Use to check whether a booking payment session is pending, paid, failed, canceled, or expired before attempting booking creation.
| Name | Required | Description | Default |
|---|---|---|---|
| session_token | Yes | ||
| payment_session_id | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full responsibility. It states that the tool 'checks' statuses, implying a read-only operation, and adds useful context about timing. However, it does not disclose any potential side effects, error conditions, or what happens if the session is invalid, leaving some behavioral gaps.
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?
A single, well-structured sentence that front-loads the action ('Use to check') and wastes no words. It is concise and to the point.
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 purpose and timing but does not explain the return value format in detail (no output schema exists). It indirectly indicates the response will reflect one of the listed statuses, but it could be more explicit about what the agent should expect. Given the tool's simplicity and the presence of clear statuses, this is adequate but not fully 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 does not mention session_token or payment_session_id at all. While the parameter names are somewhat self-explanatory, the description adds no meaning about their origins, relationships, or usage, failing to compensate for the schema's lack of 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 checks the status of a booking payment session, listing five specific statuses (pending, paid, failed, canceled, expired). The verb 'check' and resource 'booking payment session' are precise, and it distinguishes from siblings like get_booking_status and start_booking_payment.
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 timing context: 'before attempting booking creation.' It does not name alternatives or exclusions, but the context is clear enough to understand when this tool should be used in the booking flow.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Some tools overlap in purpose, such as check_availability vs get_customer_availability and the various verification entry points. Descriptions clarify the context of each, but an agent could still misselect without careful reading.
All tools follow a consistent verb_noun pattern with snake_case, e.g., check_availability, create_booking_request, get_booking_status. This makes the naming predictable and easy to navigate.
With 20 tools, the server is on the heavier side but the scope is broad, covering booking, customer verification, payments, and provider matching. The count feels slightly high but each tool serves a distinct step in the workflow.
The tool surface covers the full booking lifecycle from availability and quote to payment and final creation. Notable gaps include lack of update or cancel booking operations, but the core flow is well covered.