# Germany Visa-Sponsored Jobs (`cg_nguyen/germany-visa-jobs`) Actor Find Germany jobs that sponsor work visas (Blue Card, Skilled Worker, ICT). Pulls the federal Bundesagentur Jobboerse, enriches with full descriptions, classifies visa-sponsorship likelihood (regex + opt-in LLM tie-breaker), and dedupes across runs. For relocation services and intl. job seekers. - **URL**: https://apify.com/cg\_nguyen/germany-visa-jobs.md - **Developed by:** [CG Nguyễn](https://apify.com/cg_nguyen) (community) - **Categories:** Jobs, Automation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $5.00 / 1,000 enriched job results This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## germany-visa-jobs — German jobs that actually sponsor work visas, as a JSON feed > **The Bundesagentur federal job board, filtered for visa sponsorship.** For relocation consultants, expat engineers, and AI agents who can't ask candidates "but will they sponsor?" one more time. Searches Germany's federal job board (Bundesagentur für Arbeit Jobboerse, ~1.6M live listings) and emits structured JSON with a **visa-sponsorship classifier** stamped on every row: `confirmed | likely | unlikely | unknown`. Pay-per-result. --- ### Why this exists The federal Bundesagentur board has every German job opening worth looking at — but it has no "sponsors visa" filter, no salary band, and no English search. So every Tier-3 country candidate, every relocation consultant, every AI job-search agent ends up doing the same thing: fetch a listing, eyeball the description for "visa sponsorship" / "Aufenthaltstitel" / "Blue Card", repeat 200 times. This actor closes that gap. One API call, structured JSON, visa status pre-classified. It is **not** a job board. There's no UI. You bring the automation; we bring the typed, deduplicated, classified data. --- ### Who it's for | Persona | Use case | |---|---| | **Relocation consultancy** | Daily pull of `confirmed` + `likely` Berlin SWE roles into a Notion DB. Replace ~3 hrs/week per junior consultant. | | **Expat job-mover** | Pipe new `confirmed`-status Blue Card roles for your stack into a personal Telegram bot. Apply within hours of listing. | | **AI job-search agent (MCP)** | Apify Actors are auto-exposed as MCP tools. Claude / / Codex agents call this when a user asks about visa-sponsoring German jobs. Zero integration work. | | **Recruitment SaaS** | Source side of a visa-aware ATS. License via Apify Enterprise. | | **Researcher / labour-market analyst** | Time-series of sponsorship signals across regions and professions. The federal API doesn't expose this — we synthesize it. | --- ### The moat: visa-sponsorship classifier Every dataset row carries a `visaStatus` plus the evidence we used to label it. | `visaStatus` | What it means | How we decide | |---|---|---| | `confirmed` | Multiple hard-positive sponsorship phrases. Apply with confidence. | ≥2 hard-positive signals AND no hard-negatives | | `likely` | One explicit sponsorship phrase ("visa sponsorship", "Blue Card", "relocation support", "Aufenthaltstitel"). | ≥1 hard-positive AND no hard-negatives | | `unlikely` | Hard-negative phrase or known citizenship-restricted employer (e.g. BWI GmbH = Bundeswehr IT). | ≥1 hard-negative | | `unknown` | Description doesn't mention visa either way. Default majority. | Neither side fires | **Reality check from production runs:** ~93% of German listings fall to `unknown` because most employers simply don't state sponsorship in text. This is the actual market signal, not a bug. For agencies who only want safe bets, filter to `confirmed + likely`. For aggressive sourcers, filter to `confirmed + likely + unknown` and assume "unknown = ask the recruiter." Optional **LLM tie-breaker** (`useLlmTiebreaker: true`) escalates the bottom 30% of ambiguous cases to Claude Haiku 4.5 for a final read. Costs $0.001 per escalation, capped at a configurable fraction of the run. Default off. --- ### Output — real, unredacted One verified dataset row from a Berlin "visa sponsorship" search: ```json { "refnr": "15170-448146640-S", "title": "Quality Engineer (f/m/d) Investment Castings", "employer": "Siemens Energy Global GmbH & Co. KG", "profession": "Ingenieur/in - Maschinenbau", "city": "Berlin", "postalCode": "13629", "region": "BERLIN", "country": "DEUTSCHLAND", "fullTime": true, "isStaffingAgency": false, "url": "https://www.arbeitsagentur.de/jobsuche/jobdetail/15170-448146640-S", "visaStatus": "likely", "visaClassifier": "regex-v1", "visaReason": "1 hard-positive: visa sponsorship", "visaSignals": { "hardPositive": ["visa sponsorship"], "hardNegative": [], "soft": ["global organization"] }, "descriptionPreview": "A Snapshot of Your Day — This position combines Project, Quality, and Supplier Management...", "fetchedAt": "2026-05-17T11:19:45.990Z" } ```` And a hard-negative example (correctly filtered as `unlikely`): ```json { "title": "Software Engineer Full Stack (m/w/d)", "employer": "BWI GmbH", "city": "München", "visaStatus": "unlikely", "visaReason": "Hard-negative signal(s): BWI GmbH (Bundeswehr IT — citizenship typically required)", "visaSignals": { "hardPositive": [], "hardNegative": ["BWI GmbH (Bundeswehr IT — citizenship typically required)"], "soft": ["remote / mobile work"] } } ``` Full field list: `refnr, title, employer, profession, city, postalCode, region, country, coordinates, salaryFromEUR, salaryToEUR, salaryKind, salaryRange, fullTime, partTime, shiftWork, isStaffingAgency, isPrivatePlacement, employerHomepage, publishedAt, modifiedAt, description, descriptionPreview, descriptionLength, allLocations, url, visaStatus, visaClassifier, visaReason, visaSignals, fetchedAt`. Three dataset views are exposed (`overview`, `confirmed-only`, `full-details`) — pick from the Apify console. *** ### Input Full schema with descriptions: see the **Input** tab in the Apify console. | Field | Type | Default | Notes | |---|---|---|---| | `searchTerm` | `string` | **required** | Role keyword, EN or DE. E.g. `"Software Engineer"`, `"Data Scientist"`, `"Pflegefachkraft"`. | | `location` | `string` | `""` | German city or postal area. Empty = all Germany. | | `radiusKm` | `integer` | `25` | Search radius around `location`. | | `salaryMinEUR` | `integer` | `0` | Minimum yearly salary filter (federal API field). | | `remoteAllowed` | `boolean` | `false` | Filter to remote-allowed listings only. | | `publishedDaysAgo` | `integer` | `7` | Skip listings older than N days. | | `offerTypes` | `array` | `["1"]` | `1`=permanent, `2`=temp, `4`=apprenticeship, etc. | | `includeTemporaryAgency` | `boolean` | `false` | Include staffing agencies (often visa-unfriendly). | | `visaStatusFilter` | `array` | `["confirmed","likely","unknown"]` | Drop everything else from the dataset. | | `useLlmTiebreaker` | `boolean` | `false` | Escalate ambiguous cases to Claude Haiku 4.5. Requires `anthropicApiKey`. | | `anthropicApiKey` | `string` (secret) | `""` | Your Anthropic API key. Only needed if tie-breaker is on. | | `llmTiebreakerMaxFraction` | `number` | `0.3` | Cap LLM calls at this fraction of the run. | | `dedupAcrossRuns` | `boolean` | `true` | Persistent KV store of seen `refnr`s; skip on repeat. | | `dedupHorizonDays` | `integer` | `7` | Prune dedup cache entries older than N days. | | `maxResults` | `integer` | `100` | Hard cap per run. | | `includeRawDescription` | `boolean` | `false` | Emit full description in addition to the preview. | *** ### Pricing — Pay Per Event | Event | Price | Fires when | |---|---|---| | `actor-start-gb` | **$0.00005 / GB** | At run start. First 5 seconds waived. | | `enriched-result` | **$0.005** | A job that passes classifier + filter + dedup and lands in the dataset. | | `llm-tiebreaker-call` | **$0.001** | One Anthropic Haiku 4.5 escalation. Only if `useLlmTiebreaker: true`. | **≈ $5 per 1,000 enriched results.