finwire.pl - Polish financial data

Retail prices in shops (GUS)

get_retail_prices

Read-onlyIdempotent

Average retail prices of 30 goods and services in Poland from GUS (bread, butter, milk, eggs, meat, vegetables, sugar, electricity, gas, heating, petrol, diesel, bus ticket, taxi, haircut, doctor visit, cinema) for the latest month, with change vs the previous month and the same month a year earlier and the minutes of work each costs at the average net wage; plus the finwire shopping basket of 10 staple foods (finwire_shopping_basket_index).

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_retail_prices"
  }
}

Input Schema

Name	Required	Description	Default
`product`	No	Product name in Polish, e.g. "masło", "chleb", "benzyna"; returns that item with its monthly price history. Omit for all items.

Output Schema

Name	Required	Description	Default
`url`	Yes
`asOf`	No
`data`	No
`title`	Yes
`source`	Yes
`docsUrl`	Yes
`license`	Yes
`summary`	Yes
`citation`	Yes
`datasetId`	Yes
`sourceUrl`	No
`truncated`	No
`serverDate`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

AddedNov 2, 2026

TDQS

A3.6/5.0

Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive, closed-world, so the safety profile is covered. The description adds genuine substance beyond that: the exact measure set (change vs previous month and same month a year earlier), the wage-normalized 'minutes of work' derivation, and the inclusion of a shopping-basket sub-index — things an agent could not infer from the annotations or schema.

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

Conciseness3/5

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

The core claim is front-loaded, which is good, but the whole definition is a single run-on sentence with an 18-item parenthetical that is not exhaustive of the stated 30 goods and duplicates information the schema covers. Trimming the list would sharpen it without losing meaning.

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?

An output schema exists, so return values need no explanation, and the description covers scope, measures, and the basket sub-index. The only soft gap is the time dimension — 'latest month' versus the per-product monthly history is left to the schema rather than stated here.

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% and the sole parameter is fully documented (Polish names, examples, omit-for-all behavior, history semantics), so the baseline is 3. The description's enumerated goods list loosely hints at valid values but conflates English list entries with the Polish inputs the schema actually requires, adding little.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific resource (average retail prices of 30 goods/services in Poland from GUS) and enumerates the derived measures: MoM change, YoY change, work-minutes at average net wage, plus the finwire shopping basket. It is clearly a prices dataset tool, but it never distinguishes itself from overlapping siblings such as get_fuel_prices, get_energy_prices, or get_housing_costs, whose domains appear inside its own item list.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage is only implied: 'for the latest month' plus the schema note that supplying a product returns that item's monthly history. There is no explicit statement of when to choose this over get_fuel_prices/get_energy_prices despite the topical overlap, and no preconditions or exclusions are given.

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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