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Orders: create labels

orders_generate_labels

Generate PDF labels for pickup-point orders. Submit up to 100 order IDs to create a label generation task, then download the file using the returned taskID.

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
orderIDsYesArray of order IDs in the deals service (marketplace), from 1 to 100.
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).
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 — this is safe by design.
Behavior4/5

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

Annotations indicate mutation (readOnlyHint=false). Description adds context on async behavior (taskID, waiting), dryRun safety, and idempotencyKey conflict handling. No contradictions. Could mention rate limits but not required.

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?

Very concise: three sentences cover purpose, constraints, alternatives, and follow-up. Front-loaded with key info. No unnecessary words.

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?

Despite no output schema, description fully explains return value (taskID) and required follow-up step. Covers all necessary context: scope, limitations, and sibling differentiation.

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

Parameters4/5

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

Schema coverage is 100% with detailed descriptions. Tool description reinforces constraints (max 100 orders) and adds behavioral notes (dryRun preview, idempotencyKey duplication protection). Adds value beyond 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?

Description clearly states it creates a task to generate PDF labels for pickup-point orders, with a limit of 100 orders. It distinguishes from sibling tools like orders_generate_labels_extended and orders_download_label.

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?

Explicitly states when to use (pickup-point orders) and when to use alternatives (orders_generate_labels_extended for batches up to 1000, with rate limit warning). Provides clear workflow instructions (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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