# Reddit Lead Scraper — Emails, Socials & Contact Info (`blackfalcondata/reddit-lead-scraper`) Actor

Turn Reddit into a B2B lead list. Keep only records that expose a contact signal — email, social profile or external website — found across posts, comments and user profiles. AI-ready text included; no login or developer token needed.

- **URL**: https://apify.com/blackfalcondata/reddit-lead-scraper.md
- **Developed by:** [Black Falcon Data](https://apify.com/blackfalcondata) (community)
- **Categories:** Social media, Lead generation, Automation
- **Stats:** 1 total users, 0 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $2.00 / 1,000 results

This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage.

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

### What does Reddit Lead Scraper do?

Reddit Lead Scraper turns Reddit discussions into a B2B lead list. Point it at any subreddit, post, profile, or keyword search and it returns only the records that carry a contact signal — an email, a social profile (LinkedIn, X, GitHub, Instagram and more), or an external website — mined from post bodies, comment threads, and user profiles. Each lead includes the contact fields plus the surrounding text in clean text / HTML / Markdown. No Reddit account, login, or API key required.

**New to Apify?** [Sign up free](https://console.apify.com/sign-up?fpr=1h3gvi) and use the included $5 monthly platform credit to test this actor.

### Key features

<!-- KEY_FEATURES:START -->
- **🎯 Contact-bearing records only** — returns only Reddit records that carry an email, a social profile, or an external website, so every row in your dataset is an actual lead. You pay for leads, not noise.
- **📇 Emails, socials & websites** — each lead carries an `emails` array, a structured `socialProfiles` map (LinkedIn, X, GitHub, Instagram…), and `extractedUrls`, parsed from posts, comments, and profiles.
- **🔎 Search, subreddits & profiles** — build lead lists from a subreddit feed, a keyword search across Reddit, a single thread, or specific user profiles — mix and match by dropping in any Reddit URL.
- **💬 Comment-thread coverage** — contacts are often buried in replies, so the actor scans nested comment threads (with depth and volume controls), not just top-level posts.
- **🧩 Lead context included** — every lead keeps the post or comment it came from, in clean text / HTML / Markdown, so you know who to contact and why before you reach out.
- **🤖 AI-ready & automatable** — structured JSON output drops straight into CRMs, enrichment tools, LLMs, and automation pipelines.
- **🧹 Lean, flexible output** — strip empty fields and pick a single description format to keep lead lists small and import-ready.
- **🔑 No login or API key required** — point the actor at any public Reddit URL or search term and run; no Reddit account or app registration needed.
<!-- KEY_FEATURES:END -->

### What data can you extract from reddit.com?

This actor returns **only records that carry a contact signal** — an email, a social profile, or an external (non-Reddit) website. Every other record is skipped, so each row in your dataset is an actual lead. Each record keeps a stable `itemType` (`post`, `comment`, or `user`) so you can tell the source apart inside a single dataset.

- **`emails`** — de-duplicated, lowercased emails from the body text and `mailto:` links (tracking / no-reply / asset false positives filtered out).
- **`socialProfiles`** — structured map: `linkedin`, `twitter`, `github`, `instagram`, `facebook`, `youtube`, `tiktok`, `xing`, `bluesky`, `threads`, `mastodon`.
- **`extractedUrls`** — outbound (non-Reddit) website links mentioned in the content.
- **Context fields** — `title`, body as text / HTML / Markdown, `score`, `author`, `community`, `createdAt`, and the canonical `url`, so you can see where each lead came from.

Leads are richest in business-oriented communities — for example r/forhire, r/freelance, r/Entrepreneur, r/startups, r/SaaS. Point the actor at the subreddits or searches where your audience is active. Records with no contact signal are skipped, so you only pay for leads.


### Input

Configure the actor through the input schema in Apify Console.

