# AI Icebreaker Generator - Cold-Email Opening Lines (`santamaria-automations/ai-icebreaker`) Actor Generate one personalized cold-outreach opening line per Google Maps place record using a BYO LLM key chain (Gemini, Groq, OpenRouter). Base mode uses only fields already on the place record (zero fetch). Enriched mode also fetches the homepage and folds a summary into the prompt. Pay-per-result. - **URL**: https://apify.com/santamaria-automations/ai-icebreaker.md - **Developed by:** [NanoScrape](https://apify.com/santamaria-automations) (community) - **Categories:** Lead generation, AI, Automation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $3.00 / 1,000 result (base)s 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/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 ## AI Icebreaker Generator Turn a batch of Google Maps place records into one hyper-personalized cold-outreach opening line per business. Bring your own LLM key (Gemini has a generous free tier). Two modes: base uses only fields already present on the place, enriched also fetches the homepage and folds a summary into the prompt. Feed it the output of the [Google Maps Scraper](https://apify.com/santamaria-automations/google-maps-scraper) and get one ready-to-send opener per business. ### What It Does Given a Google Maps place record, the actor asks an LLM to write ONE sentence that: - Is at most 200 characters - References something specific about the business (rating, category + city, tenure, description, homepage detail) - Matches the requested `tone` (friendly, professional, casual, direct) - Is grounded in the input data. Never a generic template, never invented facts. - Falls back to an empty string when the record has too little signal (no name, or missing category AND reviews AND description) ### Modes #### Base (default, zero-fetch) Uses only fields already on the place record: - `title` / `name` - `category`, `categories` - `city`, `country` (from `complete_address`) - `rating` / `review_rating`, `review_count` - `description` - `phone`, `website` (reference only, not fetched) #### Enriched (opt-in) Set `enableEnriched: true`. In addition to base mode, the actor fetches the business's homepage, condenses it into a ~1000 character markdown summary (headings + tagline + prose paragraphs), and appends it to the LLM prompt. Falls back silently to base mode when the site returns non-200, redirects strangely, or trips an anti-bot challenge. ### Input Two shapes are accepted, and you can mix them in one run. Flat places list (natural shape, just pipe the google-maps-scraper output): ```json { "places": [ { "place_id": "ChIJN1t_tDeuEmsRUsoyG83frY4", "title": "Example Coffee House", "category": "Coffee shop", "website": "https://example-coffee.example", "rating": 4.8, "review_count": 1240, "complete_address": { "city": "Berlin", "country": "Germany" } } ], "tone": "friendly", "outputLanguage": "en", "geminiApiKey": "AIza..." } ```` Companies shape (with a `company_id` passthrough for join-back to your CRM): ```json { "companies": [ { "company_id": "acme-42", "place": { "place_id": "ChIJ...", "title": "Example Company Ltd." } } ], "tone": "professional", "geminiApiKey": "AIza..." } ``` ### LLM Configuration You must supply at least one LLM key. All three providers are supported: | Provider | Free tier | Get a key | |----------|-----------|-----------| | Gemini | Yes (generous) | https://aistudio.google.com/app/apikey | | Groq | Yes | https://console.groq.com/keys | | OpenRouter | Pay-as-you-go, cheap | https://openrouter.ai/keys | Set `llmProvider` to pick the primary, `fallbackProvider` and `fallback2Provider` for the chain. Same-provider transient errors (5xx, timeouts) get one retry; auth/quota errors fall through to the next provider. ### Output One row per input place: ```json { "company_id": "acme-42", "place_id": "ChIJN1t_tDeuEmsRUsoyG83frY4", "name": "Example Coffee House", "icebreaker_line": "Noticed you are running one of the highest-rated (4.8 stars, 1,240 reviews) coffee shops in Berlin. Curious how you keep that streak going.", "icebreaker_enriched": false, "llm_provider": "gemini", "llm_model": "gemini-2.0-flash", "llm_tokens_input": 340, "llm_tokens_output": 45, "generated_at": "2026-07-17T10:30:00Z" } ``` `icebreaker_line` is an empty string when the record had too little signal to produce a specific line. The actor never invents facts to fill the gap. ### How To Use It 1. Run [Google Maps Scraper](https://apify.com/santamaria-automations/google-maps-scraper) to collect places for a niche and city. 2. Feed the dataset into this actor as `places` (or wrap each in `companies` for join-back). 