order_starbucks_favorite

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the transparency burden. It discloses a potential failure mode (item names not found) and suggests recovery, which is valuable. However, it does not mention side effects like payment, confirmation, or how order status is returned, leaving gaps for a mutation tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, with the primary action front-loaded and the troubleshooting tip highlighted with 'IMPORTANT'. Every word earns its place; no fluff or repetition.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description provides a useful failure-recovery note, but the tool lacks an output schema and does not explain what happens after ordering (e.g., auto-confirm, cancellation, or status return). Sibling tools like confirm_starbucks_order and cancel_starbucks_order suggest additional steps, yet the description does not guide the agent on these dependencies.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with descriptions for both parameters. The description adds value over the schema by giving examples of favorite names ('Morning Coffee Run', 'Breakfast'), which helps infer the expected format. The location parameter is mentioned in schema and not expanded, but the description's examples enhance understanding.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action: 'Order a saved Starbucks favorite' with concrete examples. It distinguishes from siblings like order_starbucks_custom by focusing on 'saved' favorites, and from list_starbucks_favorites by indicating an ordering action.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives a clear when-to-use context ('Order a saved favorite') and a specific conditional fallback: 'If order fails due to item names not found, use get_starbucks_menu first'. However, it does not explicitly contrast with order_starbucks_custom or mention prerequisites like login, but the siblings signal these are available.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.