Key parameters:

- **`startUrls`** — Reddit URLs to scrape — subreddits, post pages, user profiles, community pages, or search result pages. Each URL determines what type of content is fetched.
- **`searchTerms`** — Search Reddit for these terms. Each entry becomes an independent search. Search posts are lightweight discovery records (plus their comments) — see Search Type.
- **`searchType`** — Type of results to return when using Search Terms. Post results are lightweight discovery records — id, url, title, subreddit and NSFW flag — plus their comment threads; scrape a result's URL directly for its full post fields (author, body, score, timestamp). (default: `"posts"`)
- **`sort`** — Sort order for posts and search results. (default: `"hot"`)
- **`time`** — Restrict subreddit-feed results to a time window (applies to Top sort on feeds; search is not time-windowed). (default: `"all"`)
- **`includeNSFW`** — Include posts and communities marked as NSFW (18+). (default: `false`)
- **`postDateLimit`** — Skip posts older than this ISO-8601 date (e.g. "2024-01-01"). Applies to subreddit feeds and post URLs; search results carry no date and are not filtered. Leave blank for no date limit.
- **`maxItems`** — Maximum total records to save across all sources (posts, comments, users, communities). (default: `100`)
- **`maxComments`** — Maximum number of comments to collect from each post page. (default: `200`)
- **`includeCollapsed`** — Expand and include comments that are initially collapsed (controversial or low-score). Enables deeper thread coverage, up to the comment and depth limits you set. (default: `true`)
- **`commentDepth`** — Maximum reply nesting depth to collect (1 = top-level only). (default: `10`)
- **`skipComments`** — Do not collect comments from post pages — output posts only. (default: `false`)
- ...and 5 more parameters

### Input examples

**Leads from a hiring subreddit** — Scan a freelance/hiring subreddit's posts and comments for contacts.

→ Only r/forhire records that carry an email, social profile, or website.

```json
{
  "startUrls": [
    {
      "url": "https://www.reddit.com/r/forhire/"
    }
  ],
  "sort": "new",
  "maxItems": 50,
  "maxComments": 50
}
````

**Keyword lead search** — Run keyword searches across Reddit and keep only contact-bearing posts.

→ Posts matching the search terms that expose a contact signal.

```json
{
  "searchTerms": [
    "looking for a developer"
  ],
  "searchType": "posts",
  "sort": "new",
  "maxItems": 100
}
```

**Subreddit + comment leads** — Founder and entrepreneur threads share contacts deep in the comments.

→ Contact-bearing posts and comments from r/Entrepreneur.

```json
{
  "startUrls": [
    {
      "url": "https://www.reddit.com/r/Entrepreneur/"
    }
  ],
  "maxItems": 50,
  "maxComments": 200
}
```

### Output

Each run produces a dataset of structured Reddit records. Results can be downloaded as JSON, CSV, or Excel from the Dataset tab in Apify Console.

### Example Reddit record

```json
{
  "itemType": "post",
  "id": "t3_1ttjtwv",
  "url": "https://www.reddit.com/r/programming/comments/1ttjtwv/your_process_memory_is_a_file_the/",
  "title": "Your process' memory is a file: The underappreciated gem that is /proc/<pid>/mem",
  "body": null,
  "bodyHtml": null,
  "contentHref": "https://lcamtuf.substack.com/p/weekend-trivia-your-process-memory",
  "postType": "link",
  "language": "en",
  "score": 129,
  "upvoteRatio": 0.9708029197080292,
  "numComments": 1,
  "awardCount": 0,
  "author": "mttd",
  "authorId": "t2_6gkbb",
  "community": "r/programming",
  "communityId": "t5_2fwo",
  "createdAt": "2026-06-01T08:32:12.581+02:00",
  "icon": "https://www.redditstatic.com/avatars/defaults/v2/avatar_default_7.png",
  "nsfw": false
}
```

### Example lead record (post with contact)

```json
{
  "itemType": "post",
  "id": "t3_1abc234",
  "url": "https://www.reddit.com/r/Entrepreneur/comments/1abc234/launching_my_saas_feedback_welcome/",
  "title": "Launched my SaaS — feedback welcome",
  "descriptionText": "Spent 6 months building this. Would love feedback — site is https://acme.io, I'm on https://www.linkedin.com/in/janedoe, or email jane@acme.io.",
  "score": 48,
  "author": "jane_builds",
  "community": "r/Entrepreneur",
  "createdAt": "2026-06-10T09:22:00.000Z",
  "emails": [
    "jane@acme.io"
  ],
  "extractedUrls": [
    "https://acme.io",
    "https://www.linkedin.com/in/janedoe"
  ],
  "socialProfiles": {
    "linkedin": "https://www.linkedin.com/in/janedoe",
    "twitter": null,
    "github": null
  }
}
```

