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milomymilo

BuchhaltungsButler MCP-Server

by milomymilo

list_transactions

Retrieve bank transactions for a customer, filtering by account, date range, amount, or counterparty to get exactly the financial records you need.

Instructions

Ruft Banktransaktionen für einen Kunden ab. Kann nach Konto, Zeitraum, Betrag und Gegenpartei gefiltert werden.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximale Anzahl Ergebnisse (1-500).
orderNoOptional: Sortierung als Objekt.
offsetNoOffset für Paginierung.
accountNoOptional: Kontonummer des Zahlungskontos.
api_keyNoAPI-Key des zu verwaltenden Kunden. Optional, falls BUCHHALTUNGSBUTLER_API_KEY als Umgebungsvariable gesetzt ist.
date_toNoEnddatum im Format YYYY-MM-DD (inklusiv).
purposeNoOptional: Verwendungszweck filtern.
to_fromNoOptional: Auftraggeber/Empfänger filtern.
amount_toNoOptional: Höchstbetrag.
date_fromNoStartdatum im Format YYYY-MM-DD (inklusiv).
amount_fromNoOptional: Mindestbetrag.
Behavior2/5

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

No annotations are provided, so the description carries the full burden for behavioral disclosure. It mentions retrieving transactions but does not clarify that this is a read-only operation, does not mention pagination behavior beyond schema, nor any side effects. There is no mention of authentication requirements or data scope, leaving the agent to infer safety.

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 two concise sentences, front-loaded with the verb and resource. It efficiently communicates the core function and filtering options without any redundant or verbose language.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite having 11 parameters and no output schema, the description offers minimal guidance on expected results, pagination handling, or return structure. It does not explain how filters combine or what response format to expect, making it incomplete for agents needing to understand the tool's full behavior.

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 100%, so the baseline is 3. The description adds a summary of filter dimensions (account, time period, amount, counterparty) that maps loosely to the schema parameters, but it does not provide additional semantic meaning beyond what the schema already conveys.

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 clearly states the action ('Ruft ab' - retrieves) and the resource ('Banktransaktionen' - bank transactions) for a customer. It also highlights key filtering capabilities (account, time period, amount, counterparty), which distinguishes it from sibling tools like list_receipts or list_accounts.

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 description implies a listing use case for transactions but does not explicitly state when to prefer this tool over alternatives like get_transaction (single) or create_transaction. It lacks explicit exclusion criteria or conditions, though the filtering context is useful.

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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