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get_listing_issues

Read-only

READ-ONLY. Issue Amazon di SKU SPECIFICI (una chiamata SP-API per SKU): usalo quando l'utente nomina 1-20 SKU. Per la domanda "quali dei miei articoli NON sono in vendita / sono bloccati / soppressi e perché" NON usare questo in loop: usa list_inactive_listings, che copre tutto il catalogo con una chiamata ogni 20 SKU.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
skusNo
account_idNoID dell'outpost Amazon (= un seller su uno specifico marketplace; vedi list_clients). Opzionale se il token è legato a un solo outpost.
issue_localeNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=false, so restating 'READ-ONLY' is redundant. However, the description discloses a genuinely useful trait beyond the annotations: the per-SKU API call cost, contrasting sharply with list_inactive_listings taking one call per 20 SKUs.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three tight clauses, front-loaded with the read-only flag and scope, then the when-to-use and the routing exclusion. Efficient, though the all-caps and dense phrasing make it slightly harder to scan than plain prose.

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?

No output schema exists, so return values need not be described. Given three params at 33% coverage and the absence of annotations detail, the description supplies the key constraints (batch size, execution cost, alternative routing), leaving only issue_locale undocumented.

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 only 33% (only account_id is documented, issue_locale and skus are bare). The description compensates partially by capping the skus batch at 1-20, but it says nothing about issue_locale or account_id, leaving the low-coverage parameters under-explained.

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?

States a specific verb/resource ('Issue Amazon di SKU SPECIFICI') plus the execution model ('una chiamata SP-API per SKU'). It explicitly excludes the sibling it resembles by naming list_inactive_listings, so an agent can disambiguate without opening any schema.

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?

Gives both a positive trigger ('usalo quando l'utente nomina 1-20 SKU') and an explicit negative trigger with the correct alternative ('NON usare questo in loop: usa list_inactive_listings'). The condition that selects each tool is fully specified.

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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