### How to scrape reddit.com

1. Go to [Reddit Lead Scraper](https://apify.com/blackfalcondata/reddit-lead-scraper?fpr=1h3gvi) in Apify Console.
2. Configure the input.
3. Set `maxItems` to control how many results you need.
4. Click **Start** and wait for the run to finish.
5. Export the dataset as JSON, CSV, or Excel.

### Use cases

- Build B2B lead lists from freelance, hiring, founder, and SaaS communities.
- Find prospects who share a LinkedIn, GitHub, or website in relevant threads.
- Source freelancers and candidates posting in r/forhire and r/freelance.
- Enrich an existing CRM with emails, social profiles, and websites from target subreddits.
- Monitor specific subreddits on a schedule and collect new leads as they appear.
- Combine emails, social handles, and websites into a single ready-to-import lead file.

### How much does it cost to scrape reddit.com?

Reddit Lead Scraper uses [pay-per-event](https://docs.apify.com/platform/actors/paid-actors/pay-per-event) pricing. You pay a small fee when the run starts and then for each result that is actually produced.

- **Run start:** $0.008 per run
- **Per result:** $0.002 per Reddit record

Example costs:

- 10 results: **$0.028**
- 25 results: **$0.058**
- 100 results: **$0.21**
- 200 results: **$0.41**
- 500 results: **$1.01**

### FAQ

#### How many results can I get from reddit.com?

The number of results depends on the search query and available listings on reddit.com. Use the `maxItems` parameter to control how many results are returned per run.

#### Can I integrate Reddit Lead Scraper with other apps?

Yes. Reddit Lead Scraper works with Apify's [integrations](https://apify.com/integrations?fpr=1h3gvi) to connect with tools like Zapier, Make, Google Sheets, Slack, and more. You can also use webhooks to trigger actions when a run completes.

#### Can I use Reddit Lead Scraper with the Apify API?

Yes. You can start runs, manage inputs, and retrieve results programmatically through the [Apify API](https://docs.apify.com/api/v2). Client libraries are available for JavaScript, Python, and other languages.

#### Can I use Reddit Lead Scraper through an MCP Server?

Yes. Apify provides an [MCP Server](https://apify.com/apify/actors-mcp-server?fpr=1h3gvi) that lets AI assistants and agents call this actor directly. Use a single `descriptionFormat` and `excludeEmptyFields` to keep payloads manageable for LLM context windows.

#### Is it legal to scrape reddit.com?

This actor extracts publicly available data from reddit.com. Web scraping of public information is generally considered legal, but you should always review the target site's terms of service and ensure your use case complies with applicable laws and regulations, including GDPR where relevant.

#### Your feedback

If you have questions, need a feature, or found a bug, please [open an issue](https://apify.com/blackfalcondata/reddit-lead-scraper/issues?fpr=1h3gvi) on the actor's page in Apify Console. Your feedback helps us improve.

### You might also like

- [Reddit Email Scraper — Extract Emails from Posts & Comments](https://apify.com/blackfalcondata/reddit-email-scraper?fpr=1h3gvi) — Extract email addresses and contact details from Reddit posts, comments and user profiles. Search.
- [Reddit RAG Dataset — LLM Training Data from Posts & Comments](https://apify.com/blackfalcondata/reddit-rag-dataset?fpr=1h3gvi) — Build clean LLM and RAG datasets from Reddit. Export posts with full comment threads as.
- [Reddit Scraper 💰 $1.25/1K — Posts & Full Comment Threads](https://apify.com/blackfalcondata/reddit-scraper?fpr=1h3gvi) — Scrape Reddit posts with their full nested comment threads, user profiles, and community pages..
- [Reddit Sentiment Scraper — Analyze Posts & Comments](https://apify.com/blackfalcondata/reddit-sentiment-scraper?fpr=1h3gvi) — Scrape Reddit and score every post and comment for sentiment — positive, negative or neutral with a.
- [YouTube Scraper $2/1K — Videos, Channels, Comments, Transcripts](https://apify.com/blackfalcondata/youtube-data-scraper?fpr=1h3gvi) — Scrape YouTube videos, channels, comments, and transcripts in one tool — by keyword or by video,.