** You pay for results, not for cycles. Repeated runs skip already-seen jobs and cost nothing. | You are... | Cadence | Enriched/mo | Monthly cost | |---|---|---|---| | Solo job-mover (one role, one city) | Daily | ~150 | **~$0.75** | | Active consultancy (5 roles × Berlin/Munich/Hamburg) | Daily | ~1,500 | **~$7.50** | | Recruitment SaaS (50 client searches) | Daily | ~15,000 | **~$75** | *** ### How it stays clean - **Federal API direct** — `bundesagentur-jobsuche` upstream, no scraping fragile HTML, no Cloudflare challenges, no proxy needed. - **Deduplication across runs** — refnrs persisted in an Apify KV store. Poll daily without paying twice for the same job. - **Stale-prune** — refnr cache older than 7 days (configurable) is dropped to keep the store light. - **Classifier transparency** — every row exposes `visaReason` + `visaSignals`. You can override our judgement; we don't hide the evidence. - **Cost ceiling** — LLM tie-breaker is opt-in and capped at a fraction of the run. Worst-case cost is bounded before you press Start. *** ### Limits & legal - Reads only the **public** Bundesagentur Jobboerse API via client `jobboerse-jobsuche` (no OAuth, no scraping). De-facto public, no formal commercial-use restriction documented — verify before running at scale. - The visa classifier is heuristic, not legal advice. `confirmed` does not guarantee sponsorship will be offered; `unlikely` does not guarantee it won't. Always confirm with the employer. - We don't store personal data beyond what the federal API itself publishes. *** ### Frequently asked **Q: Why not just grep "visa sponsorship" yourself?** You can. But the federal API only returns 25 listings per page, requires base64 keys for detail fetches, has German-only category codes, and returns no sponsorship signal of its own. Doing this once is fine. Doing it on a cadence for 5 roles across 3 cities is a part-time job. **Q: What's the false-positive rate on `confirmed`?** The classifier is rule-based and conservative: `confirmed` requires multiple hard-positive phrases AND no hard-negatives, so false positives are rare in practice (we have not yet published a hand-graded benchmark). False negatives in `unknown` are the dominant error class — most German employers simply don't state sponsorship policy in text. The LLM tie-breaker is the lever for catching those. **Q: Can I add my own classifier rules?** Not in v0.2. Patch list / employer hard-negatives are coming in v0.3 — open a request via the Apify console issues tab. **Q: Is there an MCP endpoint?** Yes — automatically. Every Apify Actor with an input schema is exposed as an MCP tool. Point your Claude / / Codex client at the Apify MCP and this actor appears as `germany-visa-jobs`. **Q: Why "pay-per-event" and not subscription?** Because most users only need a few hundred fresh listings per month. PPE means you pay for results, not for cycles. Sleeping users cost nothing. *** ### Roadmap - **v0.2** *(current)* — federal API, regex-v1 classifier, optional Haiku 4.5 tie-breaker, persistent dedup. - **v0.3** — user-supplied hard-negative employer patches; per-row salary inference from text; German-language `Aufenthaltstitel` / `Blaue Karte` synonym set. - **v0.4** — Stepstone + LinkedIn Jobs sibling actor wired into the same classifier. - **v1.0** — calibrated probability output instead of bucket labels. *** ### Sister actor Need somewhere to live in the same city? [`cg_nguyen/wg-gesucht-de`](https://apify.com/cg_nguyen/wg-gesucht-de) emits new WG-Zimmer listings minutes after they're posted. Same author, same pricing model. *** ### Author Built by [@cg\_nguyen](https://apify.com/cg_nguyen). Senior Backend Engineer at SOA (Source of Asia), Hanoi. Working with European clients; lived the Tier-3 visa search myself. Bugs and feature requests via the Apify console issues tab. # Actor input Schema ## `searchTerm` (type: `string`): Free-text search on job title. Example: 'software engineer', 'data scientist', 'pflegefachkraft'. ## `location` (type: `string`): City, postal code, or state in Germany. Leave empty for nationwide search. ## `radiusKm` (type: `integer`): Only applied when location is set. Defaults to 25 km on the federal API. ## `salaryMinEUR` (type: `integer`): Hard filter — drops jobs whose advertised upper salary is below this. 0 means no filter. ## `remoteAllowed` (type: `boolean`): Soft filter — currently keyword-based on the description ('remote', 'homeoffice', 'mobile working'). Improves Day 2 with the classifier. ## `publishedDaysAgo` (type: `integer`): 0 = no time filter. Federal API caps at 100. ## `offerTypes` (type: `array`): 1 = Job, 2 = Self-employment, 4 = Training/Dual studies, 34 = Internship/Trainee. ## `includeTemporaryAgency` (type: `boolean`): Off by