Annotating Agent Methods (Scala)

Overview

Golem agents can annotate methods with @prompt and @description annotations. These provide metadata for AI/LLM tool discovery — agents with annotated methods can be used as tools by LLM-based systems.

Annotations

@prompt("...") — A short instruction telling an LLM when to call this method
@description("...") — A longer explanation of what the method does, its parameters, and return value

Usage

import golem.runtime.annotations.{agentDefinition, description, prompt}
import golem.BaseAgent
 
import scala.concurrent.Future
 
@agentDefinition(mount = "/inventory/{warehouseId}")
trait InventoryAgent extends BaseAgent {
  class Id(val warehouseId: String)
 
  @prompt("Look up the current stock level for a product")
  @description("Returns the number of units in stock for the given product SKU. Returns 0 if the product is not found.")
  def checkStock(sku: String): Future[Int]
 
  @prompt("Add units of a product to inventory")
  @description("Increases the stock count for the given SKU by the specified amount. Returns the new total.")
  def restock(sku: String, quantity: Int): Future[Int]
 
  @prompt("Remove units of a product from inventory")
  @description("Decreases the stock count for the given SKU. Returns a Left if insufficient stock.")
  def pick(sku: String, quantity: Int): Future[Either[String, Int]]
}

Guidelines

@prompt should be a natural-language instruction an LLM can match against a user request
@description should document behavior, edge cases, and expected inputs/outputs
Both annotations are optional — omit them for internal methods not intended for LLM discovery
Annotations have no effect on runtime behavior; they are purely metadata

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