Cancel a booking
cancel_bookingCancels a booking under the business cancellation policy. Confirm with the user first and tell them whether a late fee applies.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| reason | No | ||
| booking_id | Yes | ||
| manage_token | No |
cancel_bookingCancels a booking under the business cancellation policy. Confirm with the user first and tell them whether a late fee applies.
| Name | Required | Description | Default |
|---|---|---|---|
| reason | No | ||
| booking_id | Yes | ||
| manage_token | No |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already signal destructive and non-read-only behavior. The description adds meaningful behavioral context beyond that: cancellation is governed by the business policy, user confirmation is required, and the user must be informed of late fees. It aligns with destructiveHint and idempotentHint, with no contradiction.
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 short sentences with no filler. It front-loads the primary action and policy immediately, then states the required user-facing steps. Every sentence earns its place.
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 covers the core action, policy context, confirmation requirement, and fee disclosure, which is adequate for a simple cancellation. However, it lacks guidance on manage_token, what happens after cancellation (e.g., refunds or side effects), and does not distinguish itself from owner_cancel_booking. Given no output schema, these gaps make it only partially complete.
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 0%, and the description adds no meaning for the three parameters. It never explains booking_id, reason, or manage_token, leaving manage_token particularly ambiguous. With no parameter descriptions in the schema and no compensation in the description, an agent has insufficient semantic grounding.
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 states a clear, specific action ('Cancels a booking') and the resource affected. It implies a customer-side cancellation via 'under the business cancellation policy' and 'Confirm with the user first,' but it does not explicitly distinguish this tool from the sibling owner_cancel_booking.
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 intended usage is implied by the action itself: use when a booking must be cancelled. It also gives a key precondition and follow-up step ('Confirm with the user first and tell them whether a late fee applies'). However, it gives no explicit guidance about when not to use it or which sibling alternative to prefer.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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