default — staffing-agency listings are usually thin (no description, no salary, often re-postings). Set true to include them anyway. ## `maxResults` (type: `integer`): Hard cap on jobs fetched + detail-enriched. Each result fires one PPE event. ## `includeRawDescription` (type: `boolean`): If false (default), output keeps the first 500 characters of the description. Set true for downstream NLP. ## `visaStatusFilter` (type: `array`): Only emit jobs whose classifier verdict matches one of these. Default: confirmed + likely + unknown (drops only explicit no-sponsorship). Set to \['confirmed'] for the strictest list. ## `useLlmTiebreaker` (type: `boolean`): Escalate 'unknown' verdicts to Claude Haiku for a final classification. Requires an Anthropic API key below. Rate-limited per run by llmTiebreakerMaxFraction. ## `anthropicApiKey` (type: `string`): Optional, only used when 'useLlmTiebreaker' is on. Format: sk-ant-…. Stored as a per-run secret — not retained on the actor. ## `llmTiebreakerMaxFraction` (type: `integer`): Hard cap on tie-breaker calls per run as a percentage of fetched jobs (0–100). Default 30. Prevents runaway cost on ambiguous result sets. ## `dedupAcrossRuns` (type: `boolean`): On by default. The Bundesagentur API surfaces the same listing for ~14 days, so daily runs would otherwise emit massive duplicates. We cache emitted refnrs in the actor's key-value store and skip them on subsequent runs. Turn this off if you want every run to be a full snapshot. ## `dedupHorizonDays` (type: `integer`): How long a refnr stays in the dedup cache before it can re-emit. Default 7 days — matches the typical churn rate of new listings. ## Actor input object example ```json { "searchTerm": "software engineer", "location": "Berlin", "radiusKm": 25, "salaryMinEUR": 0, "remoteAllowed": false, "publishedDaysAgo": 30, "offerTypes": [ "1" ], "includeTemporaryAgency": false, "maxResults": 5, "includeRawDescription": false, "visaStatusFilter": [ "confirmed", "likely", "unknown" ], "useLlmTiebreaker": false, "llmTiebreakerMaxFraction": 30, "dedupAcrossRuns": true, "dedupHorizonDays": 7 } ``` # Actor output Schema ## `results` (type: `string`): No description # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "searchTerm": "software engineer", "location": "Berlin", "maxResults": 5 }; // Run the Actor and wait for it to finish const run = await client.actor("cg_nguyen/germany-visa-jobs").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "searchTerm": "software engineer", "location": "Berlin", "maxResults": 5, } # Run the Actor and wait for it to finish run = client.actor("cg_nguyen/germany-visa-jobs").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "searchTerm": "software engineer", "location": "Berlin", "maxResults": 5 }' | apify call cg_nguyen/germany-visa-jobs --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=cg_nguyen/germany-visa-jobs", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Germany Visa-Sponsored Jobs", "description": "Find Germany jobs that sponsor work visas (Blue Card, Skilled Worker, ICT). Pulls the federal Bundesagentur Jobboerse, enriches with full descriptions, classifies visa-sponsorship likelihood (regex + opt-in LLM tie-breaker), and dedupes across runs. For relocation services and intl. job seekers.", "version": "0.2", "x-build-id": "Sdd84vwUAI1RQPLia" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/cg_nguyen~germany-visa-jobs/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-cg_nguyen-germany-visa-jobs", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/cg_nguyen~germany-visa-jobs/runs": { "post": { "operationId": "runs-sync-cg_nguyen-germany-visa-jobs", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/cg_nguyen~germany-visa-jobs/run-sync": { "post": { "operationId": "run-sync-cg_nguyen-germany-visa-jobs", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "searchTerm" ], "properties": { "searchTerm": { "title": "Job title / keywords (was)", "type": "string", "description": "Free-text search on job title. Example: 'software engineer', 'data scientist', 'pflegefachkraft'.", "default": "software engineer" }, "location": { "title": "Location (wo)", "type": "string", "description": "City, postal