is designed to help customers resolve issues by searching against knowledge articles. Knowledge articles have PDF attachments that add critical details. UC reports that the agent provides excellent summaries of the knowledge articles, but seems completely unaware of the PDF attachments. How should an Agentforce Specialist configure the Data Cloud search index to include the content of these attached files? 

  • A. Increase article chunk size and token limits for Knowledge indexing so larger contexts capture attachment references. 
  • B. Enable 'Include Related Attachments’ for Knowledge-- kav and map the ContentDocumentLink unstructured data model object (UDMO). 
  • C. Use Data Cloud's ‘Include Attachments’ option and select the ContentDocumentVersion unstructured data model object (UDMO). 
Answer: C
Explanation: To include attached files in search, the Data Cloud search index must ingest the attachment content. Using the include attachments option with the ContentDocumentVersion unstructured object brings the files' text into the index, so the agent can use it. Increasing chunk size (A) does not ingest attachment content, and ContentDocumentLink (B) links files to records but does not hold their content.
Question #9

A company needs to ensure customers always receive answers based on the most current version of support documentation. What should an Agentforce Specialist recommend?

  • A. Use a file-based Agentforce Data Library (ADL) and enable the version management setting to ensure the agent always retrieves the latest document. 
  • B. Use a knowledge-based Agentforce Data Library (ADL); knowledge articles have native versioning built in, so agents automatically retrieve the current published version.
  • C. Use either Agentforce Data Library (ADL) type; both automatically serve the most recent content once the search index rebuilds. 
Answer: B
Explanation: Salesforce Knowledge has built-in versioning and a publication lifecycle. A knowledge-based data library indexes the published version, so agents retrieve the current approved article. File-based libraries (A) have no version management setting, and they do not provide the same native versioning (C).
Question #10

During retrieval-augmented generation (RAG) quality testing, an Agentforce Specialist notices that tabular information from a custom Data 360 Document Ingestion Pipeline is losing its context because the data is scattered across multiple separate chunks. What is the most appropriate approach to resolve this?

  • A. Change the search index’s parser from the default to Docling. 
  • B. Use an ensemble retriever to stitch multiple chunks back together dynamically. 
  • C. Switch the search index configuration to use only keyword search scoring. 
Answer: A
Explanation: Tables lose context when a simple parser splits them across chunks. Switching the search index parser to an advanced, layout-aware parser such as Docling preserves document structure, including tables, so related data stays together. Stitching chunks with an ensemble retriever (B) is not how ensemble retrievers work, and keyword-only search (C) does not fix chunking.
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