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iikocloud-mcp

iikocloud-mcp

by UserVanya
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

banquets__get_restaurant_sections_workload

Read-only

Check restaurant section workload for a date range to manage reservations and capacity. Input start date and section IDs; optional end date.

Instructions

Загруженность секций ресторана с указанной даты. Троттлинг MCP-сервера (не лимит iikoCloud): не чаще 20 запрос(ов) за 60 с — кэшируйте результат в диалоге.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "request": "<request>"
    },
    "name": "banquets__get_restaurant_sections_workload"
  }
}

Input Schema

NameRequiredDescriptionDefault
requestYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.2/5.0
Behavior4/5

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

The description discloses a key behavioral trait: the MCP-server throttling limit (no more than 20 requests per 60 seconds) and advises caching the result. This goes beyond the annotations (readOnlyHint, destructiveHint) by adding operational constraints. It does not contradict the annotations; readOnlyHint aligns with the read-only nature implied. The description could also mention what happens if the limit is exceeded, but the current disclosure is valuable and specific.

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 extremely concise, consisting of two short sentences. It front-loads the primary purpose and immediately adds the critical throttling constraint, which is essential for proper usage. There is no redundant or filler content; every word contributes to the tool's understanding. This is a model of efficiency for a tool description.

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

Completeness2/5

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

The tool is a read-only query with no output schema, so the description should explain what the returned workload data looks like or how to interpret it. It does not. It also omits any explanation of the parameters beyond the schema's own descriptions, and it does not clarify the meaning of 'workload' (e.g., occupancy, reservations count, capacity). Given that the tool has multiple parameters and no output schema, the description is insufficient for an agent to call it correctly without external knowledge.

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?

The schema description coverage is 0% — the tool description provides no explanation of the parameters (dateFrom, dateTo, restaurantSectionIds). While the input schema itself contains descriptions for each parameter, the description does not compensate for the low coverage. It adds no extra meaning about parameter formats, defaults, or how they relate to the workload query. The description's mention of 'from the specified date' loosely refers to dateFrom but does not clarify dateTo or the ID collection.

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 tool's purpose clearly: 'Загруженность секций ресторана с указанной даты' (Restaurant sections workload from the specified date). It identifies the resource (restaurant sections) and the action (retrieve workload), which distinguishes it from sibling tools like banquets__get_reserve_restaurant_sections (which deals with availability, not workload). However, it does not explicitly name the verb 'get', though the tool name implies it, and it lacks a direct statement of what the returned data represents beyond 'workload'.

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 no guidance on when to use this tool versus alternatives. It does not mention any sibling tools or conditions that would make this the appropriate choice. It only offers operational advice (throttling and caching), not usage context. This is a significant gap, as the agent must infer the tool's place among many related banquet and reservation tools.

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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