Live open appointment slots for a service id (from list_services) over an optional date range (default next 5 weeks, max 62 days). Slots are not held - the customer reserves by completing checkout (with payment) at the booking_url.
| Name | Required | Description | Default |
|---|---|---|---|
| date_to | No | End date YYYY-MM-DD (optional). | |
| date_from | No | Start date YYYY-MM-DD (optional, default today). | |
| service_id | Yes | Service id from list_services. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses critical behavior: slots are not held and are only reserved after payment at booking_url, clarifying the non-reserving nature. It omits auth/rate limits, but the key state-related behavior is well covered.
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 sentences pack all essential information without redundancy. Every clause adds value, making it highly efficient and well-structured.
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 no output schema, the description adequately explains the tool's purpose and behavior. It could detail the response format (e.g., per-slot fields), but the core usage and constraints are sufficiently complete for a tool with simple inputs and clear intent.
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 covers all parameters, so baseline is 3. The description adds meaningful context: service_id is from list_services, and date_from defaults to today while date range is capped at 62 days, going beyond the schema 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 lists live open appointment slots for a given service id, with an optional date range. It distinguishes itself from siblings like list_services and get_booking_link by focusing on availability and including the booking_url context.
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?
It explicitly instructs that service_id comes from list_services and sets date range defaults/maximums, implying a prerequisite and constraints. It lacks explicit 'when not to use' or alternative comparisons, but the context is clear enough for correct selection.
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 has a distinct purpose: checking availability, getting booking link, business hours, and listing services. There is no overlap or ambiguity between them.
All tool names follow a consistent verb_noun pattern: check_availability, get_booking_link, get_business_hours, list_services. The naming is uniform and predictable.
With 4 tools, the server is well-scoped for its purpose. Each tool covers a necessary aspect of the booking flow without unnecessary bloat.
The tool set covers the essential pre-booking information: services, availability, hours, and the booking link. Since payment and booking are intentionally handled on the website, the API surface is complete for its stated scope.
