Cancel a Wanaka Haus booking under the published policy (full refund to 14 days before arrival, 50% to 7 days, none inside 7). Requires the guest email the booking was made with.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | ||
| guest_email | Yes | Must match the email the booking was made with |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Since no annotations are provided, the description carries the full burden. It discloses key behavioral traits: the cancellation refund schedule (full refund, 50%, none) and the requirement for the guest email. It does not mention potential side effects or idempotency, but the disclosed traits are significant.
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 consists of two short, front-loaded sentences that convey essential information without any wasted words. Every sentence adds value.
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 (2 parameters, no output schema), the description covers the cancellation policy and required email. It could mention that the booking must exist, but the information provided is largely sufficient for an agent to invoke 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?
The input schema covers 2 parameters with partial description (guest_email has pattern and description; id lacks description). The description adds some meaning by stating the guest email requirement but provides little beyond the schema. With 50% schema description coverage, the description does not fully compensate.
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 ('Cancel') and resource ('Wanaka Haus booking') using a specific verb plus resource, and it distinguishes itself from sibling tools like create_booking or get_booking by focusing on cancellation.
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 context on when to use the tool (under the published policy with a detailed refund schedule) and a prerequisite (requires guest email). However, it does not include when not to use the tool or explicitly mention alternatives among sibling tools.
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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Each tool has a clearly distinct purpose: searching availability, getting a quote, creating a booking, checking booking status, and canceling. No overlap or ambiguity.
All tool names follow a consistent verb_noun pattern in snake_case (e.g., search_availability, create_booking, cancel_booking), making them predictable and easy to understand.
With 5 tools covering the core booking workflow (search, quote, create, status, cancel), the count is well-scoped and appropriate for the server's purpose.
The tool surface covers the essential lifecycle of a booking: checking availability, pricing, creation, status retrieval, and cancellation. No obvious gaps for typical booking operations.