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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
NameRequiredDescriptionDefault
cityYesWillhaben 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_typeYes"mietwohnungen" for apartment rentals, "eigentumswohnung" for apartments for sale.mietwohnungen
max_itemsNoMaximum number of listing rows to return in this run.
max_pagesNoHow many result pages to walk before stopping (30 listings per page).

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds valuable behavioral details: no login/browser/proxies required, and per-call pricing. It does not describe rate limits or output format, but the added access/cost context goes beyond annotations.

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 two short, information-dense sentences. It front-loads the action and source, then adds access and pricing in a compact suffix. Every word earns its place.

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

Completeness3/5

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

With no output schema, the description doesn't explain the shape or fields of the returned listing data. While the source and deal types are clear, and schema covers inputs, an agent may need to infer what each 'listing' contains or how results are paginated.

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?

Schema coverage is 100% with detailed descriptions for all four parameters, including enum titles and city slug caveats. The description only restates 'rental and sale' which already matches the deal_type enum, so it adds no meaningful parameter-level semantics 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 the tool pulls live apartment rental and sale listings from Willhaben.at for Vienna, using a specific verb ('Pull') and exact resource. It distinguishes itself from sibling tools by the portal and city scope.

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 provides clear context: this is for Vienna real estate listings on Willhaben. It does not explicitly mention alternatives or when-not-to-use, but the geographic and portal specificity makes the intended use obvious.

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
Disambiguation3/5

Many tools are distinct by region/source (e.g., otodom-warsaw vs. imovirtual-lisbon), but there are overlapping categories: multiple real estate, job, SEC, and crypto tools. Watchers/alerts (job-alert, re-new-listing-alert, tender-alert) could be confused with their corresponding search tools, and token tools (live-price-oracle, token-launch-radar, rug-pull-scorer) have similar purposes.

Naming Consistency2/5

Names follow no consistent pattern: some are hyphenated source-location (emlakjet-istanbul), some are generic descriptors (job-alert, pricing_info uses underscore), and some are verbose phrases (official-gazette-regulatory-action-router). There is no consistent verb_noun or noun structure, making it hard to predict what a tool does from its name.

Tool Count2/5

With 36 tools, the server is in the 'too many' range (25+). The broad 'Market Data' theme partially justifies the count, but it feels bloated with many single-country listings and overlapping watchers that could be consolidated.

Completeness3/5

The domain is loosely defined as 'market data,' spanning real estate, jobs, tenders, SEC filings, crypto, and clinical trials. While it covers niche areas well, there are notable gaps: no general stock/ETF quotes, no forex/commodities data, and no cross-country aggregate search. The mix of scrapers and alerts leaves the surface feeling uneven.

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