# Steam Localization Gaps (`arbogaste/steam-localization-gaps`) Actor Find well-reviewed Steam games missing localization for the languages you care about (Italian, French, German, Spanish and more). Filter by review score, owners and release year. For localization studios, indie devs and market researchers building target lists. - **URL**: https://apify.com/arbogaste/steam-localization-gaps.md - **Developed by:** [Samuele Guarnaccia](https://apify.com/arbogaste) (community) - **Categories:** Lead generation, Other - **Stats:** 2 total users, 1 monthly users, 0.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $5.00 / 1,000 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 web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows. 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/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.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/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 ## Steam Localization Gaps Finder Find well-reviewed Steam games that are **missing localization** for the languages you care about (Italian, French, German, Spanish and more). ### Who this is for - **Localizers & translation studios** — build a targeted lead list of games that objectively lack your language. - **Indie devs** — see which languages your competitors skipped (and where demand leaks). - **Market researchers** — quantify localization coverage across top-selling titles. ### What it does 1. Discovers top-selling / most-played games (SteamSpy) — or checks App IDs you provide. 2. Keeps only games above your **review count** and **positive %** thresholds (traction = a real buyer with unmet demand). 3. Reads each game's supported languages from the Steam store. 4. Outputs every game **missing any of your target languages**, with review score, owner range, and store link. ### Input | Field | Meaning | Default | |-------|---------|---------| | `targetLanguages` | languages to require | italian, french, german, spanish | | `minReviews` | skip low-traction games | 500 | | `minPositivePercent` | keep only well-rated games | 80 | | `maxGames` | hard cap on games scanned | 300 | | `appIds` | check only these (optional) | — | ### Output (dataset) `appid`, `name`, `reviewScore`, `totalReviews`, `owners`, `supportedLanguages`, `missingLanguages`, `isFree`, `storeUrl`. ### Notes - Uses only public endpoints (SteamSpy + Steam store appdetails). Rate-limited politely. - No login, no personal data. ### Pricing (pay-per-result) Charged per game returned. See the store page for current rate. # Actor input Schema ## `targetLanguages` (type: `array`): Languages to check for. A game is reported if it is missing ANY of these. ## `minReviews` (type: `integer`): Skip games with fewer total reviews (proxy for traction = worth localizing). ## `minPositivePercent` (type: `integer`): Only keep well-reviewed games (a good game without your language = a real buyer). ## `maxGames` (type: `integer`): Hard cap on how many app IDs to fetch details for. ## `appIds` (type: `array`): If set, checks only these Steam App IDs instead of discovering games. ## `discoverySource` (type: `string`): 'all' surfaces small-studio games via pagination (real localization buyers); 'top' surfaces AAA mega-hits. ## `page` (type: `integer`): SteamSpy 'all' page (1000 games/page, sorted by owners desc). Higher = smaller studios. ## `maxOwners` (type: `integer`): Skip games above this owner count. Excludes mega-hits whose studios rarely outsource localization. ## `minReleaseYear` (type: `integer`): Keep only games released this year or later. Filters out legacy catalog; targets active studios. 0 = no filter. ## Actor input object example ```json { "targetLanguages": [ "italian", "french", "german", "spanish" ], "minReviews": 500, "minPositivePercent": 80, "maxGames": 300, "appIds": [], "discoverySource": "all", "page": 2, "maxOwners": 2000000, "minReleaseYear": 0 } ```` # Actor output Schema ## `results` (type: `string`): All items produced by this run. # 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 = {}; // Run the Actor and wait for it to finish const run = await client.actor("arbogaste/steam-localization-gaps").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 = {} # Run the Actor and wait for it to finish run = client.actor("arbogaste/steam-localization-gaps").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 '{}' | apify call arbogaste/steam-localization-gaps --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=arbogaste/steam-localization-gaps", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Steam Localization Gaps", "description": "Find well-reviewed Steam games missing localization for the languages you care about (Italian, French, German, Spanish and more). Filter by review score, owners and release year. For localization studios, indie devs and market researchers building target lists.", "version": "0.0", "x-build-id": "m4l9SEuf9VCSn6DRN" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/arbogaste~steam-localization-gaps/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-arbogaste-steam-localization-gaps", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/arbogaste~steam-localization-gaps/runs": { "post": { "operationId": "runs-sync-arbogaste-steam-localization-gaps", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/arbogaste~steam-localization-gaps/run-sync": { "post": { "operationId": "run-sync-arbogaste-steam-localization-gaps", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "properties": { "targetLanguages": { "title": "Target languages", "type": "array", "description": "Languages to check for. A game is reported if it is missing ANY of these.", "items": { "type": "string", "enum": [ "italian", "french", "german", "spanish", "portuguese", "polish", "russian", "japanese", "korean", "schinese", "tchinese", "turkish", "dutch", "swedish" ] }, "default": [ "italian", "french", "german", "spanish" ] }, "minReviews": { "title": "Minimum reviews", "minimum": 0, "type": "integer", "description": "Skip games with fewer total reviews (proxy for traction = worth localizing).", "default": 500 }, "minPositivePercent": { "title": "Minimum positive review %", "minimum": 0, "maximum": 100, "type": "integer", "description": "Only keep well-reviewed games (a good game without your language = a real buyer).", "default": 80 }, "maxGames": { "title": "Max games to scan", "minimum": 1, "type": "integer", "description": "Hard cap on how many app IDs to fetch details for.", "default": 300 }, "appIds": { "title": "Specific App IDs (optional)", "type": "array", "description": "If set, checks only these Steam App IDs instead of discovering games.", "default": [], "items": { "type": "string" } }, "discoverySource": { "title": "Discovery source", "enum": [ "all", "top" ], "type": "string", "description": "'all' surfaces small-studio games via pagination (real localization buyers); 'top' surfaces AAA mega-hits.", "default": "all" }, "page": { "title": "Page (when discovery = all)", "minimum": 0, "type": "integer", "description": "SteamSpy 'all' page (1000 games/page, sorted by owners desc). Higher = smaller studios.", "default": 2 }, "maxOwners": { "title": "Max owners", "minimum": 0, "type": "integer", "description": "Skip games above this owner count. Excludes mega-hits whose studios rarely outsource localization.", "default": 2000000 }, "minReleaseYear": { "title": "Min release year", "minimum": 0, "type": "integer", "description": "Keep only games released this year or later. Filters out legacy catalog; targets active studios. 0 = no filter.", "default": 0 } } }, "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 } } } } } } } } } } ```