# Reddit Post Comments Summarizer (`rainminer/reddit-post-comments-summarizer`) Actor Paste a Reddit post URL and get an AI-generated TL;DR of the discussion. Comments are fetched via solidcode/reddit-scraper; this Actor produces the summary. No Reddit credentials required from users. - **URL**: https://apify.com/rainminer/reddit-post-comments-summarizer.md - **Developed by:** [rainminer](https://apify.com/rainminer) (community) - **Categories:** AI, Social media, Automation - **Stats:** 3 total users, 0 monthly users, 81.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $0.90 / 1,000 comments This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. 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 ## Reddit Post Comments Summarizer Paste any Reddit post URL and get a witty, insightful **TL;DR of the discussion** — generated automatically from the comment thread. Comments are fetched by the reliable [Reddit Scraper](https://apify.com/solidcode/reddit-scraper) Actor (`solidcode/reddit-scraper`). This Actor only handles orchestration and AI summarization, so you get stable Reddit access without maintaining scrapers yourself. ### What users provide | Input | Default | Description | | -------------- | ------- | -------------------------------------------------- | | `postUrl` | — | Any public Reddit post URL | | `commentCount` | 10 | Comments to fetch and summarize (10–500) | | `commentSort` | `top` | Sort hint for the Reddit scraper (`top`, `new`, …) | No Reddit API keys, proxies, or OAuth — users only paste a link. ### Example output One dataset item per run: ```json { "postUrl": "https://www.reddit.com/r/ClaudeAI/comments/1l4yrgp/claude_code_vs_cursor/", "postTitle": "Claude Code vs Cursor — which one are you actually using daily?", "subreddit": "r/ClaudeAI", "commentsAnalyzed": 10, "summary": "> TL;DR of the discussion generated automatically after 10 comments.\n\nThe thread is less a clean winner-take-all vote and more a workflow split: people who live in the terminal and want agentic multi-file edits lean hard toward Claude Code, while folks who want IDE-native refactors, inline diffs, and a familiar VS Code shell defend Cursor. Several top comments argue the comparison is unfair because the products optimize for different surfaces — CLI orchestration vs editor UX — and that “daily driver” really means “what’s open when I’m shipping.”\n\nCost and limits dominate the skeptical takes. Multiple users report burning through subscription tiers faster with heavy agent loops, and a recurring theme is picking the tool that matches how aggressively you delegate whole tasks vs. how often you still hand-edit. A smaller camp says they run both: Cursor for navigation and quick fixes, Claude Code for repo-wide changes and test runs.\n\nPractical advice that gets upvoted: try the same real task (bugfix + small feature) in each for a week, track latency to a correct PR, and ignore benchmark screenshots. The memorable quote energy is “stop treating them like the same product with different logos.” Overall consensus: neither is magic; team habits and repo size matter more than the brand on the splash screen.", "scrapedAt": "2026-06-03T14:22:11.847Z" } ```` ### Output fields | Field | Description | | ------------------ | ------------------------------------ | | `postUrl` | Canonical Reddit post URL | | `postTitle` | Post title | | `subreddit` | e.g. `r/ClaudeAI` | | `commentsAnalyzed` | Comments included in the summary | | `summary` | Full AI-generated discussion summary | | `scrapedAt` | ISO timestamp | ### Image Credit Image credit: [reddit.com](https://www.reddit.com) # Actor input Schema ## `postUrl` (type: `string`): URL of the Reddit post to summarize. E.g. https://www.reddit.com/r/ClaudeAI/comments/abc123/title/ ## `commentCount` (type: `integer`): How many comments to fetch from the post and include in the summary. More comments = richer summary but higher cost (Reddit scraper + summarization). ## `commentSort` (type: `string`): Sort order passed to the underlying Reddit scraper when loading the post thread. ## Actor input object example ```json { "postUrl": "https://www.reddit.com/r/ClaudeAI/comments/1d2e3f/some_post_title/", "commentCount": 10, "commentSort": "top" } ``` # Actor output Schema ## `overview` (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 = { "postUrl": "https://www.reddit.com/r/AskWomen/comments/1tssh3x/whats_the_most_attractive_thing_someone_did_that/", "commentCount": 10 }; // Run the Actor and wait for it to finish const run = await client.actor("rainminer/reddit-post-comments-summarizer").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 = { "postUrl": "https://www.reddit.com/r/AskWomen/comments/1tssh3x/whats_the_most_attractive_thing_someone_did_that/", "commentCount": 10, } # Run the Actor and wait for it to finish run = client.actor("rainminer/reddit-post-comments-summarizer").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 '{ "postUrl": "https://www.reddit.com/r/AskWomen/comments/1tssh3x/whats_the_most_attractive_thing_someone_did_that/", "commentCount": 10 }' | apify call rainminer/reddit-post-comments-summarizer --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=rainminer/reddit-post-comments-summarizer", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Reddit Post Comments Summarizer", "description": "Paste a Reddit post URL and get an AI-generated TL;DR of the discussion. Comments are fetched via solidcode/reddit-scraper; this Actor produces the summary. No Reddit credentials required from users.", "version": "1.0", "x-build-id": "pIhSw3S4g0eSXliLI" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/rainminer~reddit-post-comments-summarizer/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-rainminer-reddit-post-comments-summarizer", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/rainminer~reddit-post-comments-summarizer/runs": { "post": { "operationId": "runs-sync-rainminer-reddit-post-comments-summarizer", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/rainminer~reddit-post-comments-summarizer/run-sync": { "post": { "operationId": "run-sync-rainminer-reddit-post-comments-summarizer", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "postUrl" ], "properties": { "postUrl": { "title": "Reddit post URL", "type": "string", "description": "URL of the Reddit post to summarize. E.g. https://www.reddit.com/r/ClaudeAI/comments/abc123/title/" }, "commentCount": { "title": "Number of comments to analyze", "minimum": 10, "maximum": 500, "type": "integer", "description": "How many comments to fetch from the post and include in the summary. More comments = richer summary but higher cost (Reddit scraper + summarization).", "default": 10 }, "commentSort": { "title": "Comment sort order", "enum": [ "top", "new", "controversial", "best", "old" ], "type": "string", "description": "Sort order passed to the underlying Reddit scraper when loading the post thread.", "default": "top" } } }, "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 } } } } } } } } } } ```