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finwire.pl - Polish financial data

Running costs of a flat

get_housing_costs
Read-onlyIdempotent

Monthly running costs of a flat in 20 largest cities: co-op and owners association charges per m², heating, electricity, gas, water and waste rates, each with year and scope (city or province).

Input Schema

NameRequiredDescriptionDefault
cityNoCity name or slug (e.g. "Kraków" or "krakow") ; omit for the list of cities.

Output Schema

NameRequiredDescriptionDefault
urlYes
asOfNo
dataNo
titleYes
sourceYes
docsUrlYes
licenseYes
summaryYes
citationYes
datasetIdYes
sourceUrlNo
truncatedNo
serverDateYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.5/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint=false and destructiveHint=false, so safety is covered. The description adds useful data context: coverage is limited to the 20 largest cities and each figure carries a year and a city-vs-province scope. It says nothing about pagination, refresh cadence, or data sources.

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?

One dense sentence with no wasted words, and the scope (20 largest cities) plus the enumerated metrics are front-loaded. It is a noun-phrase fragment rather than a sentence with a verb, which is slightly less scannable but not wasteful.

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?

With an output schema, full parameter documentation, and rich annotations, the description only needs to convey what the data represents and its coverage. It does that adequately, though a note on the city-omission behaviour and on sibling tools would make it complete.

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?

There is a single optional parameter at 100% schema description coverage, and the schema already explains the name-or-slug format and that omitting it returns the city list. The description adds nothing about the parameter, which is acceptable given the schema carries it fully.

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?

Names a specific resource (monthly running costs of a flat) and enumerates the cost components (co-op charges, heating, electricity, gas, water, waste), which separates it from get_housing_prices and get_rents by implication. It never explicitly states how it differs from those close siblings, so it falls short of a 5.

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?

The stated scope (20 largest cities, year and scope fields) implies when the tool is appropriate, but there is no explicit when-to-use or when-not guidance. Nothing routes the agent between this tool, get_housing_prices, get_rents, or get_regional_data.

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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