# Reddit Sentiment Scraper — Analyze Posts & Comments (`blackfalcondata/reddit-sentiment-scraper`) Actor

Scrape Reddit and score every post and comment for sentiment — positive, negative or neutral with a confidence value. Search any subreddit or keyword to gauge how communities feel about a brand, product or topic. AI-ready text. No login or developer token needed.

- **URL**: https://apify.com/blackfalcondata/reddit-sentiment-scraper.md
- **Developed by:** [Black Falcon Data](https://apify.com/blackfalcondata) (community)
- **Categories:** AI, 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 Sentiment Scraper do?

Reddit Sentiment Scraper extracts Reddit posts and comments and scores every text-bearing record for sentiment — positive, negative, or neutral with a confidence value. Point it at any subreddit, keyword search, or specific thread to measure how communities feel about a brand, product, or topic. No Reddit account or login 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 -->
- **💬 Sentiment on every record** — every post and comment is scored automatically; a `sentiment` object with `score`, `label` (positive / negative / neutral), and `confidence` is attached to every text-bearing item.
- **📝 Posts and comments scored** — sentiment covers the full discussion tree, not just top-level posts; replies at any depth carry their own label and confidence.
- **🔎 Any subreddit, search, or thread** — seed from a subreddit feed, keyword search, or specific post URL to measure mood in any community or around any topic.
- **📊 Aggregate at scale for trends** — run on hundreds of posts to track brand or topic sentiment over time; export straight to a dashboard, spreadsheet, or data warehouse.
- **🤖 AI-ready text** — body text is emitted as clean text, HTML, and Markdown — pipe directly into LLMs, RAG pipelines, or MCP tools without extra cleanup.
- **🧹 Lean output** — choose a single description format and strip empty fields to keep dataset size down for high-volume runs.
- **🔑 No login or API key required** — point the actor at any public Reddit URL or keyword and run; no Reddit account or app registration needed.
<!-- KEY_FEATURES:END -->

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

Every post and comment carries a `sentiment` object added automatically by the built-in scoring engine:

```json
"sentiment": { "score": 4, "label": "positive", "confidence": 0.8 }
````

- **`score`** — numeric sentiment value (higher = more positive).
- **`label`** — one of `positive`, `negative`, or `neutral`. The scorer is conservative: a record is labelled positive or negative only when the signal is clear; ambiguous text defaults to neutral.
- **`confidence`** — a value between 0 and 1 indicating how strongly the text leans toward the assigned label.

Sentiment scoring is always on — every post and comment with readable text is scored. No input toggle is needed.

Beyond sentiment, records carry the full standard Reddit fields:

- **Posts** — `title`, body as text / HTML / Markdown, `score`, `upvoteRatio`, `numComments`, `awardCount`, `author`, `community`, `postType`, `language`, `createdAt`, and the canonical post `url`.
- **Comments** — `postId`, `parentId`, and `depth` for tree reconstruction, plus `score`, `awardCount`, `author`, `createdAt`, and body in text / HTML / Markdown.

Text bodies are emitted as clean text, HTML, and Markdown so the output feeds straight into LLMs, RAG datasets, and dashboards without extra cleanup.

### 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 4 more parameters

### Input examples

**Brand sentiment across Reddit** — Search for a brand name and score every matching post and comment for sentiment.

→ Posts and comments mentioning Tesla, each with a sentiment label and confidence.

```json
{
  "searchTerms": [
    "Tesla"
  ],
  "sort": "new",
  "maxItems": 100,
  "maxComments": 50
}
```

**Community sentiment in a subreddit** — Measure the overall mood of a subreddit by scoring its recent posts and comments.

→ Recent posts from r/apple and their comments, all sentiment-scored.

```json
{
  "startUrls": [
    {
      "url": "https://www.reddit.com/r/apple/"
    }
  ],
  "maxItems": 100,
  "maxComments": 100
}
```

**Topic sentiment tracking** — Track how Reddit feels about a topic by pulling top-ranked posts and scoring them.

→ Top posts about remote work with sentiment labels on every post and comment.

```json
{
  "searchTerms": [
    "remote work"
  ],
  "sort": "top",
  "maxItems": 200
}
```

**Quick sentiment pulse — recent mentions** — Grab the newest posts mentioning a product or keyword for a fast sentiment snapshot.

