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

With no annotations, the description carries the full burden and does so richly: it discloses GDPR-driven data masking (address reduced to town, accounts reduced to count, no REGON/registration date/PKD, ceidg always null), the privacy field that reports hidden data, and same-day caching semantics (mfCached, bl.mfRequestDateTime). This is exactly the behavioral context an agent needs and 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.

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

The core purpose is front-loaded in the opening clause, followed by the caveats in a logical order. It is a dense paragraph, but nearly every clause carries information the agent needs; minor tightening is possible.

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?

With no output schema and no annotations, the description compensates by naming the relevant response fields (ceidg, privacy, mfCached, bl.mfRequestDateTime) and explaining what is and is not returned. For a single-parameter lookup this is complete.

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 description coverage is 100% and there is a single required parameter, so the schema already documents 'nip' fully. The description adds no format or syntax detail beyond it, which makes the baseline 3 appropriate.

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?

States a specific verb and resource: 'Check VAT status (VAT White List / Biała Lista) and KRS data for a Polish company by NIP.' It even routes account-level needs to sprawdz_rachunek. However, it does not distinguish itself from the sibling sprawdz_lista_nip, which also concerns the White List, so an agent may struggle to choose between the two.

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?

The description clearly explains the context in which output is limited (entities without a KRS number) and points to sprawdz_rachunek when a specific bank account must be verified. It lacks an explicit 'use this vs sprawdz_lista_nip/sprawdz_regon' rule, which leaves some ambiguity given the overlapping siblings.

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