order_starbucks_custom

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

With no annotations, the description must carry the burden of disclosing side effects and workflow. It fails to mention that placing an order likely triggers a purchase, requires authentication, or that confirmation may be needed (given siblings like confirm_starbucks_order). The menu prerequisite is a useful constraint, but the description omits critical behavioral context about order placement and consequences.

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?

The description is two sentences, front-loaded with the primary action, and includes a crucial tip in an attention-grabbing way. 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 tool operates within a complex workflow (login, order, confirm, cancel), yet the description provides no context about authentication, order confirmation, or cancellation. It does not mention that confirm_starbucks_order may be required after placing the order. While the schema covers parameter structure, the description fails to convey the surrounding process, making it incomplete for an agent to use correctly.

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 description coverage is 100%, so the baseline is 3. The description adds minimal extra meaning beyond the schema—it merely mentions 'specific drinks and food' and the menu prerequisite, which is more of a usage guideline than parameter semantics. The schema already provides useful examples and definitions.

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 ('Place a custom Starbucks order') and specifies the content ('specific drinks and food'). It distinguishes itself from sibling 'order_starbucks_favorite' by explicitly labeling this as 'custom', making the purpose unambiguous.

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?

The description provides an explicit prerequisite: 'Always use get_starbucks_menu first to get exact item names before ordering.' This gives clear guidance on a necessary precondition. However, it does not state when not to use this tool (e.g., for favorites) or explicitly contrast with siblings, so it misses the full 'when-not' guidance.

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