# Hacker News Monitor — Brand & Tech Keyword Alerts (Vigia) (`om_kh/vigia-hackernews-monitor`) Actor Monitor Hacker News for your brand, product or tech keywords and get only NEW stories since last check, with a discussion-spike signal. Charged only on new mentions, never per run. Ideal for dev-tool marketing, PR and competitive-intel agents. - **URL**: https://apify.com/om\_kh/vigia-hackernews-monitor.md - **Developed by:** [omar khandji](https://apify.com/om_kh) (community) - **Categories:** News, Marketing - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing Pay per event 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 ## Hacker News Monitor — Brand & Tech Keyword Alerts (Vigia) > Monitor Hacker News for your brand, product or tech keywords and get only NEW stories since last check, with a discussion-spike signal. Charged only on new mentions, never per run. Ideal for dev-tool marketing, PR and competitive-intel agents. > **100% first-party.** This monitor reads the **official Hacker News (Algolia) search API** directly — no third-party scraper in the middle. There is no upstream actor that can break, rate-limit, or go dark, and the source check costs just **$0.02**. ### What it does Get alerted when your product or a keyword hits Hacker News. You get **only what changed since your last check** — never a full re-dump to diff yourself. ### Why Vigia — 5 advantages a raw scraper can't match 1. **You pay the alert price only for real change.** New-story alerts are billed only for genuinely new stories since your last check. A quiet run bills just the small source-check fee (the cost of looking) — never the alert price on unchanged data. Raw scrapers bill every row of a full re-scan every run. 2. **Never billed on a failed source.** The source check is charged only when the source actually responded. If it's down, you don't pay for our outage. 3. **Append-only delta + spike signal.** The first monitored run stores a free baseline; later runs deliver only what's new, plus a velocity-spike alert when volume suddenly surges (trend / review-bomb / hiring-surge). 4. **Hard cost cap you control.** Set `maxTotalChargeUsd` and the run can never bill above it — predictable spend, no surprise invoice. 5. **Agent-ready output.** Clean, normalized rows and a `RUN_SUMMARY.json` with ready-to-use signals — chainable from any MCP / A2A agent in one step. ### Example input ```json { "keywords": [ "your product", "competitor name" ], "monitorEnabled": true, "maxTotalChargeUsd": 1.0 } ```` Set `monitorEnabled: true` so the first run stores a free baseline and later runs return only new results. Pin a `monitorId` to keep separate targets from sharing state. ### Output Each row is a normalized change record: `record_id`, `query_id`, `title`, `url`, `author`, `published_at`, `score`, `text`. A `RUN_SUMMARY.json` accompanies every run with the aggregated signal (counts, velocity spikes, trend). ### How you're charged - **Story alert** — billed once per new story since the last check (this is the only charge that scales with change). - **Source check** ($0.30) — billed once per monitored target per run, **only when the source responded**. A failed source is free. - **A quiet run bills only the source check** ($0.30), never the alert price. Vigia never scrapes the source itself; it chains a licensed scraper, caps every call, and passes you only the delta. *** *Part of the Vigia monitoring suite — change-only billing, outage-safe, agent-ready.* # Actor input Schema ## `keywords` (type: `array`): Brand, product, or tech keywords to monitor across Hacker News stories and comments. ## `currentItems` (type: `array`): Skip the chained fetch and pass records directly (no upstream call, no fetch fee). ## `maxTotalChargeUsd` (type: `number`): Hard maximum amount that this run may charge. ## `sources` (type: `array`): Declare every upstream source before this run. Each item needs name, authorization, and estimated\_cost\_usd. ## `monitorEnabled` (type: `boolean`): The first monitored run stores a free baseline. Later runs deliver and charge only new results. ## `monitorId` (type: `string`): Pins the persistent baseline to a name of your choice, so separate targets never share state. Leave empty to derive it automatically. ## Actor input object example ```json { "keywords": [ "your product", "competitor name" ], "currentItems": [], "maxTotalChargeUsd": 1, "sources": [ { "name": "Chained upstream actor", "authorization": "public_structured_data", "estimated_cost_usd": 0 } ], "monitorEnabled": false, "monitorId": "" } ``` # 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 = { "keywords": [ "your product", "competitor name" ] }; // Run the Actor and wait for it to finish const run = await client.actor("om_kh/vigia-hackernews-monitor").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 = { "keywords": [ "your product", "competitor name", ] } # Run the Actor and wait for it to finish run = client.actor("om_kh/vigia-hackernews-monitor").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 '{ "keywords": [ "your product", "competitor name" ] }' | apify call om_kh/vigia-hackernews-monitor --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=om_kh/vigia-hackernews-monitor", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Hacker News Monitor — Brand & Tech Keyword Alerts (Vigia)", "description": "Monitor Hacker News for your brand, product or tech keywords and get only NEW stories since last check, with a discussion-spike signal. Charged only on new mentions, never per run. Ideal for dev-tool marketing, PR and competitive-intel agents.", "version": "0.1", "x-build-id": "bOXYM8OFSNAxzSiDj" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/om_kh~vigia-hackernews-monitor/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-om_kh-vigia-hackernews-monitor", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/om_kh~vigia-hackernews-monitor/runs": { "post": { "operationId": "runs-sync-om_kh-vigia-hackernews-monitor", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/om_kh~vigia-hackernews-monitor/run-sync": { "post": { "operationId": "run-sync-om_kh-vigia-hackernews-monitor", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "maxTotalChargeUsd" ], "properties": { "keywords": { "title": "Search keywords", "type": "array", "description": "Brand, product, or tech keywords to monitor across Hacker News stories and comments.", "default": [], "items": { "type": "string" } }, "currentItems": { "title": "Bring your own items (optional)", "type": "array", "description": "Skip the chained fetch and pass records directly (no upstream call, no fetch fee).", "default": [] }, "maxTotalChargeUsd": { "title": "Maximum Vigia charge (USD)", "minimum": 0, "type": "number", "description": "Hard maximum amount that this run may charge.", "default": 1 }, "sources": { "title": "Declared upstream sources and estimated costs", "type": "array", "description": "Declare every upstream source before this run. Each item needs name, authorization, and estimated_cost_usd.", "default": [ { "name": "Chained upstream actor", "authorization": "public_structured_data", "estimated_cost_usd": 0 } ] }, "monitorEnabled": { "title": "Monitor only new results", "type": "boolean", "description": "The first monitored run stores a free baseline. Later runs deliver and charge only new results.", "default": false }, "monitorId": { "title": "Monitor ID (optional)", "type": "string", "description": "Pins the persistent baseline to a name of your choice, so separate targets never share state. Leave empty to derive it automatically.", "default": "" } } }, "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 } } } } } } } } } } ```