code, or state in Germany. Leave empty for nationwide search.", "default": "" }, "radiusKm": { "title": "Search radius around location (km)", "minimum": 0, "maximum": 200, "type": "integer", "description": "Only applied when location is set. Defaults to 25 km on the federal API.", "default": 25 }, "salaryMinEUR": { "title": "Minimum annual salary (EUR)", "minimum": 0, "type": "integer", "description": "Hard filter — drops jobs whose advertised upper salary is below this. 0 means no filter.", "default": 0 }, "remoteAllowed": { "title": "Include remote-friendly jobs only", "type": "boolean", "description": "Soft filter — currently keyword-based on the description ('remote', 'homeoffice', 'mobile working'). Improves Day 2 with the classifier.", "default": false }, "publishedDaysAgo": { "title": "Only jobs published in the last N days", "minimum": 0, "maximum": 100, "type": "integer", "description": "0 = no time filter. Federal API caps at 100.", "default": 30 }, "offerTypes": { "title": "Offer type filter (angebotsart)", "type": "array", "description": "1 = Job, 2 = Self-employment, 4 = Training/Dual studies, 34 = Internship/Trainee.", "items": { "type": "string", "enum": [ "1", "2", "4", "34" ], "enumTitles": [ "Job (Arbeit)", "Self-employment", "Training / dual studies", "Internship / trainee" ] }, "default": [ "1" ] }, "includeTemporaryAgency": { "title": "Include staffing-agency listings (Zeitarbeit)", "type": "boolean", "description": "Off by default — staffing-agency listings are usually thin (no description, no salary, often re-postings). Set true to include them anyway.", "default": false }, "maxResults": { "title": "Max results to enrich", "minimum": 1, "maximum": 2000, "type": "integer", "description": "Hard cap on jobs fetched + detail-enriched. Each result fires one PPE event.", "default": 50 }, "includeRawDescription": { "title": "Include full job description in output", "type": "boolean", "description": "If false (default), output keeps the first 500 characters of the description. Set true for downstream NLP.", "default": false }, "visaStatusFilter": { "title": "Visa-sponsorship filter", "type": "array", "description": "Only emit jobs whose classifier verdict matches one of these. Default: confirmed + likely + unknown (drops only explicit no-sponsorship). Set to ['confirmed'] for the strictest list.", "items": { "type": "string", "enum": [ "confirmed", "likely", "unlikely", "unknown" ], "enumTitles": [ "Confirmed (explicit sponsorship)", "Likely (strong indirect signals)", "Unlikely (citizenship/permit required)", "Unknown (no clear signal)" ] }, "default": [ "confirmed", "likely", "unknown" ] }, "useLlmTiebreaker": { "title": "Use LLM tie-breaker for ambiguous jobs", "type": "boolean", "description": "Escalate 'unknown' verdicts to Claude Haiku for a final classification. Requires an Anthropic API key below. Rate-limited per run by llmTiebreakerMaxFraction.", "default": false }, "anthropicApiKey": { "title": "Anthropic API key", "type": "string", "description": "Optional, only used when 'useLlmTiebreaker' is on. Format: sk-ant-…. Stored as a per-run secret — not retained on the actor." }, "llmTiebreakerMaxFraction": { "title": "Max fraction of jobs sent to LLM tie-breaker", "minimum": 0, "maximum": 100, "type": "integer", "description": "Hard cap on tie-breaker calls per run as a percentage of fetched jobs (0–100). Default 30. Prevents runaway cost on ambiguous result sets.", "default": 30 }, "dedupAcrossRuns": { "title": "Skip jobs seen in earlier runs", "type": "boolean", "description": "On by default. The Bundesagentur API surfaces the same listing for ~14 days, so daily runs would otherwise emit massive duplicates. We cache emitted refnrs in the actor's key-value store and skip them on subsequent runs. Turn this off if you want every run to be a full snapshot.", "default": true }, "dedupHorizonDays": { "title": "Dedup memory horizon (days)", "minimum": 1, "maximum": 60, "type": "integer", "description": "How long a refnr stays in the dedup cache before it can re-emit. Default 7 days — matches the typical churn rate of new listings.", "default": 7 } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```