match_receipts_to_bank_csv

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

With no annotations, the description takes on full disclosure and does well, warning about best-effort regex extraction, no OCR for scanned images, and the need to review 'unmatched' and 'extractionIssues' lists. It does not detail the output structure, but the key limitations are transparent.

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 sentences, front-loaded with the core action, followed by concise caveats. Every phrase earns its place with no redundancy.

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?

The tool has no output schema or annotations, but the description covers the algorithm, expected inputs, and limitations. It mentions returning 'unmatched' and 'extractionIssues' lists but does not describe the full return shape or the meaning of date-tolerance beyond high level.

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?

Schema coverage is only 33%, so the description must compensate. It adds context about CSV content (date + EUR amount) and matching logic, but it does not explicitly map parameters like dateToleranceDays to its behavior, leaving partial gap.

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 matches receipt PDFs against a bank statement CSV by extracting amount/date and comparing with exact-amount/date-tolerance matching. It is specific about inputs and behavior, though it does not explicitly distinguish itself from sibling tool match_bank_csv_to_vouchers.

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?

No guidance is provided about when to use this tool instead of match_bank_csv_to_vouchers or other siblings. The description explains what it does but lacks exclusions or alternative recommendations.

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