regdata_krz_debtor

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

No annotations are provided, so the description carries full burden. It discloses the 'Pay-per-result' billing model and mentions automation of checks, but does not detail error handling, rate limits, or behavior on no results. This is minimally adequate but lacks depth.

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 description is a single paragraph of five sentences, front-loading purpose and use cases. It is mostly concise, though listing nine modes could be condensed. Every sentence adds value, and the structure is logical.

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 the tool's complexity (many search modes, pay-per-result, freeform input schema), the description covers purpose, input format, guidance to use regdata_describe, and billing. It lacks an example input or output description, but is fairly complete for a scraper tool.

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 100% with only one parameter (maxItems) whose description is already adequate. The description adds 'Pay-per-result' which relates to cost, but does not enhance meaning beyond the schema for maxItems. Baseline 3 is 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?

The description clearly specifies the tool as a scraper for the Poland KRZ National Debtor Registry, used for bankruptcy and restructuring checks. It lists nine search modes and distinct use cases (credit-risk watchlist, insolvency workflow), which effectively distinguishes it from sibling tools targeting different registries.

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 advises calling regdata_describe with a specific slug if unsure of input fields, and instructs to pass search inputs as a flat object. While it lacks explicit when-not-to-use guidance, the context of sibling tools covering different registries makes this clear.

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