# Reddit Scraper — All Comments, Monitor Mode, Markdown ($1.5/1k) (`theoliveirad/reddit-comments-posts-scraper`) Actor

Scrape Reddit posts + 100% of the comment tree (97.6% benchmarked). Monitor mode: only new items on scheduled runs. Strict keyword search, date & flair filters, LLM-ready Markdown. No API key, no login. From $1.50 per 1,000 results.

- **URL**: https://apify.com/theoliveirad/reddit-comments-posts-scraper.md
- **Developed by:** [Diogo Oliveira](https://apify.com/theoliveirad) (community)
- **Categories:** AI, Lead generation, Social media
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $1.50 / 1,000 results

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event

## What's an Apify Actor?

Actors are 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/docs.md):

```bash
npm install apify-client
```

In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.md):

```bash
pip install apify-client
```

In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md):

````bash
# MacOS / Linux
curl -fsSL https://apify.com/install-cli.sh | bash
# Windows
irm https://apify.com/install-cli.ps1 | iex
```bash

In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/integrations/mcp.md).

If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).


# README

## Reddit Comments & Posts Scraper — Full Threads, Every Comment

Scrape Reddit posts, **complete comment trees**, subreddits, users, and search results. No API key, no login, no rate limits. Pure HTTP — fast and cheap.

### Why this scraper

**🧵 100% of the comment tree.** Most Reddit scrapers silently return only the comments that load on the page and skip the "load more comments" branches. This Actor recursively expands every `morechildren` stub until the tree is exhausted. If a cap is hit, items are explicitly flagged `commentsTruncated: true` — you always know whether a thread is complete.

**📡 Monitor mode.** Turn any input into a scheduled monitor: on each run, only posts and comments that are NEW since the previous run are returned. Brand mentions, keyword alerts, community tracking — without deduping downstream.

**🤖 LLM-ready output.** `outputFormat: "markdown"` adds one clean Markdown document per thread (post + threaded comments, ordered by score, with a `tokensEstimate` field), ideal for RAG pipelines, AI agents, and NotebookLM-style workflows. Token budgeting via `markdownMaxTopComments`. The doc comes on top of the structured items at no extra charge.

**🎯 Search that respects your keywords.** Reddit search is notoriously loose — the most common complaint against Reddit scrapers is "I searched X and got unrelated Y". Turn on `strictKeywordFilter` and every word of your query must actually appear in the post's title, body, or URL.

**📅 Date-range filters.** `postedAfter` / `postedBefore` and `commentedAfter` / `commentedBefore` (date or full ISO 8601). With `sort: "new"`, pagination stops early once posts fall outside your window — you don't pay for pages you don't need.

**🏷️ Flair filters.** `onlyWithFlair: true` or target specific flairs with `flairFilter: ["Discussion", "Help"]` (case-insensitive).

**🔎 Deep scan.** Reddit caps any listing at ~1,000 posts. `deepScan: true` combines every sort and time window and dedupes, surfacing several times more unique posts per subreddit.

**⚡ Pure HTTP.** No headless browser: faster runs, lower platform usage, fewer failures. Automatic anti-blocking with tiered proxy escalation — a 403 never kills your run.

**💶 Honest billing.** You pay per scraped item, with `maxItems` as a hard cost cap you control. Filtered-out posts don't count against your bill, truncation is always flagged, and the run status message reports exactly what happened.

### Live benchmark (July 12, 2026)

Real thread from r/AskReddit with **1,014 declared comments**:

| Method | Comments retrieved | Coverage |
|---|---|---|
| Inline page load only (what most scrapers return) | 491 | 48% |
| **This Actor (full 3-phase expansion)** | **990** | **97.6%** |

The remaining ~2% are deleted/removed comments — counted in Reddit's total but not retrievable by anyone. Total cost: 28 HTTP requests, ~40 seconds. Runs are always flagged `commentsTruncated` if any cap was hit, so partial data is never silent.