### Getting started with Apify

New to Apify? [Create a free account with $5 credit](https://console.apify.com/sign-up?fpr=1h3gvi) — no credit card required.

1. Sign up — $5 platform credit included
2. Open this actor and configure your input
3. Click **Start** — export results as JSON, CSV, or Excel

Need more later? [See Apify pricing](https://apify.com/pricing?fpr=1h3gvi).

# Actor input Schema

## `startUrls` (type: `array`):

Reddit URLs to scrape — subreddits, post pages, user profiles, community pages, or search result pages. Each URL determines what type of content is fetched.

## `searchTerms` (type: `array`):

Search Reddit for these terms. Each entry becomes an independent search. Search posts are lightweight discovery records (plus their comments) — see Search Type.

## `searchType` (type: `string`):

Type of results to return when using Search Terms. Post results are lightweight discovery records — id, url, title, subreddit and NSFW flag — plus their comment threads; scrape a result's URL directly for its full post fields (author, body, score, timestamp).

## `sort` (type: `string`):

Sort order for posts and search results.

## `time` (type: `string`):

Restrict subreddit-feed results to a time window (applies to Top sort on feeds; search is not time-windowed).

## `includeNSFW` (type: `boolean`):

Include posts and communities marked as NSFW (18+).

## `postDateLimit` (type: `string`):

Skip posts older than this ISO-8601 date (e.g. "2024-01-01"). Applies to subreddit feeds and post URLs; search results carry no date and are not filtered. Leave blank for no date limit.

## `maxItems` (type: `integer`):

Maximum total records to save across all sources (posts, comments, users, communities).

## `maxComments` (type: `integer`):

Maximum number of comments to collect from each post page.

## `includeCollapsed` (type: `boolean`):

Expand and include comments that are initially collapsed (controversial or low-score). Enables deeper thread coverage, up to the comment and depth limits you set.

## `commentDepth` (type: `integer`):

Maximum reply nesting depth to collect (1 = top-level only).

## `skipComments` (type: `boolean`):

Do not collect comments from post pages — output posts only.

## `descriptionFormat` (type: `string`):

Controls which body/description fields are included in output. "all" emits text + HTML + markdown variants.

## `excludeEmptyFields` (type: `boolean`):

Strip null and empty fields from output records to reduce payload size.

## `sentiment` (type: `boolean`):

Score each post and comment for sentiment — adds a `sentiment` field with a numeric score, a label (positive / negative / neutral), and a confidence value. Uses a fast lexicon heuristic.

## `includeRunMetadata` (type: `boolean`):

Append a single run-summary record at the end of the dataset (run ID, timing, item counts). It is marked itemType="runMetadata" and is added in addition to your matching records — filter on itemType to exclude it.

## `appConnector` (type: `string`):

Optional. Pick a connected app under Settings → API & Integrations to receive your scraped Reddit results. Notion is supported today (a run-summary page); other MCP connectors are best-effort as Apify expands its catalog.

## Actor input object example

```json
{
  "startUrls": [
    {
      "url": "https://www.reddit.com/r/programming/"
    }
  ],
  "searchTerms": [],
  "searchType": "posts",
  "sort": "hot",
  "time": "all",
  "includeNSFW": false,
  "maxItems": 5,
  "maxComments": 200,
  "includeCollapsed": true,
  "commentDepth": 10,
  "skipComments": false,
  "descriptionFormat": "all",
  "excludeEmptyFields": false,
  "sentiment": false,
  "includeRunMetadata": false
}
```

# Actor output Schema

## `results` (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 '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "startUrls": [
        {
            "url": "https://www.reddit.com/r/programming/"
        }
    ],
    "searchTerms": [],
    "maxItems": 5,
    "includeCollapsed": false,
    "descriptionFormat": "all",
    "excludeEmptyFields": false,
    "sentiment": false
};

