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regdata_wko_business_directory

Scrape Austria's WKO business directory to get company names, addresses, phones, emails, websites, industry codes, and trade licenses. Access 620,000+ businesses with no API needed.

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. Advanced fields beyond this schema are also accepted (regdata_describe lists them).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bezirkNoOptional district filter, e.g. 'Linz-Land', 'Hallein', 'Moedling'. For Vienna use a district name or its number ('Innere Stadt', 'Landstrasse', or '3'). Needs a searchQuery alongside it - a district on its own returns nothing. Replaces the Bundesland filter rather than adding to it.
brancheNoIndustry or trade classification to search for (e.g., 'IT-Dienstleistung', 'Gastronomie', 'Tischlerei', 'Elektrotechnik'). Synonym of searchQuery and used as the primary search term on firmen.wko.at - set either one, not both.
maxItemsNoOptional cap on billed dataset items returned.
bundeslandNoAustrian federal state to filter results. Leave empty for all of Austria.
maxResultsNoMaximum number of company records to return. The actor pages through the directory until it reaches this limit or runs out of matches. Default: 100.
searchQueryNoKeyword search for company name or service (e.g., 'Software', 'Gastronomie', 'Steuerberater'). Supply this OR bundesland at minimum - 'branche' is an accepted synonym, so filling either one is enough.
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 describes the tool as a scraper, indicates it makes multiple requests via paging, and notes that advanced fields are accepted via regdata_describe. However, it doesn't disclose rate limits, billing implications (despite mentioning 'billed dataset items'), or idempotency, leaving gaps for an agent.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

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

The description is concise with a clear introductory sentence, followed by details on what is scraped and notes about advanced fields. Parameter descriptions are detailed. Slightly could be improved with more structured formatting, but overall 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?

Given no output schema, the description explains what data is returned (names, addresses, etc.) and refers to regdata_describe for advanced fields. It covers all 6 parameters with descriptions. However, it does not describe the response format or error handling, which would be helpful for a scraper tool.

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

Parameters5/5

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

Schema coverage is 100%, yet the description adds significant value by explaining relationships between parameters (e.g., bezirk needs searchQuery, branche synonym), providing examples, and describing paging behavior for maxResults. This goes well beyond the schema.

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 a scraper for Austrian businesses from the official WKO directory, listing the data fields obtained. It distinguishes itself from sibling tools by specifying the country and source, making it easy for an agent to select the correct tool for Austrian business data.

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 implies usage for Austrian business data and mentions that no API exists, indicating necessity. It provides specific guidance on parameter usage (e.g., bezirk needs searchQuery, branche synonym). However, it lacks explicit when-to-use vs. alternative tools or exclusions, though the context makes it clear.

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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