Market and Regulatory Data Feeds — Zinin M2M Hub

Willhaben Vienna Real Estate Listings

willhaben-vienna

Read-only

Pull live apartment rental and sale listings straight from Willhaben.at — Austria's biggest classifieds portal — for Vienna. No login, no browser, no proxies. — $0.02/call, x402 (USDC on base).

Input Schema

TableJSON Schema

Name	Required	Description	Default
`city`	Yes	Willhaben city/region URL slug. Only "wien" (Vienna) is verified to work reliably with this Actor's path shape — other slugs may 404 even for real Austrian cities (willhaben structures some regions' URLs differently).	wien
`deal_type`	Yes	"mietwohnungen" for apartment rentals, "eigentumswohnung" for apartments for sale.	mietwohnungen
`max_items`	No	Maximum number of listing rows to return in this run.
`max_pages`	No	How many result pages to walk before stopping (30 listings per page).

TDQS

A4.2/5.0

Behavior4/5

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

Annotations mark this read-only, and the description adds that it requires 'No login, no browser, no proxies' and costs '$0.02/call', which are operational behaviors not captured by annotations. However, it does not mention rate limits or error conditions.

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?

Single sentence with no filler. It front-loads the action and includes only additional operational facts (no login, no browser, cost).

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?

For a simple query tool with no output schema, the description explains the input and the high-level output (listings) but doesn't specify the exact fields returned. Given the well-documented input schema, this is adequately complete, though it could mention output structure.

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

Parameters3/5

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

The input schema has detailed descriptions for all four parameters (100% coverage), so the description adds little beyond mentioning 'rental and sale' which maps to deal_type and 'Vienna' to city. The baseline of 3 is appropriate.

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 uses specific verb 'Pull' to state it retrieves live apartment rental and sale listings from Willhaben.at for Vienna. It identifies the source portal (Willhaben.at) and city (Vienna), distinguishing it from other real estate listing tools.

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?

Description clearly scopes usage to Vienna real estate on Willhaben, but it does not mention when not to use it or name alternative tools. It gives context such as 'for Vienna' and 'Austria's biggest classifieds portal', but there are no explicit exclusions.

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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TDQS

B3.4/5.0

Disambiguation2/5

Many tools have overlapping purposes, with over a dozen real-estate scrapers and half a dozen job boards differentiated only by geography. While descriptions are clear, an agent would struggle to pick the correct tool without prior knowledge of the specific site or region, leading to frequent misselection.

Naming Consistency2/5

Tool names use a mix of lowercase-hyphenated (boss-az, clinical-trials-monitor), underscore (pricing_info), and long descriptive phrases (official-gazette-regulatory-action-router). No consistent verb_noun pattern exists; some start with source domains, others with action nouns. This lack of predictability makes navigation confusing.

Tool Count3/5

36 tools is on the heavy side for a server that could have been more focused. While a 'data hub' can justify many endpoints, the high number of near-identical scrapers (12+ real estate, 6+ job boards) suggests bloat rather than well-scoped functionality. A leaner set with parameterized regional filters would be more appropriate.

Completeness2/5

The claimed domain 'Market and Regulatory Data Feeds' is poorly served: there are no stock/forex/commodity price feeds, few global regulatory sources (only FDA, SEC, EU tenders), and many tools are for job and property listings which are tangential. The set feels like a random aggregation rather than a coherent surface, with obvious gaps for core market and regulatory data.

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