// Run the Actor and wait for it to finish
const run = await client.actor("blackfalcondata/reddit-lead-scraper").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 '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "startUrls": [{ "url": "https://www.reddit.com/r/programming/" }],
    "searchTerms": [],
    "maxItems": 5,
    "includeCollapsed": False,
    "descriptionFormat": "all",
    "excludeEmptyFields": False,
    "sentiment": False,
}

# Run the Actor and wait for it to finish
run = client.actor("blackfalcondata/reddit-lead-scraper").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 '{
  "startUrls": [
    {
      "url": "https://www.reddit.com/r/programming/"
    }
  ],
  "searchTerms": [],
  "maxItems": 5,
  "includeCollapsed": false,
  "descriptionFormat": "all",
  "excludeEmptyFields": false,
  "sentiment": false
}' |
apify call blackfalcondata/reddit-lead-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=blackfalcondata/reddit-lead-scraper",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

```json
{
    "openapi": "3.0.1",
    "info": {
        "title": "Reddit Lead Scraper — Emails, Socials & Contact Info",
        "description": "Turn Reddit into a B2B lead list. Keep only records that expose a contact signal — email, social profile or external website — found across posts, comments and user profiles. AI-ready text included; no login or developer token needed.",
        "version": "0.1",
        "x-build-id": "tAkkHdMbhBuUahciw"
    },
    "servers": [
        {
            "url": "https://api.apify.com/v2"
        }
    ],
    "paths": {
        "/acts/blackfalcondata~reddit-lead-scraper/run-sync-get-dataset-items": {
            "post": {
                "operationId": "run-sync-get-dataset-items-blackfalcondata-reddit-lead-scraper",
                "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": {
                                "$ref": "#/components/schemas/inputSchema"
                            }
                        }
                    }
                },
                "parameters": [
                    {
                        "name": "token",
                        "in": "query",
                        "required": true,
                        "schema": {
                            "type": "string"
                        },
                        "description": "Enter your Apify token here"
                    }
                ],
                "responses": {
                    "200": {
                        "description": "OK"
                    }
                }
            }
        },
        "/acts/blackfalcondata~reddit-lead-scraper/runs": {
            "post": {
                "operationId": "runs-sync-blackfalcondata-reddit-lead-scraper",
                "x-openai-isConsequential": false,
                "summary": "Executes an Actor and returns information about the initiated run in response.",
                "tags": [
                    "Run Actor"
                ],
                "requestBody": {
                    "required": true,
                    "content": {
                        "application/json": {
                            "schema": {
                                "$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": {
                                    "$ref": "#/components/schemas/runsResponseSchema"
                                }
                            }
                        }
                    }
                }
            }
        },
        "/acts/blackfalcondata~reddit-lead-scraper/run-sync": {
            "post": {
                "operationId": "run-sync-blackfalcondata-reddit-lead-scraper",
                "x-openai-isConsequential": false,
                "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
                "tags": [
                    "Run Actor"
                ],
                "requestBody": {
                    "required": true,
                    "content": {
                        "application/json": {
                            "schema": {
                                "$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": {
                    "startUrls": {
                        "title": "🔗 Start URLs",
                        "type": "array",
                        "description": "Reddit URLs to scrape — subreddits, post pages, user profiles, community pages, or search result pages. Each URL determines what type of content is fetched.",
                        "items": {
                            "type": "object",
                            "required": [
                                "url"
                            ],
                            "properties": {
                                "url": {
                                    "type": "string",
                                    "title": "URL of a web page",
                                    "format": "uri"
                                }
                            }
                        }
                    },
                    "searchTerms": {
                        "title": "🔎 Search Terms",
                        "type": "array",
                        "description": "Search Reddit for these terms. Each entry becomes an independent search. Search posts are lightweight discovery records (plus their comments) — see Search Type.",
                        "items": {
                            "type": "string"
                        }
                    },
                    "searchType": {
                        "title": "🔎 Search Type",
                        "enum": [
                            "posts"
                        ],
                        "type": "string",
                        "description": "Type of results to return when using Search Terms. Post results are lightweight discovery records — id, url, title, subreddit and NSFW flag — plus their comment threads; scrape a result's URL directly for its full post fields (author, body, score, timestamp).",
                        "default": "posts"
