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Delivery: change parcel [sandbox v1]

delivery_v1_change_parcel

Queue a request to change a test parcel's receiver, prohibit receive/acceptance, or extend storage. Poll for the outcome.

Instructions

[SANDBOX v1] Creates a request to change ONE test parcel's data (e.g. the receiver's name/phone), per the type enum (changeReceiver / prohibitParcelReceive / extendParcelStorage / prohibitParcelAcceptance). The call only QUEUES the request — poll delivery_v1_get_change_parcel_info for the outcome. For bulk changes use delivery_change_parcels instead. Sandbox-only, for delivery-service PARTNERS.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeYesRequest type.
dryRunNov0.7.0: if true — returns a preview of the HTTP request without calling the Avito API. Safe for inspecting exactly what would be done. Default: the value of AVITO_MCP_DRY_RUN_DEFAULT (usually false).
optionsNoAdditional request options (optional).
parcelIDYesIdentifier of the test parcel to change.
applicationNoReceiver change data (optional).
idempotencyKeyNov0.7.0: optional key for duplicate protection. A repeat call with the same key within AVITO_MCP_IDEMPOTENCY_TTL_SEC returns the cached result. The same key with different args returns a conflict error. Keys are stored as bounded SHA-256 fingerprints.
Behavior5/5

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

Annotations provide readOnlyHint=false and openWorldHint=true but the description adds critical async behavior: 'The call only QUEUES the request — poll delivery_v1_get_change_parcel_info for the outcome.' This is beyond what annotations convey. No contradictions.

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?

Two sentences with no wasted words. The first sentence covers purpose and type, the second covers async behavior and sibling alternative. Front-loaded with essential information.

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

Completeness4/5

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

For a sandbox-only tool with no output schema, the description covers key aspects: purpose, async nature, polling, bulk alternative, and sandbox restriction. It could mention potential error responses or success indicators, but overall it is sufficient for correct usage.

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?

Schema description coverage is 100%, so baseline is 3. The description mentions the type enum values and the async polling concept but does not add significant meaning beyond the schema for individual parameters. The parameter details are already well-documented in the schema.

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 verb ('Creates a request to change') and resource ('ONE test parcel's data'), specifies the type enum values, and distinguishes from siblings by noting 'For bulk changes use delivery_change_parcels instead.' It also clarifies it's sandbox-only and for partners.

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 tells when to use this tool (to change one parcel) and explicitly advises using delivery_change_parcels for bulk changes. It lacks explicit prerequisites or conditions when not to use, but the sibling differentiation is clear.

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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