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A1-x-Tech

mcp-yandex-dostavka

Платформа: отменить заказ

platform_cancel_request
Destructive

Cancel a delivery order on the Yandex logistics platform before it reaches the recipient. Returns cancellation status, reason, and error details for unauthorized or missing orders.

Instructions

Отменяет заказ в логистической платформе. Курьерский заказ можно отменить до статуса DELIVERY_TRANSPORTATION_RECIPIENT (передача получателю). Возвращает status (CREATED | SUCCESS | ERROR), reason и description. Ошибки: 403 — чужой заказ/нет прав, 404 — не найден.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
request_idYesid заказа в платформе (из platform_confirm_offer).
Behavior5/5

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

Beyond the annotations (destructiveHint=true, readOnlyHint=false), the description discloses important behavioral context: the cancellation is conditional on order status, it returns specific fields (status, reason, description), and it lists error codes 403 and 404. This provides the agent with actionable expectations not present in the structured data.

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 three concise sentences, each serving a distinct purpose: stating the action, specifying the cancellation scope and return values, and listing error codes. There is no redundancy or excessive detail.

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?

For a single-parameter cancellation tool with annotations covering safety and destructiveness, the description provides all necessary operational context: the cancellation precondition, return shape, and error semantics. Even without an output schema, an agent can correctly invoke and interpret the result.

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

Parameters3/5

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

The single parameter request_id is fully described in the schema (id заказа в платформе (из platform_confirm_offer)), giving 100% coverage. The description adds no additional parameter-level detail, so the baseline score of 3 applies.

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 clearly states the action: 'Отменяет заказ в логистической платформе' (cancels an order in the logistics platform). It also distinguishes from siblings like express_cancel_claim by specifying 'Курьерский заказ' (courier order) and the platform context, making the purpose specific and unambiguous.

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

Usage Guidelines4/5

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

The description provides a clear usage condition: cancellation is possible only up to the status DELIVERY_TRANSPORTATION_RECIPIENT, which tells the agent when this tool is applicable. However, it does not explicitly mention alternatives (e.g., express_cancel_claim for express orders), so it lacks explicit exclusions.

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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