                    },
                    "sort": {
                        "title": "📊 Sort",
                        "enum": [
                            "relevance",
                            "hot",
                            "top",
                            "new",
                            "comments"
                        ],
                        "type": "string",
                        "description": "Sort order for posts and search results.",
                        "default": "hot"
                    },
                    "time": {
                        "title": "🕒 Time Filter",
                        "enum": [
                            "hour",
                            "day",
                            "week",
                            "month",
                            "year",
                            "all"
                        ],
                        "type": "string",
                        "description": "Restrict subreddit-feed results to a time window (applies to Top sort on feeds; search is not time-windowed).",
                        "default": "all"
                    },
                    "includeNSFW": {
                        "title": "🔞 Include NSFW",
                        "type": "boolean",
                        "description": "Include posts and communities marked as NSFW (18+).",
                        "default": false
                    },
                    "postDateLimit": {
                        "title": "📅 Post Date Limit",
                        "type": "string",
                        "description": "Skip posts older than this ISO-8601 date (e.g. \"2024-01-01\"). Applies to subreddit feeds and post URLs; search results carry no date and are not filtered. Leave blank for no date limit."
                    },
                    "maxItems": {
                        "title": "🔢 Max Items",
                        "minimum": 1,
                        "type": "integer",
                        "description": "Maximum total records to save across all sources (posts, comments, users, communities).",
                        "default": 100
                    },
                    "maxComments": {
                        "title": "💬 Max Comments Per Post",
                        "minimum": 0,
                        "type": "integer",
                        "description": "Maximum number of comments to collect from each post page.",
                        "default": 200
                    },
                    "includeCollapsed": {
                        "title": "💬 Include Collapsed Comments",
                        "type": "boolean",
                        "description": "Expand and include comments that are initially collapsed (controversial or low-score). Enables deeper thread coverage, up to the comment and depth limits you set.",
                        "default": true
                    },
                    "commentDepth": {
                        "title": "🌳 Comment Depth",
                        "minimum": 1,
                        "type": "integer",
                        "description": "Maximum reply nesting depth to collect (1 = top-level only).",
                        "default": 10
                    },
                    "skipComments": {
                        "title": "⏭️ Skip Comments",
                        "type": "boolean",
                        "description": "Do not collect comments from post pages — output posts only.",
                        "default": false
                    },
                    "descriptionFormat": {
                        "title": "📄 Description Format",
                        "enum": [
                            "all",
                            "text",
                            "html",
                            "markdown"
                        ],
                        "type": "string",
                        "description": "Controls which body/description fields are included in output. \"all\" emits text + HTML + markdown variants.",
                        "default": "all"
                    },
                    "excludeEmptyFields": {
                        "title": "🧹 Exclude Empty Fields",
                        "type": "boolean",
                        "description": "Strip null and empty fields from output records to reduce payload size.",
                        "default": false
                    },
                    "sentiment": {
                        "title": "💬 Sentiment Analysis",
                        "type": "boolean",
                        "description": "Score each post and comment for sentiment — adds a `sentiment` field with a numeric score, a label (positive / negative / neutral), and a confidence value. Uses a fast lexicon heuristic.",
                        "default": false
                    },
                    "includeRunMetadata": {
                        "title": "📋 Include Run Metadata",
                        "type": "boolean",
                        "description": "Append a single run-summary record at the end of the dataset (run ID, timing, item counts). It is marked itemType=\"runMetadata\" and is added in addition to your matching records — filter on itemType to exclude it.",
                        "default": false
                    },
                    "appConnector": {
                        "title": "Send results to Notion (or another connected app)",
                        "type": "string",
                        "description": "Optional. Pick a connected app under Settings → API & Integrations to receive your scraped Reddit results. Notion is supported today (a run-summary page); other MCP connectors are best-effort as Apify expands its catalog."
                    }
                }
            },
            "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
                                    }
                                }
                            }
                        }
                    }
                }
            }
        }
    }
}
```
