match_bank_csv_to_vouchers

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

With no annotations, the description fully discloses key behaviors: it fetches the voucher list itself (paginated, date-range padded), matches by exact amount and tolerance, and highlights the /voucherlist endpoint's traversal limit. This goes beyond a simple 'matches transactions' and gives valuable operational details.

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

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

Two dense sentences convey the entire purpose without filler. The first sentence front-loads the primary function, and the second adds crucial edge-case behavior. Every sentence earns its place.

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

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

Given no annotations and no output schema, the description covers the input format, matching logic, self-fetching behavior, pagination, and the 10,000-entry limit with a mitigation strategy. It does not explicitly state the output format, but for a matching tool this is a minor gap.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema already describes voucherType, voucherStatus, and csvContent (75% coverage). The description adds meaning beyond the schema by specifying that csvContent must contain date and EUR amount columns, and clarifies the date-tolerance window concept. Some parameter details are still left to the reader.

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

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

The description clearly states the tool parses a bank statement CSV and matches transactions against Lexware vouchers using exact amount and date-tolerance criteria. It distinguishes from siblings like match_receipts_to_bank_csv by specifying the bank CSV + voucher matching focus.

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

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

It provides practical guidance on narrowing voucherType/voucherStatus for specific categories and warns about the 10,000-entry limit with a split-by-date-range workaround. However, it does not explicitly name alternative tools or state when not to use this tool, so it falls short of a 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.