### Input examples

Monitor a keyword in one community (schedule this daily):

```json
{
  "searches": ["shopify"],
  "searchCommunityName": "ecommerce",
  "sort": "new",
  "monitorMode": true,
  "scrapeComments": false,
  "maxItems": 200
}
````

Full thread as LLM Markdown:

```json
{
  "startUrls": [{ "url": "https://www.reddit.com/r/webscraping/comments/abc123/example/" }],
  "outputFormat": "markdown",
  "maxCommentsPerPost": 2000
}
```

Archive a whole subreddit beyond the 1k cap:

```json
{
  "subreddits": ["MachineLearning"],
  "deepScan": true,
  "scrapeComments": false,
  "maxItems": 5000
}
```

Precise search: only posts that really mention your brand, from June 2026 onward:

```json
{
  "searches": ["acme widgets"],
  "strictKeywordFilter": true,
  "postedAfter": "2026-06-01",
  "sort": "new",
  "scrapeComments": false,
  "maxItems": 500
}
```

Flair-targeted community research:

```json
{
  "subreddits": ["ecommerce"],
  "flairFilter": ["Discussion", "Question"],
  "postedAfter": "2026-01-01",
  "scrapeComments": true,
  "maxCommentsPerPost": 300
}
```

### Output

Structured items with `dataType`: `post`, `comment`, `community`, `user`, or `thread_markdown`. Every item also carries a unified `content` field (post title / comment body) so mixed exports render cleanly in one column. Comments carry `parentId`, `depth`, and `threadPath` (e.g. `"c1/c2/c5"`) so you can rebuild the exact tree in one pass. All timestamps are ISO 8601 UTC. Export JSON, CSV, Excel via the Apify API or console.

```json
{
  "dataType": "comment",
  "id": "c2",
  "parentId": "t1_c1",
  "postId": "p1",
  "author": "alice_dev",
  "body": "Thanks, trying that now.",
  "score": 7,
  "depth": 1,
  "threadPath": "c1/c2",
  "isSubmitter": true,
  "createdAt": "2026-07-12T06:43:20+00:00",
  "permalink": "https://www.reddit.com/r/webscraping/comments/p1/x/c2/"
}
```

### Integrations

Works with the Apify MCP server (give AI agents direct access), n8n, Make, Zapier, LangChain, and the Apify API (Python/JS clients). Schedules + monitor mode = zero-infrastructure Reddit alerting.

### FAQ

**Do I need a Reddit account or API key?** No. Only publicly visible content is scraped.

**Legal?** Scraping publicly available data is generally permissible, but you are responsible for complying with applicable laws (including GDPR when storing usernames) and Reddit's terms for your use case. Intended uses: research, sentiment analysis, brand monitoring, AI/RAG datasets.

**Why are some threads flagged truncated?** You hit `maxCommentsPerPost`. Raise it (cost scales with results) — the flag exists so partial data is never silent.

# Actor input Schema

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

Any Reddit URLs: posts (full comment tree), subreddits, user pages, or search result URLs.

## `searches` (type: `array`):

Keywords to search across Reddit (or inside one community — see 'Restrict search to community').

## `searchCommunityName` (type: `string`):

Subreddit name (without r/) to scope all search terms to, e.g. 'ecommerce'.

## `subreddits` (type: `array`):

Subreddit names (without r/) to scrape, e.g. 'webscraping'.

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

Listing/search sort order.

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

Time filter for 'top' / 'controversial' / search sorts.

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

Hard cap on total results (posts + comments) — controls your cost.

## `maxPostsPerSource` (type: `integer`):

Cap on posts fetched from each subreddit/search/user source.

## `scrapeComments` (type: `boolean`):

Fetch the FULL comment tree for every post (all 'load more comments' branches expanded).

## `maxCommentsPerPost` (type: `integer`):

Cap per post. If hit, items are flagged commentsTruncated=true — you always know if a tree is partial.

## `commentsSort` (type: `string`):

Order used when expanding comment trees.

## `postedAfter` (type: `string`):

Only keep posts created on or after this date — 'YYYY-MM-DD' (00:00 UTC) or full ISO 8601. Tip: combine with sort='new' for fastest runs (pagination stops early once posts get older than this).

