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regdata_knf_registry

Extract payment institutions, e-money issuers, credit intermediaries, lending companies, and pawnbroking operators from 3 Polish KNF registries. Search by name, NIP, or entity type and export 75,000+ entities as structured JSON.

Instructions

Poland KNF Financial Registry Scraper. Extract payment institutions, e-money issuers, credit intermediaries, lending companies & pawnbroking operators from 3 Polish KNF registries. Search by name, NIP, entity type. Bulk export 75,000+ entities. Structured JSON. No auth needed. Pass the registry's search input as a flat object (e.g. name, tax ID, or registration number); call regdata_describe with slug "knf-registry-scraper" first if unsure of the exact fields.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
maxItemsNoOptional cap on billed dataset items returned.
Behavior3/5

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

No annotations provided, so description carries burden. Discloses no auth needed, bulk export, structured JSON, but omits potential side effects (read-only?), rate limits, or error behavior. Adequate but not thorough.

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?

Two well-structured sentences, no wasted words. Front-loaded with purpose and key details (entity types, search fields, bulk export). Meets high bar for conciseness.

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

Completeness4/5

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

Complex tool with 75k+ entities and no output schema, but description covers purpose, search capabilities, and directs to regdata_describe for field details. Lacks output format details but acceptable given the reference.

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

Parameters4/5

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

Schema coverage is 100% but schema is very generic (freeform with additionalProperties). Description adds meaning by specifying typical search fields (name, NIP, entity type) and that maxItems caps billed dataset items. Compensates for schema vagueness.

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

Purpose5/5

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

Description clearly states it scrapes the Polish KNF Financial Registry for specific entity types (payment institutions, e-money issuers, etc.), distinguishing it from other registry tools in the sibling list.

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

Usage Guidelines4/5

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

Provides explicit guidance: pass search input as flat object, and call regdata_describe first if unsure. Lacks explicit when-not-to-use but is clear enough.

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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