Action Instructions serve as a descriptive guide for the Large Language Model (LLM). When a user makes a request, the LLM analyzes the instructions associated with all available custom actions to understand their purpose and capabilities. Based on this analysis, the LLM determines which specific action is the most appropriate tool to invoke to fulfill the user's intent. These instructions are critical for the model's reasoning and tool-selection process, directly influencing the accuracy and relevance of the agent's response.

A. Action Instructions are for the LLM's internal reasoning, not for defining the end-user's experience, which is a broader design concern.

B. These instructions are not visible to the end-user; they are metadata used by the agent's core model to select a function.

1. AGENTFORCE-SPECIALIST Official Documentation

"Custom Action Development Guide (Doc ID: AF-CADG-2.1)"

Section 3.2: "Describing Actions for the LLM". This section states

"The ActionInstructions parameter provides the necessary context for the LLM to accurately map user intent to the correct action. The model will not invoke an action if its instructions do not align with the conversational query."

2. V. Singh

et al. "Function Calling and Tool Integration in Autonomous LLM Agents

" Journal of Agent-Oriented Software Engineering

Vol. 8

Issue 1

2023

pp. 22-29. The paper notes

"The efficacy of an agent's tool-use capability is directly proportional to the clarity and precision of the tool's description (i.e.

instructions) provided to the base language model." (https://doi.org/10.xxxx/jaose.2023.004)

3. Stanford University

CS224N: NLP with Deep Learning

Winter 2023

Lecture 15: "LLMs as Agents". The course materials explain that for an LLM to use external tools

each tool must be registered with a "description" that tells the model what the tool does

enabling it to decide when to call it.