## `postedBefore` (type: `string`):

Only keep posts created on or before this date — 'YYYY-MM-DD' (23:59:59 UTC) or full ISO 8601.

## `commentedAfter` (type: `string`):

Only keep comments created on or after this date (UTC). 'YYYY-MM-DD' or ISO 8601.

## `commentedBefore` (type: `string`):

Only keep comments created on or before this date (UTC). 'YYYY-MM-DD' or ISO 8601.

## `onlyWithFlair` (type: `boolean`):

Drop posts without any flair assigned.

## `flairFilter` (type: `array`):

Keep only posts whose flair matches one of these values (case-insensitive, substring match) — e.g. 'Discussion', 'Help'. Leave empty to keep all flairs.

## `strictKeywordFilter` (type: `boolean`):

Reddit search often returns loosely related posts. When enabled, every word of your search term must actually appear in the post's title, body, or link URL — fewer results, but they match what you asked for.

## `deepScan` (type: `boolean`):

Combine all sorts and time windows per subreddit and dedupe, surfacing far more than the ~1k listing cap.

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

Include posts and comments marked NSFW (over\_18) in the results.

## `includeCommunityInfo` (type: `boolean`):

Push one community item (subscribers, description) per scraped subreddit.

## `includeUserInfo` (type: `boolean`):

Push one user item (karma, created date) per scraped user page.

## `outputFormat` (type: `string`):

'items' = structured post/comment rows only. 'markdown' and 'both' are IDENTICAL: structured items PLUS one LLM-ready Markdown document per thread (with a token estimate). You're billed per structured item either way — the Markdown doc is a free extra.

## `markdownMaxTopComments` (type: `integer`):

Keep only the N highest-scored top-level comment branches in Markdown output (token budgeting).

## `concurrency` (type: `integer`):

Parallel thread fetches (1-10). Higher = faster but more block risk.

## `monitorMode` (type: `boolean`):

Remembers what it already saw: on scheduled runs, only NEW posts/comments since the previous run are returned. Ideal for brand/keyword monitoring. Note: the memory is keyed to your sources + sort + time window — changing startUrls/searches/subreddits/sort/time starts fresh (the next run returns everything again).

## Actor input object example

```json
{
  "startUrls": [
    {
      "url": "https://www.reddit.com/r/webscraping/"
    }
  ],
  "sort": "top",
  "time": "week",
  "maxItems": 1000,
  "maxPostsPerSource": 5,
  "scrapeComments": true,
  "maxCommentsPerPost": 200,
  "commentsSort": "top",
  "onlyWithFlair": false,
  "strictKeywordFilter": false,
  "deepScan": false,
  "includeNSFW": false,
  "includeCommunityInfo": false,
  "includeUserInfo": false,
  "outputFormat": "items",
  "concurrency": 3,
  "monitorMode": false
}
```

# 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/webscraping/"
        }
    ],
    "sort": "top",
    "time": "week",
    "maxPostsPerSource": 5,
    "maxCommentsPerPost": 200
};

// Run the Actor and wait for it to finish
const run = await client.actor("theoliveirad/reddit-comments-posts-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/webscraping/" }],
    "sort": "top",
    "time": "week",
    "maxPostsPerSource": 5,
    "maxCommentsPerPost": 200,
}

# Run the Actor and wait for it to finish
run = client.actor("theoliveirad/reddit-comments-posts-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/webscraping/"
    }
  ],
  "sort": "top",
  "time": "week",
  "maxPostsPerSource": 5,
  "maxCommentsPerPost": 200
}' |
apify call theoliveirad/reddit-comments-posts-scraper --silent --output-dataset

```

## MCP server setup

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

