List the user's saved payment methods for booking. Returns saved credit/debit cards with their payment IDs, needed for the book_hotel tool.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark the operation as read-only and non-destructive. The description adds meaningful context about what is returned (credit/debit cards and payment IDs) and why, which is useful for the agent.
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?
Two concise sentences with no filler. The main action and key return value are front-loaded, and the booking context is included efficiently.
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?
With zero parameters, an output schema present, and safe read-only annotations, the description sufficiently explains what the tool does and why it is used. Nothing essential is missing for correct invocation.
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 tool accepts no parameters and the schema has no properties, so there is little for the description to add. The baseline of 4 applies because parameter semantics are effectively irrelevant here.
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 uses a specific verb ('List') and resource ('user's saved payment methods'), and clarifies the purpose: returning credit/debit cards with payment IDs for booking. It clearly distinguishes itself from the many other get_* sibling tools by connecting to the book_hotel tool.
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 gives clear context: this is for booking and provides inputs needed for book_hotel. It doesn't explicitly exclude alternatives or state when not to use it, but the intended use case is evident.
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.
Each tool targets a distinct resource and action; no two tools have overlapping purposes. For example, search_hotels, get_hotel_details, get_hotel_reviews, and get_hotel_stats all address different aspects of hotel research.
Tool names follow consistent patterns: search_ for searches, get_ for retrievals, book_ for bookings, and a few standalone verbs like cancel_, create_, delete_. All use snake_case with no mixing of conventions.
With 31 tools, the server is on the high side but covers a broad domain (hotels, flights, vehicles, loyalty, payments). Most tools are justified, though a few hotel analysis tools could potentially be consolidated.
Hotels and vehicles have near-complete lifecycle coverage (search, details, book, manage), but flights are missing a book_flight tool, and hotel cancellation is not present. These gaps limit completeness.
