Kitchen Flow Summary

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

Annotations already indicate readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds behavioral context: it aggregates data, returns a bottleneck flag, and provides wait times. No contradictions.

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 English portion is concise and front-loaded. However, the Spanish duplicate makes the description longer than necessary. It's still readable and efficient enough for a simple tool.

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?

Given no parameters, a relatively simple output, and comprehensive annotations, the description fully explains the tool's purpose, usage, and return values, making it complete for an AI agent.

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?

No parameters exist, so the schema fully covers them. The description adds no parameter information, but none is needed. Baseline for 0 params is 4, but the description's clarity on output compensates for the lack of param details.

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 tool aggregates open kitchen tickets per station and flags the bottleneck. It specifies the returned fields (openTickets, oldest wait, isBottleneck). This distinguishes it from siblings like list_kitchen_tickets or get_kitchen_ticket.

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?

Explicit instruction: 'Call this first to diagnose kitchen throughput issues before drilling into individual tickets.' Provides a clear when-to-use and implies not to use for other purposes.

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