Use after verification to check availability for a verified customer at a selected saved address.
| Name | Required | Description | Default |
|---|---|---|---|
| address_id | No | ||
| service_type | Yes | ||
| session_token | Yes | ||
| preferred_date | No | ||
| time_preference | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description mentions the prerequisite of verification and implies a non-destructive read operation via 'check'. However, without annotations, it omits details about response format, error conditions, or side effects, leaving some behavioral ambiguity.
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 a single, unambiguous sentence, front-loaded with the key usage condition ('after verification'). No filler words.
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 5 parameters, no output schema, and no annotations, the description is too brief to provide a complete understanding. It lacks information about return values, error handling, and how the parameters interact.
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 has zero description coverage, and the tool description only loosely refers to a 'verified customer' and 'selected saved address', which likely map to session_token and address_id. It does not explain preferred_date, time_preference, or service_type, requiring the agent to infer from enums and patterns alone.
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 availability for a verified customer at a selected saved address, using the specific verb 'check' and resource 'availability'. It distinguishes from sibling check_availability by adding the context of verification and saved address.
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 sequencing ('after verification') and specifies the target scenario (verified customer, selected saved address). It does not name alternative tools or exclusion criteria, but the context is clear.
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.