| name | golem-annotate-agent-ts |
| description | Adding prompt and description annotations to TypeScript agents and their methods. Use when the user asks to add descriptions, prompts, or documentation metadata to agent classes or methods for AI/LLM discovery. |
Annotating Agents and Methods (TypeScript)
Overview
Golem agents can annotate the agent class and its methods with @prompt() and @description() decorators. These provide metadata for AI/LLM tool discovery — agents with annotations 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 agent or method does, its parameters, and return value
Agent-Level Annotations
To describe the agent itself (its overall purpose), apply @description() as a standalone class-level decorator alongside @agent(). Do NOT pass description as a property inside the @agent() options — AgentDecoratorOptions does not accept it, and it will cause a TypeScript compilation error.
@agent({ mount: "/api/v1/profiles" })
@description("Handles user profile management and preferences")
class ProfileAgent extends BaseAgent { ... }
@agent({ mount: "/api/v1/profiles", description: "..." })
class ProfileAgent extends BaseAgent { ... }
Method-Level Annotations
import { BaseAgent, agent, prompt, description } from '@golemcloud/golem-ts-sdk';
@agent({ mount: "/warehouses/{warehouseId}" })
@description("Manages product inventory for a warehouse")
class InventoryAgent extends BaseAgent {
constructor(warehouseId: string) {
super();
}
@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.")
async checkStock(sku: string): Promise<number> {
}
@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.")
async restock(sku: string, quantity: number): Promise<number> {
}
@prompt("Remove units of a product from inventory")
@description("Decreases the stock count for the given SKU. Throws if insufficient stock.")
async pick(sku: string, quantity: number): Promise<number> {
}
}
Guidelines
@description() on the class describes the agent's overall purpose for LLM discovery
@prompt() on a method should be a natural-language instruction an LLM can match against a user request
@description() on a method should document behavior, edge cases, and expected inputs/outputs
- Both decorators are optional — omit them for internal methods not intended for LLM discovery
- Annotations have no effect on runtime behavior; they are purely metadata
- Never pass
description as a property of the @agent() decorator options — always use the standalone @description() decorator