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Ręczniki Haftowane

get_shop_policies

Read-onlyIdempotent

Zasady sklepu: waluta PLN, metody i ceny dostawy, próg darmowej dostawy, termin realizacji z dostawą i opis materiału. Kwoty: *_minor (grosze), *_formatted (PLN); null gdy brak danych. Narzędzie nie przyjmuje parametrów. Pusty katalog daje not_found, niedostępność sklepu shop_unavailable.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_shop_policies"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault
errorNoTylko przy isError: { code, message, ... }
currencyNo
deliveryNo
lead_timeNoTermin realizacji wraz z czasem dostawy; null gdy brak
materialsNoOpis materiału ze szczegółów produktu; null gdy brak

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint=false and destructiveHint=false, so the safety profile is covered. The description adds useful behavioral detail: amount fields come as *_minor (grosz) and *_formatted (PLN), null appears when data is missing, and specific error cases are named. This is solid extra context, though it does not discuss auth, rate limits, or response shape beyond output schema.

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 front-loaded with the resource purpose, then compactly covers amount formats and error codes. Every sentence adds operational value; nothing is wasted.

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?

With an output schema present, the description needn't explain return structures, and annotations already cover safety and idempotence. The description fills the remaining gaps by confirming parameterlessness, documenting amount semantics, and naming error outcomes, so it is complete for an agent to invoke correctly.

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?

The tool has zero parameters, so the schema baseline is 4. The description explicitly confirms 'Narzędzie nie przyjmuje parametrów', consistent with the empty input 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 names a specific resource ('Zasady sklepu') and enumerates exactly what it returns: currency, delivery methods and prices, free-delivery threshold, fulfillment time, and material description. This distinguishes it clearly from product/design sibling tools such as search_products or list_designs.

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?

It gives clear context for use: this is the shop-policy resource, it takes no parameters, and it defines error outcomes (not_found for an empty catalog, shop_unavailable for a closed shop). It does not explicitly name when to prefer or avoid it versus siblings, but for a no-param static resource fetch the usage context is unambiguous.

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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