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Orders: create labels

orders_generate_labels

Generate PDF labels for up to 100 pickup-point orders by submitting order IDs; returns a taskID for later download.

Instructions

Creates a task to generate PDF labels for orders (generate_labels, up to 100 orders at a time). Available only for pickup-point orders. Returns a taskID; wait for it to be ready and download the file via orders_download_label. For large batches (up to 1000 orders) use orders_generate_labels_extended — it has a higher limit but a strict rate limit (1 request/min).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
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).
orderIDsYesArray of order IDs in the deals service (marketplace), from 1 to 100.
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.
Behavior4/5

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

Discloses asynchronous nature (returns taskID), scope (pickup-point only), and relationship to other tools. Annotations provide some context (openWorldHint=true), description adds further behavioral details.

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 sentences with front-loaded main purpose, followed by constraints and alternatives. No redundant information.

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 3 params, no output schema, and annotations, the description fully covers what the tool does, constraints, and usage flow. Complete for agent decision-making.

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 coverage is 100%, so description does not need to add much. It doesn't provide additional semantics beyond 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?

Clearly states it creates a task to generate PDF labels for orders, with specific constraints (up to 100, pickup-point only). Distinguishes from sibling tool orders_generate_labels_extended.

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?

Provides explicit when-to-use: indicates alternative for larger batches (orders_generate_labels_extended) and describes post-invocation steps (wait for task, download via orders_download_label).

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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