1Stay Hotel Booking

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

The description adds significant behavioral context beyond annotations. Annotations indicate read-only and non-destructive operations, but the description elaborates on identity verification requirements, privacy protections (doesn't return booking details in conversation), and the email-sending outcome. It doesn't contradict annotations—the 'resend' action aligns with read-only since it doesn't modify the booking itself. However, it doesn't mention rate limits or error handling.

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 well-structured and front-loaded with the core purpose. Each sentence adds critical information: identity verification, required inputs, usage constraints, and differentiation from siblings. There's no wasted text—every part (including the numbered list) serves to guide the agent effectively. The formatting with clear sections enhances readability.

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 the tool's complexity (verification logic, privacy considerations) and lack of output schema, the description provides complete context. It covers the tool's purpose, behavioral traits, parameter semantics, and usage guidelines. The annotations cover safety (read-only, non-destructive), and the description fills in the gaps about verification, email outcomes, and sibling tool differentiation. No essential information is missing for an agent to use this tool 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?

With 100% schema description coverage, the baseline is 3. The description adds value by explaining parameter dependencies and verification logic: it clarifies that 'last_four_card' requires 'check_in_date', and that parameters represent verification factors. It also emphasizes that 'first_name' and 'last_name' are mandatory together. This provides context beyond the schema's individual parameter descriptions.

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's purpose: 'Find a reservation and resend the confirmation email.' It specifies this is a 'guest-facing lookup tool' that enforces identity verification, distinguishing it from sibling tools like 'get_booking' (which likely returns booking details directly) and 'cancel_booking' (which modifies the reservation). The description goes beyond the name/title by explaining the dual functionality of lookup and email resending.

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 explicit guidance on when to use this tool versus alternatives. It states: 'Do NOT call this tool until you have the guest's full name AND at least one verification factor' and specifies what to do if verification factors are missing. It also distinguishes from 'cancel_booking' for cancellation tasks. The guidelines cover prerequisites, exclusions, and alternative actions clearly.

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