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Ua Spend Between

ua_spend_between
Read-onlyIdempotent

Payments from ONE Ukrainian public payer to ONE recipient (both by EDRPOU) in a window of up to 92 days, from State Treasury data on spending.gov.ua (keyless). Returns found true/false, payment count, total UAH, a per-month breakdown, and the payment rows with purpose text and any recorded contract number. found:false means the Treasury published no payment between the two in that window — not proof none was made (some payers, e.g. defence, are withheld). Use to check whether and how much a specific public body paid a specific supplier.

Input Schema

NameRequiredDescriptionDefault
limitNoRows to return, newest first (1-500). Default 100.
date_toNoWindow end, YYYY-MM-DD. Default: today. Window may not exceed 92 days.
date_fromNoWindow start, YYYY-MM-DD. Default: 30 days before date_to.
payer_edrpouYesPayer (spending body) EDRPOU code, e.g. "26510514".
recipient_edrpouYesRecipient (payee) EDRPOU code, e.g. "37988155".

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior5/5

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

Goes well beyond the annotations (readOnly/idempotent/openWorld) by disclosing the data source (State Treasury, spending.gov.ua, keyless) and, critically, the meaning and limits of a negative result — found:false is not proof no payment was made, with defence payers withheld. That caveat is exactly the behavioral context an agent cannot get from structured fields.

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?

Purpose is front-loaded and the sentences are information-dense with little filler. The middle sentence packing source, return fields, and the found:false caveat is long but each clause carries necessary information.

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?

No output schema exists, yet the description fully enumerates the return shape (found flag, payment count, total UAH, per-month breakdown, payment rows with purpose text and contract number). Combined with the negative-result caveat, an agent has everything needed to call and interpret it.

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%, so payer_edrpou, recipient_edrpou, dates and limit are already documented. The description reinforces the one-to-one scoping and the 92-day window cap, but the 92-day limit is already in the date_to schema description, so marginal added value over structured data.

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+scope: payments from ONE Ukrainian public payer to ONE recipient, in a bounded window, from a named source. The directional one-to-one framing clearly distinguishes it from sibling listing tools like ua_spend_payments and ua_spend_prozorro_link.

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?

Ends with explicit when-to-use guidance: 'Use to check whether and how much a specific public body paid a specific supplier.' That is a clear context for invocation, but it never names an alternative tool or states when NOT to use this one, leaving sibling selection to inference.

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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