# Hacker News Idea & Pain Point Finder (`bohard/hacker-news-idea-finder`) Actor Search Hacker News for posts where people complain about problems and ask for tools. Find validated pain points, startup ideas and market-research signals. - **URL**: https://apify.com/bohard/hacker-news-idea-finder.md - **Developed by:** [Bohdan Shtelmakh](https://apify.com/bohard) (community) - **Categories:** Developer tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## 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 ## Hacker News Idea & Pain Point Finder Find **validated startup ideas and customer pain points** on Hacker News in seconds. Give it a topic — get back the posts and comments where real people complain, get frustrated, and ask "is there a tool that…". Perfect for **indie hackers, SaaS founders, marketers and product teams** doing market research and idea validation. ### What it does For each topic you provide, the actor: 1. Searches Hacker News (stories, Ask HN, Show HN and/or comments) via the official HN Algolia API. 2. Scans each item's title and text for **pain signals** — frustration, complaints, and requests for tools/alternatives. 3. Scores every item by how many pain signals it contains and returns the strongest ones, with a direct HN link. ### Input | Field | Type | Default | Description | |-------|------|---------|-------------| | `queries` | array | — | Topics / keywords to search. Required. | | `tags` | array | ["story"] | Content types: story, ask_hn, show_hn, comment. | | `maxItemsPerQuery` | integer | 100 | Items to scan per query. | | `sort` | string | relevance | relevance or new. | | `time` | string | all | all / year / month / week / day. | | `minPoints` | integer | 0 | Minimum HN points (0 = no filter). | | `minPainScore` | integer | 1 | Minimum number of pain signals to include an item. | #### Example input ```json { "queries": ["project management", "time tracking"], "tags": ["story", "ask_hn"], "maxItemsPerQuery": 100, "sort": "relevance", "time": "year", "minPoints": 5, "minPainScore": 1 } ```` ### Output Each dataset item: ```json { "query": "project management", "painScore": 3, "matchedSignals": ["frustration", "has a problem with something", "looking for a tool"], "type": "Ask HN", "title": "Ask HN: Why is project management software so frustrating?", "snippet": "I've tried everything and I'm looking for a tool that just works…", "hnUrl": "https://news.ycombinator.com/item?id=12345678", "externalUrl": null, "author": "someuser", "points": 142, "numComments": 87, "createdAt": "2026-01-12T08:30:00.000Z" } ``` Sort by `painScore` to find the strongest, most actionable complaints. ### Notes & limits - Uses the public Hacker News (Algolia) search API — no login or API key required. - Pain detection is heuristic (pattern-based), tuned for precision over recall. - Great companion to building products: validate that a problem is real before you code it. # Actor input Schema ## `queries` (type: `array`): Topics or keywords to search Hacker News for (e.g. "project management", "invoicing", "note taking"). The actor finds posts where people express frustration or ask for tools around these topics. ## `tags` (type: `array`): Which Hacker News content to search: stories, Ask HN, Show HN, or comments. ## `maxItemsPerQuery` (type: `integer`): How many Hacker News items to fetch and analyse per query. Higher = more results but slower. ## `sort` (type: `string`): Relevance ranks by best match; Newest returns the most recent first. ## `time` (type: `string`): Only include items created within this window. ## `minPoints` (type: `integer`): Only include items with at least this many points (0 = no filter). ## `minPainScore` (type: `integer`): Only return items with at least this many pain signals (1 = any signal, higher = stronger complaints only). ## Actor input object example ```json { "queries": [ "project management" ], "tags": [ "story" ], "maxItemsPerQuery": 100, "sort": "relevance", "time": "all", "minPoints": 0, "minPainScore": 1 } ``` # Actor output Schema ## `painPoints` (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 = { "queries": [ "project management" ] }; // Run the Actor and wait for it to finish const run = await client.actor("bohard/hacker-news-idea-finder").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 = { "queries": ["project management"] } # Run the Actor and wait for it to finish run = client.actor("bohard/hacker-news-idea-finder").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 '{ "queries": [ "project management" ] }' | apify call bohard/hacker-news-idea-finder --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=bohard/hacker-news-idea-finder", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Hacker News Idea & Pain Point Finder", "description": "Search Hacker News for posts where people complain about problems and ask for tools. Find validated pain points, startup ideas and market-research signals.", "version": "0.1", "x-build-id": "yLKth4TlowheXk3T8" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/bohard~hacker-news-idea-finder/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-bohard-hacker-news-idea-finder", "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/bohard~hacker-news-idea-finder/runs": { "post": { "operationId": "runs-sync-bohard-hacker-news-idea-finder", "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/bohard~hacker-news-idea-finder/run-sync": { "post": { "operationId": "run-sync-bohard-hacker-news-idea-finder", "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": [ "queries" ], "properties": { "queries": { "title": "Search queries / topics", "type": "array", "description": "Topics or keywords to search Hacker News for (e.g. \"project management\", \"invoicing\", \"note taking\"). The actor finds posts where people express frustration or ask for tools around these topics.", "items": { "type": "string" } }, "tags": { "title": "Content types", "type": "array", "description": "Which Hacker News content to search: stories, Ask HN, Show HN, or comments.", "items": { "type": "string", "enum": [ "story", "ask_hn", "show_hn", "comment" ], "enumTitles": [ "Stories", "Ask HN", "Show HN", "Comments" ] }, "default": [ "story" ] }, "maxItemsPerQuery": { "title": "Max items to scan per query", "minimum": 10, "maximum": 1000, "type": "integer", "description": "How many Hacker News items to fetch and analyse per query. Higher = more results but slower.", "default": 100 }, "sort": { "title": "Sort order", "enum": [ "relevance", "new" ], "type": "string", "description": "Relevance ranks by best match; Newest returns the most recent first.", "default": "relevance" }, "time": { "title": "Time range", "enum": [ "all", "year", "month", "week", "day" ], "type": "string", "description": "Only include items created within this window.", "default": "all" }, "minPoints": { "title": "Minimum points", "minimum": 0, "maximum": 1000, "type": "integer", "description": "Only include items with at least this many points (0 = no filter).", "default": 0 }, "minPainScore": { "title": "Minimum pain score", "minimum": 1, "maximum": 10, "type": "integer", "description": "Only return items with at least this many pain signals (1 = any signal, higher = stronger complaints only).", "default": 1 } } }, "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 } } } } } } } } } } ```