3. Pick a tone, set your Gemini key, and (optionally) turn on enriched mode. 4. Drop the output into your outbound sequencer. ### Pricing Pay-per-result via Apify Pay-Per-Event billing: | Event | Price | Description | |-------|-------|-------------| | Actor start | $0.001 | Charged once per run | | Icebreaker generated (base) | $0.003 | Charged per row in base mode | | Icebreaker generated (enriched) | $0.005 | Charged per row when enriched mode succeeded | Generating 1,000 lines in base mode costs about $3. Empty input rows and rows the model refused to write for (insufficient signal) are still counted as a result. LLM API usage is billed by your provider directly, not by this actor. ### Related Actors Discovery: - [Google Maps Scraper](https://apify.com/santamaria-automations/google-maps-scraper) - collect places in bulk Enrichment: - [GBP Completeness Audit](https://apify.com/santamaria-automations/gbp-completeness-audit) - score Google Business Profiles for lead prioritization - [Website Email Scraper](https://apify.com/santamaria-automations/website-email-scraper) - pull emails and phones from company sites - [Website Contact Extractor](https://apify.com/santamaria-automations/website-contact-extractor) - LLM-powered people extraction ### Notes - Empty input is free. No `enrichment-start` is billed unless there is at least one valid place. - The proxy configuration is only used by enriched mode's homepage fetch. - Language: set `outputLanguage: "auto"` to have the model match the business's country language. ### Issues & Feature Requests If the model keeps refusing lines for a class of business, or if you would like a new tone, open an issue on the actor's Issues tab and we will take a look. # Actor input Schema ## `places` (type: `array`): Array of Google Maps place records. Each element is a full place object as emitted by the google-maps-scraper actor (with `title`, `category`, `categories`, `website`, `phone`, `rating`, `review_count`, `description`, `complete_address`, etc.). ## `companies` (type: `array`): Alternative to `places`. Each entry carries a company\_id (echoed on the output row) plus the place record. ## `tone` (type: `string`): Voice of the generated line. `friendly` is warm and professional (default), `professional` is buttoned-up, `casual` is chatty, `direct` is punchy and to-the-point. ## `focus` (type: `string`): Optional free-text guidance passed to the LLM alongside the place record. Steers every line toward your specific outreach angle. Example: 'Focus on their photo count and their newest reviews', or 'Mention that we specialize in local SEO for care homes'. ## `enableEnriched` (type: `boolean`): When true, the actor fetches each business's homepage, condenses it into a short summary, and folds it into the icebreaker prompt. Costs slightly more per row but produces sharper lines. Falls back silently to base mode when the site 404s or hits an anti-bot challenge. ## `llmProvider` (type: `string`): Primary AI provider. Gemini Flash is fastest and has a generous free tier. ## `fallbackProvider` (type: `string`): Second-level fallback if the primary provider fails (rate limit, auth error, etc). ## `fallback2Provider` (type: `string`): Third-level fallback if both primary and first fallback fail. ## `llmModel` (type: `string`): Override the default model. Defaults: Gemini -> gemini-2.0-flash, Groq -> llama-3.3-70b-versatile, OpenRouter -> google/gemini-2.0-flash-001. If your OpenRouter key does not have access to the default paid Gemini model, try a free model like meta-llama/llama-3.1-8b-instruct. ## `geminiApiKey` (type: `string`): Google Gemini Flash. Best quality/cost ratio, generous free tier. Get a key at https://aistudio.google.com/app/apikey ## `groqApiKey` (type: `string`): Groq. Ultra-fast inference. Get a key at https://console.groq.com/keys ## `openrouterApiKey` (type: `string`): OpenRouter. Access to 100+ models. Get a key at https://openrouter.ai/keys ## `outputLanguage` (type: `string`): Language for the generated icebreaker line. Uses standard ISO 639-1 codes. Pass any ISO 639-1 language code: en, de, fr, ja, es, pt, it, ko, zh-CN, ar, nl, pl, sv, da, fi, no, cs, hu, ro, el, tr, th, vi, id, and more. Set to `auto` to match the business's country/language. ## `proxyConfiguration` (type: `object`): Only used when enriched mode is enabled (for the homepage fetch). Apify proxy works for most sites. ## Actor input object example ```json { "places": [ { "place_id": "ChIJN1t_tDeuEmsRUsoyG83frY4", "title": "Example Coffee House", "category": "Coffee shop", "categories": [ "Coffee shop", "Cafe" ], "website": "https://example-coffee.example", "phone": "+49 30 12345678", "rating": 4.8, "review_count": 1240, "description": "Specialty coffee roastery, direct-trade beans, natural wines and weekend brunch.", "complete_address": { "city": "Berlin", "country": "Germany", "borough": "Sample District" } }, { "place_id": "ChIJcareHomeSAMPLE12345", "title": "Sample Care Foundation", "category": "Nursing home", "categories": [ "Nursing home", "Senior care service" ], "phone": "+49 7531 200000", "rating": 4.4, "review_count": 87, "description": "Sample