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milomymilo

BuchhaltungsButler MCP-Server

by milomymilo

list_postings

Retrieve accounting postings for a customer using optional date range, account, posting status, and modification date filters. Returns up to 1000 postings per call.

Instructions

Ruft Buchungen (Postings) für einen Kunden ab. Pro Aufruf maximal 1000 Buchungen.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
accountNoOptional: Komma-getrennte Liste von Konten (z.B. '1200,1210' oder 'all').
api_keyNoAPI-Key des zu verwaltenden Kunden. Optional, falls BUCHHALTUNGSBUTLER_API_KEY als Umgebungsvariable gesetzt ist.
date_toNoEnddatum im Format YYYY-MM-DD (inklusiv).
date_fromNoStartdatum im Format YYYY-MM-DD (inklusiv).
posting_statusNoOptional: all, fixed oder unfixed.
postingaccountNoOptional: Komma-getrennte Liste von Sachkonten (z.B. '8400,8401' oder 'all').
date_last_action_toNoOptional: Nur Buchungen, die bis zu diesem Datum erstellt/geändert wurden (YYYY-MM-DD).
date_last_action_fromNoOptional: Nur Buchungen, die seit diesem Datum erstellt/geändert wurden (YYYY-MM-DD).
Behavior3/5

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

With no annotations present, the description carries the full transparency burden. It adds value by disclosing the 1000-postings-per-call limit, but it leaves unstated what happens when that limit is reached (truncation, error, pagination), result ordering, and whether the operation is strictly read-only (only implied by 'abrufen').

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 short sentences, front-loaded with the core purpose and followed by a critical constraint. Every sentence earns its place, with no filler or redundancy.

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

Completeness3/5

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

Given the tool has 8 optional parameters and no output schema, the description covers the essential operation and maximum result size. However, it omits guidance on filter combinations, default behavior when no filters are supplied, and the semantics of the 1000-item cap. It is adequate but minimal for a tool with this parameter count.

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%, with each of the 8 parameters having a descriptive comment. The tool description itself adds no parameter-level meaning, so the baseline score of 3 is appropriate: the schema already does the heavy lifting.

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 clearly states the action ('Ruft ... ab') and resource ('Buchungen (Postings) für einen Kunden'), distinguishing it from list_receipts, list_accounts, and other sibling list tools. However, it does not differentiate list_postings from list_transactions, which may be semantically overlapping in accounting contexts.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus the many sibling list tools, nor does it mention prerequisites or ideal use cases. The only usage-related detail is the maximum 1000 postings per call, which is a constraint rather than an applicability guideline.

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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