# Substack newsletter monitor: weekly, only the new posts

**Use case:** 

A weekly watch on a Substack newsletter (Lenny's Newsletter): its 50 newest posts read each run with the body as HTML and text. The first run delivers every post; each later run delivers and charges only the posts no earlier run of this memory delivered, with first_seen_at and times_seen on each row; the free publication row counts the skipped (skipped_seen). Nothing new, nothing charged.

## Input

```json
{
  "startUrls": [
    "https://www.lennysnewsletter.com"
  ],
  "maxPostsPerPublication": 50,
  "includeBody": true,
  "onlyNew": true,
  "stateStoreName": "",
  "maxItems": 100
}
```

## Output

```json
{
  "row_type": {
    "label": "Row type",
    "format": "string"
  },
  "input_index": {
    "label": "Input #",
    "format": "integer"
  },
  "input_value": {
    "label": "Input",
    "format": "string"
  },
  "input_kind": {
    "label": "Input kind",
    "format": "string"
  },
  "status": {
    "label": "Status",
    "format": "string"
  },
  "status_detail": {
    "label": "Status detail",
    "format": "string"
  },
  "scraped_at": {
    "label": "Scraped at",
    "format": "string"
  },
  "post_id": {
    "label": "Post ID",
    "format": "integer"
  },
  "url": {
    "label": "URL",
    "format": "string"
  },
  "slug": {
    "label": "Slug",
    "format": "string"
  },
  "title": {
    "label": "Title",
    "format": "string"
  },
  "subtitle": {
    "label": "Subtitle",
    "format": "string"
  },
  "description": {
    "label": "Description",
    "format": "string"
  },
  "post_date": {
    "label": "Published",
    "format": "string"
  },
  "updated_at": {
    "label": "Updated",
    "format": "string"
  },
  "post_type": {
    "label": "Type",
    "format": "string"
  },
  "audience": {
    "label": "Audience",
    "format": "string"
  },
  "is_paywalled": {
    "label": "Paywalled",
    "format": "boolean"
  },
  "body_status": {
    "label": "Body status",
    "format": "string"
  },
  "body_html": {
    "label": "Body (HTML)",
    "format": "string"
  },
  "body_text": {
    "label": "Body (text)",
    "format": "string"
  },
  "truncated_body_text": {
    "label": "Teaser",
    "format": "string"
  },
  "wordcount": {
    "label": "Words",
    "format": "integer"
  },
  "cover_image": {
    "label": "Cover image",
    "format": "string"
  },
  "tags": {
    "label": "Tags",
    "format": "array"
  },
  "section_name": {
    "label": "Section",
    "format": "string"
  },
  "language": {
    "label": "Language",
    "format": "string"
  },
  "reaction_count": {
    "label": "Likes",
    "format": "integer"
  },
  "reactions": {
    "label": "Reactions",
    "format": "object"
  },
  "comment_count": {
    "label": "Comments",
    "format": "integer"
  },
  "child_comment_count": {
    "label": "Replies",
    "format": "integer"
  },
  "restacks": {
    "label": "Restacks",
    "format": "integer"
  },
  "has_voiceover": {
    "label": "Voiceover",
    "format": "boolean"
  },
  "podcast_url": {
    "label": "Podcast URL",
    "format": "string"
  },
  "podcast_duration": {
    "label": "Podcast seconds",
    "format": "number"
  },
  "authors": {
    "label": "Authors",
    "format": "array"
  },
  "author_name": {
    "label": "Author",
    "format": "string"
  },
  "author_handle": {
    "label": "Author handle",
    "format": "string"
  },
  "first_seen_at": {
    "label": "First seen",
    "format": "string"
  },
  "last_seen_at": {
    "label": "Last seen",
    "format": "string"
  },
  "times_seen": {
    "label": "Times seen",
    "format": "integer"
  },
  "publication_id": {
    "label": "Publication ID",
    "format": "integer"
  },
  "publication_name": {
    "label": "Publication",
    "format": "string"
  },
  "publication_url": {
    "label": "Publication URL",
    "format": "string"
  },
  "posts_delivered": {
    "label": "Delivered",
    "format": "integer"
  },
  "pages_read": {
    "label": "Pages read",
    "format": "integer"
  },
  "skipped_seen": {
    "label": "Skipped (seen before)",
    "format": "integer"
  },
  "verdict": {
    "label": "Verdict",
    "format": "string"
  },
  "verdict_detail": {
    "label": "Verdict detail",
    "format": "string"
  }
}
```

## How it works

### 1. Sign up on Apify or log in

The Substack Post Scraper: Newsletter Articles, Full Text & Likes Actor is ready to run with the inputs already set for "Substack newsletter monitor: weekly, only the new posts". [Sign up or log in](https://console.apify.com/create-task-from-example/tTsjVtmDvbZRlgAo4) and you'll land in Apify Console with a copy of this exact task.

### 2. Start the "Substack newsletter monitor: weekly, only the new posts" task

The Substack Post Scraper: Newsletter Articles, Full Text & Likes Actor will start running based on the input automatically. You can also change all the input fields, like publications or posts (urls), max posts per publication, and more, to match your specific use case.

### 3. Receive the "Substack newsletter monitor: weekly, only the new posts" output

Monitor the progress in real time. You will be notified as soon as your dataset is complete and ready for review. Each result includes data such as row type, input #, input, and more.

### 4. Integrate into your workflow

The final output is delivered in JSON, CSV, or Excel format, ready to be plugged into your workflow. You can also [run the "Substack newsletter monitor: weekly, only the new posts" task via API](https://apify.com/hyperbach/substack-scraper.md).

## About this Actor

This example demonstrates how to use [Substack Post Scraper: Newsletter Articles, Full Text & Likes](https://apify.com/hyperbach/substack-scraper.md) with a specific input configuration. Visit the [Actor detail page](https://apify.com/hyperbach/substack-scraper.md) to learn more, explore other use cases, and run it yourself.


## How to integrate an Actor?

This Task's input is already configured above. Use it as-is rather than inventing a new one.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For full API examples (JavaScript, Python, CLI, MCP, OpenAPI), see this Task's Actor page: https://apify.com/hyperbach/substack-scraper.md

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).