Care Foundation has been caring for seniors for over 20 years across three residential campuses.", "complete_address": { "city": "Sampletown", "country": "Germany" } }, { "place_id": "ChIJsculptureStudio77", "title": "Example Art Studio", "category": "Sculptor", "website": "https://example-studio.example", "rating": 5, "review_count": 12, "complete_address": { "city": "Berlin", "country": "Germany" } } ], "tone": "friendly", "enableEnriched": false, "llmProvider": "gemini", "outputLanguage": "en", "proxyConfiguration": { "useApifyProxy": true } } ``` # Actor output Schema ## `icebreakers` (type: `string`): Dataset of generated icebreaker rows # 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 = { "places": [ { "place_id": "ChIJN1t_tDeuEmsRUsoyG83frY4", "title": "Example Coffee House", "category": "Coffee shop", "categories": [ "Coffee shop", "Cafe" ], "website": "https://example-coffee.example", "phone": "+49 30 12345678", "rating": 4.8, "review_count": 1240, "description": "Specialty coffee roastery, direct-trade beans, natural wines and weekend brunch.", "complete_address": { "city": "Berlin", "country": "Germany", "borough": "Sample District" } }, { "place_id": "ChIJcareHomeSAMPLE12345", "title": "Sample Care Foundation", "category": "Nursing home", "categories": [ "Nursing home", "Senior care service" ], "phone": "+49 7531 200000", "rating": 4.4, "review_count": 87, "description": "Sample Care Foundation has been caring for seniors for over 20 years across three residential campuses.", "complete_address": { "city": "Sampletown", "country": "Germany" } }, { "place_id": "ChIJsculptureStudio77", "title": "Example Art Studio", "category": "Sculptor", "website": "https://example-studio.example", "rating": 5, "review_count": 12, "complete_address": { "city": "Berlin", "country": "Germany" } } ] }; // Run the Actor and wait for it to finish const run = await client.actor("santamaria-automations/ai-icebreaker").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 = { "places": [ { "place_id": "ChIJN1t_tDeuEmsRUsoyG83frY4", "title": "Example Coffee House", "category": "Coffee shop", "categories": [ "Coffee shop", "Cafe", ], "website": "https://example-coffee.example", "phone": "+49 30 12345678", "rating": 4.8, "review_count": 1240, "description": "Specialty coffee roastery, direct-trade beans, natural wines and weekend brunch.", "complete_address": { "city": "Berlin", "country": "Germany", "borough": "Sample District", }, }, { "place_id": "ChIJcareHomeSAMPLE12345", "title": "Sample Care Foundation", "category": "Nursing home", "categories": [ "Nursing home", "Senior care service", ], "phone": "+49 7531 200000", "rating": 4.4, "review_count": 87, "description": "Sample Care Foundation has been caring for seniors for over 20 years across three residential campuses.", "complete_address": { "city": "Sampletown", "country": "Germany", }, }, { "place_id": "ChIJsculptureStudio77", "title": "Example Art Studio", "category": "Sculptor", "website": "https://example-studio.example", "rating": 5, "review_count": 12, "complete_address": { "city": "Berlin", "country": "Germany", }, }, ] } # Run the Actor and wait for it to finish run = client.actor("santamaria-automations/ai-icebreaker").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 '{ "places": [ { "place_id": "ChIJN1t_tDeuEmsRUsoyG83frY4", "title": "Example Coffee House", "category": "Coffee shop", "categories": [ "Coffee shop", "Cafe" ], "website": "https://example-coffee.example", "phone": "+49 30 12345678", "rating": 4.8, "review_count": 1240, "description": "Specialty coffee roastery, direct-trade beans, natural wines and weekend brunch.", "complete_address": { "city": "Berlin", "country": "Germany", "borough": "Sample District" } }, { "place_id": "ChIJcareHomeSAMPLE12345", "title": "Sample Care Foundation", "category": "Nursing home", "categories": [ "Nursing home", "Senior care service" ], "phone": "+49 7531 200000", "rating": 4.4, "review_count": 87, "description": "Sample Care Foundation has been caring for seniors for over 20 years across three residential campuses.", "complete_address": { "city": "Sampletown", "country": "Germany" } }, { "place_id": "ChIJsculptureStudio77", "title": "Example Art Studio", "category": "Sculptor", "website": "https://example-studio.example", "rating": 5, "review_count": 12, "complete_address": { "city": "Berlin", "country": "Germany" } } ] }' | apify call santamaria-automations/ai-icebreaker --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=santamaria-automations/ai-icebreaker", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "AI Icebreaker Generator - Cold-Email Opening Lines", "description": "Generate one personalized cold-outreach opening line per Google Maps place record using a BYO LLM key chain (Gemini, Groq, OpenRouter). Base mode uses only fields already on the place record (zero fetch). Enriched mode also fetches the