```

## OpenAPI specification

```json
{
    "openapi": "3.0.1",
    "info": {
        "title": "Reddit Scraper — All Comments, Monitor Mode, Markdown ($1.5/1k)",
        "description": "Scrape Reddit posts + 100% of the comment tree (97.6% benchmarked). Monitor mode: only new items on scheduled runs. Strict keyword search, date & flair filters, LLM-ready Markdown. No API key, no login. From $1.50 per 1,000 results.",
        "version": "0.1",
        "x-build-id": "32cnd7tX2EdkkBcsy"
    },
    "servers": [
        {
            "url": "https://api.apify.com/v2"
        }
    ],
    "paths": {
        "/acts/theoliveirad~reddit-comments-posts-scraper/run-sync-get-dataset-items": {
            "post": {
                "operationId": "run-sync-get-dataset-items-theoliveirad-reddit-comments-posts-scraper",
                "x-openai-isConsequential": false,
                "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.",
                "tags": [
                    "Run Actor"
                ],
                "requestBody": {
                    "required": true,
                    "content": {
                        "application/json": {
                            "schema": {
                                "$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/theoliveirad~reddit-comments-posts-scraper/runs": {
            "post": {
                "operationId": "runs-sync-theoliveirad-reddit-comments-posts-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/theoliveirad~reddit-comments-posts-scraper/run-sync": {
            "post": {
                "operationId": "run-sync-theoliveirad-reddit-comments-posts-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": "Any Reddit URLs: posts (full comment tree), subreddits, user pages, or search result URLs.",
                        "items": {
                            "type": "object",
                            "required": [
                                "url"
                            ],
                            "properties": {
                                "url": {
                                    "type": "string",
                                    "title": "URL of a web page",
                                    "format": "uri"
                                }
                            }
                        }
                    },
                    "searches": {
                        "title": "Search terms",
                        "type": "array",
                        "description": "Keywords to search across Reddit (or inside one community — see 'Restrict search to community').",
                        "items": {
                            "type": "string"
                        }
                    },
                    "searchCommunityName": {
                        "title": "Restrict search to community",
                        "type": "string",
                        "description": "Subreddit name (without r/) to scope all search terms to, e.g. 'ecommerce'."
                    },
                    "subreddits": {
                        "title": "Subreddits",
                        "type": "array",
                        "description": "Subreddit names (without r/) to scrape, e.g. 'webscraping'.",
                        "items": {
                            "type": "string"
                        }
                    },
                    "sort": {
                        "title": "Sort",
                        "enum": [
                            "hot",
                            "new",
                            "top",
                            "controversial",
                            "rising",
                            "relevance"
                        ],
                        "type": "string",
                        "description": "Listing/search sort order.",
                        "default": "new"
                    },
                    "time": {
                        "title": "Time window",
                        "enum": [
                            "hour",
                            "day",
                            "week",
                            "month",
                            "year",
                            "all"
                        ],
                        "type": "string",
                        "description": "Time filter for 'top' / 'controversial' / search sorts."
                    },
                    "maxItems": {
                        "title": "Max items (total)",
                        "minimum": 1,
                        "type": "integer",
                        "description": "Hard cap on total results (posts + comments) — controls your cost.",
                        "default": 1000
                    },
                    "maxPostsPerSource": {
                        "title": "Max posts per source",
                        "minimum": 1,
                        "type": "integer",
                        "description": "Cap on posts fetched from each subreddit/search/user source.",
                        "default": 100
                    },
                    "scrapeComments": {
                        "title": "Scrape comments",
                        "type": "boolean",
                        "description": "Fetch the FULL comment tree for every post (all 'load more comments' branches expanded).",
                        "default": true
                    },
                    "maxCommentsPerPost": {
                        "title": "Max comments per post",
                        "minimum": 0,
                        "type": "integer",
                        "description": "Cap per post. If hit, items are flagged commentsTruncated=true — you always know if a tree is partial.",
                        "default": 2000
                    },
                    "commentsSort": {
                        "title": "Comments sort",
                        "enum": [
                            "top",
                            "new",
                            "controversial",
                            "old",
                            "qa"
                        ],
