Salesforce Agentforce-Specialist Online Access

The correct answer is C because the company is not asking for a generic quality score; it needs evaluation against a proprietary de-escalation framework and empathy standard. Salesforce Testing Center supports LLM-judge style evaluations where a judge model compares the agent response against task criteria. For a custom rubric, the specialist should create a custom evaluation and provide a tailored prompt that defines the exact framework criteria. Option A is wrong because standard Coherence is not intended to be rewritten into a proprietary policy rubric. Option B is also too generic because default instruction adherence does not necessarily understand UC’s internal de-escalation model. Custom evaluation is the right mechanism for organization-specific qualitative standards.

Per the AgentForce Configuration and Control Flow Guide, enforcing deterministic business rules—such as restricting certain actions based on a data condition—requires using context variables with conditional filters. The guide specifies: “Use context variables mapped to relevant Salesforce fields to store state information. Then apply conditional filters to ensure actions execute only when specific conditions (e.g., membership tier) are met.”

This ensures the rule is deterministic, meaning the action cannot trigger if the condition is not satisfied.

Option A (object validation rules) restricts record creation or updates but does not control AgentForce’s action logic. Option B (topic instructions) relies on natural language guidance, which is non-deterministic and can be ignored by the model.

Therefore, Option C—creating a context variable mapped to the membership tier and applying a conditional filter—is the correct, documented approach.

References (AgentForce Documents / Study Guide):

AgentForce Implementation Guide: “Conditional Logic Using Context Variables”

AgentForce Study Guide: “Deterministic Action Control with Filters”

Salesforce Agent Configuration Best Practices

According to the AgentForce Action Orchestration and Control Logic Guide, deterministic restrictions on action execution should be implemented using context variables and conditional filters.

By creating a context variable (e.g., AccountStatus) that pulls the customer’s current status and applying a conditional filter that limits execution to cases where AccountStatus = " Active " , the refund action can be programmatically restricted. This ensures the agent can only trigger the refund flow when conditions are met, providing both consistency and governance over sensitive actions.

Option A (adding instructions in a prompt) is non-deterministic — the LLM might ignore or misinterpret instructions. Option C (explaining rules in text) adds guidance but not enforcement. Only filters guarantee deterministic enforcement.

Thus, the correct answer is Option B – Use context variables with conditional filters for deterministic action control.

Action Assertion is the correct metric because the failure is not subagent routing; the agent already selected the correct subagent. The failure is at the tool/action selection layer inside that subagent. Salesforce Testing Center evaluations include subagent assertion and action assertion as separate checks. Subagent Assertion validates whether the utterance was routed to the expected subagent. Action Assertion validates whether the correct required actions were selected or used. Response Evaluation is broader and focuses on the quality of the final answer, such as relevance or accuracy, but it does not specifically isolate missing tool selection. In this scenario, the specialist needs to identify that the agent reached the right area but failed to invoke all required actions, so Action Assertion is the precise metric.