An Al Specialist is creating a custom action for Agentforce.

To ensure a custom action in Agentforce performs as expected, the AI Specialist must focus on Action Instructions. Here's why:

Action Instructions define the logic, parameters, and steps the AI should follow to execute the action. They include:

How input data is processed.

API calls or Apex invocations.

Conditional logic (e.g., decision trees).Testing and iterating on these instructions ensures alignment with the intended workflow. For example, incorrect API endpoint references or misconfigured parameters in the instructions will cause failures.

Action Input (Option A) refers to the data provided to the action. While validating input formats is important, inputs are static once defined. The primary issue lies in whether the instructions correctly use the inputs.

Action Name (Option B) is a descriptive label and does not affect functionality.

Salesforce Documentation Support:

Salesforce Einstein Bots & Custom Actions Guide highlights that Action Instructions are where the "core logic" resides, requiring rigorous testing (Source: Einstein Bots Developer Guide).

Trailhead Module "Build Custom Actions for Einstein Bots" emphasizes refining instructions to handle edge cases and validate outputs (Source: Trailhead).

By iterating on Action Instructions, the AI Specialist ensures the action’s logic, integrations, and error handling are robust.