                        "type": "string",
                        "description": "Order used when expanding comment trees.",
                        "default": "top"
                    },
                    "postedAfter": {
                        "title": "Posts created on or after",
                        "type": "string",
                        "description": "Only keep posts created on or after this date — 'YYYY-MM-DD' (00:00 UTC) or full ISO 8601. Tip: combine with sort='new' for fastest runs (pagination stops early once posts get older than this)."
                    },
                    "postedBefore": {
                        "title": "Posts created on or before",
                        "type": "string",
                        "description": "Only keep posts created on or before this date — 'YYYY-MM-DD' (23:59:59 UTC) or full ISO 8601."
                    },
                    "commentedAfter": {
                        "title": "Comments created on or after",
                        "type": "string",
                        "description": "Only keep comments created on or after this date (UTC). 'YYYY-MM-DD' or ISO 8601."
                    },
                    "commentedBefore": {
                        "title": "Comments created on or before",
                        "type": "string",
                        "description": "Only keep comments created on or before this date (UTC). 'YYYY-MM-DD' or ISO 8601."
                    },
                    "onlyWithFlair": {
                        "title": "Only posts that have a flair",
                        "type": "boolean",
                        "description": "Drop posts without any flair assigned.",
                        "default": false
                    },
                    "flairFilter": {
                        "title": "Flair filter",
                        "type": "array",
                        "description": "Keep only posts whose flair matches one of these values (case-insensitive, substring match) — e.g. 'Discussion', 'Help'. Leave empty to keep all flairs.",
                        "items": {
                            "type": "string"
                        }
                    },
                    "strictKeywordFilter": {
                        "title": "Strict keyword filter (search)",
                        "type": "boolean",
                        "description": "Reddit search often returns loosely related posts. When enabled, every word of your search term must actually appear in the post's title, body, or link URL — fewer results, but they match what you asked for.",
                        "default": false
                    },
                    "deepScan": {
                        "title": "Deep scan (beat the ~1,000 post cap)",
                        "type": "boolean",
                        "description": "Combine all sorts and time windows per subreddit and dedupe, surfacing far more than the ~1k listing cap.",
                        "default": false
                    },
                    "includeNSFW": {
                        "title": "Include NSFW",
                        "type": "boolean",
                        "description": "Include posts and comments marked NSFW (over_18) in the results.",
                        "default": false
                    },
                    "includeCommunityInfo": {
                        "title": "Include community info",
                        "type": "boolean",
                        "description": "Push one community item (subscribers, description) per scraped subreddit.",
                        "default": false
                    },
                    "includeUserInfo": {
                        "title": "Include user info",
                        "type": "boolean",
                        "description": "Push one user item (karma, created date) per scraped user page.",
                        "default": false
                    },
                    "outputFormat": {
                        "title": "Output format",
                        "enum": [
                            "items",
                            "markdown",
                            "both"
                        ],
                        "type": "string",
                        "description": "'items' = structured post/comment rows only. 'markdown' and 'both' are IDENTICAL: structured items PLUS one LLM-ready Markdown document per thread (with a token estimate). You're billed per structured item either way — the Markdown doc is a free extra.",
                        "default": "items"
                    },
                    "markdownMaxTopComments": {
                        "title": "Markdown: max top-level branches",
                        "type": "integer",
                        "description": "Keep only the N highest-scored top-level comment branches in Markdown output (token budgeting)."
                    },
                    "concurrency": {
                        "title": "Thread fetch concurrency",
                        "minimum": 1,
                        "maximum": 10,
                        "type": "integer",
                        "description": "Parallel thread fetches (1-10). Higher = faster but more block risk.",
                        "default": 3
                    },
                    "monitorMode": {
                        "title": "Monitor mode (scheduled runs)",
                        "type": "boolean",
                        "description": "Remembers what it already saw: on scheduled runs, only NEW posts/comments since the previous run are returned. Ideal for brand/keyword monitoring. Note: the memory is keyed to your sources + sort + time window — changing startUrls/searches/subreddits/sort/time starts fresh (the next run returns everything again).",
                        "default": false
                    }
                }
            },
            "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
                                    }
                                }
                            }
                        }
                    }
                }
            }
        }
    }
}
```