→ 25 recent posts mentioning ChatGPT, scored with comments.

```json
{
  "searchTerms": [
    "chatgpt"
  ],
  "sort": "new",
  "maxItems": 25,
  "maxComments": 50
}
```

### 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 post record with sentiment

```json
{
  "itemType": "post",
  "id": "t3_1tqwksq",
  "url": "https://www.reddit.com/r/technology/comments/1tqwksq/chatgpt_just_saved_me_hours_of_debugging/",
  "title": "ChatGPT just saved me hours of debugging",
  "body": "I was stuck on a race condition for two days. Asked ChatGPT, it spotted the issue in seconds. Genuinely impressed.",
  "score": 842,
  "upvoteRatio": 0.97,
  "numComments": 134,
  "awardCount": 3,
  "author": "dev_jasper",
  "community": "technology",
  "postType": "self",
  "language": "en",
  "createdAt": "2026-06-10T09:14:22.000Z",
  "sentiment": {
    "score": 4,
    "label": "positive",
    "confidence": 0.8
  }
}
```

### How to scrape reddit.com

1. Go to [Reddit Sentiment Scraper](https://apify.com/blackfalcondata/reddit-sentiment-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

- Track how a brand or product is perceived on Reddit over time — spot positive spikes after launches and negative dips after incidents.
- Compare sentiment toward competing products or services by running parallel searches and aggregating label distributions.
- Monitor a product launch: search the product name on launch day and score posts and comments as they appear.
- Market and audience research — understand what Reddit communities genuinely feel about a topic, not just what they say.
- Flag negative threads for support or PR response by filtering for high-confidence negative posts in relevant subreddits.
- Track community mood over time with scheduled runs on the same subreddit or keyword — export to a dashboard for trend analysis.

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

Reddit Sentiment 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 Sentiment Scraper with other apps?

Yes. Reddit Sentiment 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 Sentiment 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 Sentiment 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-sentiment-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 Lead Scraper — Emails, Socials & Contact Info](https://apify.com/blackfalcondata/reddit-lead-scraper?fpr=1h3gvi) — Turn Reddit into a B2B lead list. Keep only records that expose a contact signal — email, social.
- [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..
- [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.

## `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,
  "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
};

// Run the Actor and wait for it to finish
const run = await client.actor("blackfalcondata/reddit-sentiment-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,
}

# Run the Actor and wait for it to finish
run = client.actor("blackfalcondata/reddit-sentiment-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
}' |
apify call blackfalcondata/reddit-sentiment-scraper --silent --output-dataset

```

## MCP server setup

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

```

## OpenAPI specification

```json
{
    "openapi": "3.0.1",
    "info": {
        "title": "Reddit Sentiment Scraper — Analyze Posts & Comments",
        "description": "Scrape Reddit and score every post and comment for sentiment — positive, negative or neutral with a confidence value. Search any subreddit or keyword to gauge how communities feel about a brand, product or topic. AI-ready text. No login or developer token needed.",
        "version": "0.1",
        "x-build-id": "LQwtiE57erWa6yaPc"
    },
    "servers": [
        {
            "url": "https://api.apify.com/v2"
        }
    ],
    "paths": {
        "/acts/blackfalcondata~reddit-sentiment-scraper/run-sync-get-dataset-items": {
            "post": {
                "operationId": "run-sync-get-dataset-items-blackfalcondata-reddit-sentiment-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": {
                                "$ref": "#/components/schemas/inputSchema"
                            }
                        }
                    }
                },
                "parameters": [
                    {
                        "name": "token",
                        "in": "query",
                        "required": true,
                        "schema": {
                            "type": "string"
                        },
                        "description": "Enter your Apify token here"
                    }
                ],
                "responses": {
                    "200": {
                        "description": "OK"
                    }
                }
            }
        },
        "/acts/blackfalcondata~reddit-sentiment-scraper/runs": {
            "post": {
                "operationId": "runs-sync-blackfalcondata-reddit-sentiment-scraper",
                "x-openai-isConsequential": false,
                "summary": "Executes an Actor and returns information about the initiated run in response.",
                "tags": [
                    "Run Actor"
                ],
                "requestBody": {
                    "required": true,
                    "content": {
                        "application/json": {
                            "schema": {
                                "$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": {
                                    "$ref": "#/components/schemas/runsResponseSchema"
                                }
                            }
                        }
                    }
                }
            }
        },
        "/acts/blackfalcondata~reddit-sentiment-scraper/run-sync": {
            "post": {
                "operationId": "run-sync-blackfalcondata-reddit-sentiment-scraper",
                "x-openai-isConsequential": false,
                "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
                "tags": [
                    "Run Actor"
                ],
                "requestBody": {
                    "required": true,
                    "content": {
                        "application/json": {
                            "schema": {
                                "$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
                    },
                    "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
                                    }
                                }
                            }
                        }
                    }
                }
            }
        }
    }
}
```