homepage and folds a summary into the prompt. Pay-per-result.", "version": "1.0", "x-build-id": "aGMDLPWqGWVv1ahYH" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/santamaria-automations~ai-icebreaker/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-santamaria-automations-ai-icebreaker", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/santamaria-automations~ai-icebreaker/runs": { "post": { "operationId": "runs-sync-santamaria-automations-ai-icebreaker", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/santamaria-automations~ai-icebreaker/run-sync": { "post": { "operationId": "run-sync-santamaria-automations-ai-icebreaker", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "places": { "title": "Places", "type": "array", "description": "Array of Google Maps place records. Each element is a full place object as emitted by the google-maps-scraper actor (with `title`, `category`, `categories`, `website`, `phone`, `rating`, `review_count`, `description`, `complete_address`, etc.).", "items": { "type": "object" } }, "companies": { "title": "Companies (with company_id passthrough)", "type": "array", "description": "Alternative to `places`. Each entry carries a company_id (echoed on the output row) plus the place record.", "items": { "type": "object", "required": [ "place" ], "properties": { "company_id": { "title": "Company ID", "type": "string", "description": "Your internal identifier, echoed on the output row so you can join icebreakers back to your source data." }, "place": { "title": "Place", "type": "object", "description": "The Google Maps place record." } } } }, "tone": { "title": "Tone", "enum": [ "friendly", "professional", "casual", "direct" ], "type": "string", "description": "Voice of the generated line. `friendly` is warm and professional (default), `professional` is buttoned-up, `casual` is chatty, `direct` is punchy and to-the-point.", "default": "friendly" }, "focus": { "title": "Focus (optional free-text)", "type": "string", "description": "Optional free-text guidance passed to the LLM alongside the place record. Steers every line toward your specific outreach angle. Example: 'Focus on their photo count and their newest reviews', or 'Mention that we specialize in local SEO for care homes'." }, "enableEnriched": { "title": "Enable Enriched Mode (homepage fetch)", "type": "boolean", "description": "When true, the actor fetches each business's homepage, condenses it into a short summary, and folds it into the icebreaker prompt. Costs slightly more per row but produces sharper lines. Falls back silently to base mode when the site 404s or hits an anti-bot challenge.", "default": false }, "llmProvider": { "title": "LLM Provider", "enum": [ "gemini", "groq", "openrouter" ], "type": "string", "description": "Primary AI provider. Gemini Flash is fastest and has a generous free tier.", "default": "gemini" }, "fallbackProvider": { "title": "Fallback LLM Provider", "enum": [ "gemini", "groq", "openrouter" ], "type": "string", "description": "Second-level fallback if the primary provider fails (rate limit, auth error, etc)." }, "fallback2Provider": { "title": "Third-Level Fallback", "enum": [ "gemini", "groq", "openrouter" ], "type": "string", "description": "Third-level fallback if both primary and first fallback fail." }, "llmModel": { "title": "LLM Model (optional override)", "type": "string", "description": "Override the default model. Defaults: Gemini -> gemini-2.0-flash, Groq -> llama-3.3-70b-versatile, OpenRouter -> google/gemini-2.0-flash-001. If your OpenRouter key does not have access to the default paid Gemini model, try a free model like meta-llama/llama-3.1-8b-instruct." }, "geminiApiKey": { "title": "Gemini API Key (recommended)", "type": "string", "description": "Google Gemini Flash. Best quality/cost ratio, generous free tier. Get a key at https://aistudio.google.com/app/apikey" }, "groqApiKey": { "title": "Groq API Key (optional)", "type": "string", "description": "Groq. Ultra-fast inference. Get a key at https://console.groq.com/keys" }, "openrouterApiKey": { "title": "OpenRouter API Key (optional)", "type": "string", "description": "OpenRouter. Access to 100+ models. Get a key at https://openrouter.ai/keys" }, "outputLanguage": { "title": "Output Language", "type": "string", "description": "Language for the generated icebreaker line. Uses standard ISO 639-1 codes. Pass any ISO 639-1 language code: en, de, fr, ja, es, pt, it, ko, zh-CN, ar, nl, pl, sv, da, fi, no, cs, hu, ro, el, tr, th, vi, id, and more. Set to `auto` to match the business's country/language.", "default": "en" }, "proxyConfiguration": { "title": "Proxy Configuration", "type": "object", "description": "Only used when enriched mode is enabled (for the homepage fetch). Apify proxy works for most sites.", "default": { "useApifyProxy": true } } } }, "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 } } } } } } } } } } ```