golemcloud/golem/golem-annotate-agent-rust

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Adding prompt and description annotations to Rust agent methods. Use when the user asks to add descriptions, prompts, or documentation metadata to agent methods for AI/LLM discovery.

Install

npx vskill@latest install golemcloud/golem/golem-annotate-agent-rust

SKILL.md

The same SKILL.md was published earlier as adrielc/helios-alpha/golem-annotate-agent-rust.

Annotating Agent Methods (Rust)

Overview

Golem agents can annotate methods with #[prompt] and #[description] attributes. 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

rust
use golem_rust::{agent_definition, agent_implementation, prompt, description};
 
#[agent_definition]
pub trait InventoryAgent {
    fn new(warehouse_id: String) -> Self;
 
    #[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.")]
    fn check_stock(&self, sku: String) -> u32;
 
    #[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.")]
    fn restock(&mut self, sku: String, quantity: u32) -> u32;
 
    #[prompt("Remove units of a product from inventory")]
    #[description("Decreases the stock count for the given SKU. Returns err if insufficient stock.")]
    fn pick(&mut self, sku: String, quantity: u32) -> Result<u32, String>;
}

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

Security

  • Security scanPassed, 100 of 100Pattern checks on the skill's files.
  • Model reviewNot runA model review is scheduled for the next rescan.

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Quality evaluation

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Source

Popularity

Repository stars
1,516
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210
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