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banquets__get_reserve_restaurant_sections

Read-only

Retrieve restaurant sections with table layouts for banquet and reservation booking using terminal group IDs. Filters sections available for reserve, with optional revision and schema parameters.

Instructions

Секции (залы) ресторана со схемой столов. Где взять ID: terminalGroupIds → terminal_groups__get_terminal_groups. Троттлинг MCP-сервера (не лимит iikoCloud): не чаще 20 запрос(ов) за 60 с — кэшируйте результат в диалоге.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
requestYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the description is not required to repeat that. It adds valuable behavioral context: the MCP server throttling (20 requests per 60 seconds) and the recommendation to cache results in the dialog. This goes beyond annotations and helps agents plan calls safely.

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?

Three short sentences: purpose, parameter provenance, and throttling advice. The information is front-loaded and every sentence contributes critical operational context. No filler or redundancy.

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

Completeness3/5

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

The description covers the main purpose, points to the ID source, and warns about rate limits, which is good for a read-only tool. However, it does not mention the 'returnSchema' parameter's effect on the output shape (despite the description claiming 'with table layout') and does not describe the response format (no output schema exists). This leaves some ambiguity for an agent about what fields to expect and how to toggle layout information.

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

Parameters2/5

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

Schema description coverage is 0% from the description text, so the description must compensate. It only addresses terminalGroupIds by pointing to the sibling tool for getting the IDs, which adds value. However, it does not explain 'revision' or 'returnSchema' (which controls the table layout output mentioned in the description). The schema's own property descriptions carry that burden, but the description does not fully compensate for the gaps.

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

Purpose4/5

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

The description states the resource clearly: 'Секции (залы) ресторана со схемой столов' (restaurant sections/halls with table layout). Although it lacks an explicit verb, the intent is unambiguous and it distinguishes from generic 'get sections' by mentioning table layout. It is not a tautology and adds specific meaning.

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

Usage Guidelines2/5

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

The description provides a prerequisite pointer for obtaining terminalGroupIds ('Где взять ID: terminalGroupIds → terminal_groups__get_terminal_groups') but does not explain when to choose this tool over alternative banquet tools (e.g., banquets__get_restaurant_sections_workload). No exclusions or alternative comparisons are given. The guidance is about input preparation, not usage context.

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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