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regdata_wko_business_directory

Scrape Austrian business records from the WKO directory - no API needed. Get company names, addresses, contact details, industry codes, and trade licenses.

Instructions

Austria WKO Business Directory Scraper. Scrape 620,000+ Austrian businesses from WKO Firmen A-Z - the official Chamber of Commerce directory. Get company names, addresses, phone numbers, emails, websites, industry codes, and trade licenses. No API exists for this data. Pass the registry's search input as a flat object (e.g. name, tax ID, or registration number); call regdata_describe with slug "wko-business-directory-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 are provided, so the description carries the full burden. It states the tool 'scrapes' data, implying a read-only operation, but does not disclose output format, pagination behavior, rate limits, or data freshness. For a scraper, more details on returned data structure would improve transparency.

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?

The description is four sentences with no fluff. The first sentence states the purpose, the second lists data types, the third notes the lack of API, and the fourth gives usage guidance. Information is front-loaded and efficient.

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?

With one optional parameter and no output schema, the description provides sufficient context for understanding the tool's function and how to call it. However, it lacks details on output format, which would be helpful given the absence of an output schema. The recommendation to use regdata_describe compensates partially.

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?

The input schema has one parameter (maxItems) with description. The description adds value by explaining the input is freeform and matching the Apify schema, and gives examples of search fields (name, tax ID). This goes beyond the schema's minimal description, but could still be more precise about accepted query formats.

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?

The description clearly states it is an 'Austria WKO Business Directory Scraper' and specifies exactly what data is scraped (company names, addresses, etc.). It distinguishes this tool from siblings by naming the specific directory (WKO Firmen A-Z).

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?

The description instructs to pass a flat search object (name, tax ID, etc.) and recommends calling regdata_describe first if unsure. This provides clear usage context but does not explicitly contrast with sibling tools or mention when not to use it.

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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