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Timeplex K-Beauty Booking

get_shop_services

Read-onlyIdempotent

Get the available services, prices, durations, and bookable staff or resources for a specific Korean beauty or wellness shop. Use this after finding a shop when service details, prices, durations, staff, or resources are needed before checking appointment availability. Pass lang to receive the content translated into the customer's language.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
langNoCustomer language (optional): ko|en|ja|zh|th. Defaults to the original text (ko).
slugYesShop slug returned by search_shops

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
langNo
noteNo
shopYes
servicesYes
resourcesNoStaff to designate (designated-staff shops) or seats (capacity-based shops).
booking_modelNoHow this shop books: 'designated' — pass items as [{service_id, resource_id}]; 'capacity' — pass items as [{service_id, qty}]. Use this for search_availability and start_booking.

TDQS

A4.7/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds meaningful context beyond the annotations by stating it returns services, prices, durations, and bookable staff/resources, and that passing 'lang' translates content into the customer's language. This adds functional behavior not present in the structured metadata, though it doesn't mention rate limits or pagination, which is minor for a simple read operation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is just two sentences and front-loads the core purpose. The first sentence states the primary function, and the second sentence covers usage timing and translation behavior. There is no superfluous content, and every statement earns its place. It is concise yet informative.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's low complexity (2 params, 1 required), the presence of an output schema, and annotations covering safety, the description is complete. It explains what the tool returns, when to use it in the workflow, and how to request translation. Nothing an agent needs to correctly invoke it is missing. The sibling distinction and usage guidance are fully covered.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so both 'slug' and 'lang' are already documented in the schema. The description goes beyond the schema by explaining that 'lang' translates the returned content, adding a behavioral nuance not in the schema's parameter description. For 'slug,' the schema already references it as returned by search_shops, and the description doesn't need to add more. This is a slight enhancement over the baseline of 3 for full coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb 'Get' and names the exact resource ('available services, prices, durations, and bookable staff or resources') for a specific shop. It differentiates itself from siblings by placing itself between finding a shop and checking availability, which maps directly to search_shops and search_availability. This is unambiguous and distinguishes it from the other tools without needing their schemas.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly states when to use the tool: 'Use this after finding a shop when service details, prices, durations, staff, or resources are needed before checking appointment availability.' This provides a clear temporal sequence and condition, implicitly contrasting with search_availability (for checking availability) and search_shops (for finding the shop). It also mentions the optional 'lang' parameter for translation, which further guides correct invocation.

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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TDQS

A4.5/5.0
Disambiguation5/5

Each tool targets a distinct step in the booking workflow: searching shops, retrieving services, checking availability, initiating a booking, and handling manual requests for non-bookable shops. Their purposes and usage conditions are clearly separated with specific guidance on when to use each, eliminating ambiguity.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern in snake_case: get_shop_services, request_booking, search_availability, search_shops, start_booking. The verbs (get, request, search, start) and nouns (shop_services, booking, availability, shops) are all lowercase and underscore-separated, providing a predictable and readable naming scheme.

Tool Count5/5

With exactly 5 tools, the server is well-scoped for its purpose. It covers the essential phases of finding a shop, inspecting services, checking availability, and initiating bookings, without unnecessary expansion. This count is typical for a focused domain-specific MCP and each tool earns its place.

Completeness4/5

The tool set covers the primary booking flow comprehensively: search_shops, get_shop_services, search_availability, and start_booking handle the standard online-booking path, while request_booking covers shops that require manual concierge intervention. Minor gaps exist (e.g., no tool for canceling or modifying bookings), but since start_booking only generates a booking link and actual reservation management happens on the booking page, the surface is reasonably complete for its stated purpose.

Resources