# Greenhouse Job Delta Monitor (`accountable_eel/greenhouse-job-delta-monitor`) Actor

Stateful enterprise ATS delta monitoring actor for Greenhouse job boards. Detects newly posted roles against a persistent baseline Key-Value store. Charged per job posting returned. Boards with no result are free.

- **URL**: https://apify.com/accountable_eel/greenhouse-job-delta-monitor.md
- **Developed by:** [Adrian Voss](https://apify.com/accountable_eel) (community)
- **Categories:** Jobs, Business
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $0.50 / 1,000 job posting returneds

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

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

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
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.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## 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.

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 examples already wired to this Actor's own input schema, see the [API](#api) section below.

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`).

# README

## Greenhouse Job Delta Monitor: Get Only the Roles You Haven't Seen

Point this at a list of Greenhouse job boards, put it on a schedule, and each run hands back only the postings that were not on the board the last time it looked. One row per new job, with title, location, posting date and apply link. It reads Greenhouse's public board API directly, so there is no login and no page scraping.

### Who it's for

**A revenue-operations analyst at a sales-tooling vendor.** Your ideal customers are scaling SaaS companies, and a freshly opened "Head of Sales Operations" requisition is the best timing signal you will get. You keep 150 target accounts in a sheet, you do not want to reread 150 careers pages every Monday, and you do want a Slack message the day a matching role appears.

**A researcher at a small executive-search firm.** A venture fund hands you its portfolio list and asks which companies are hiring for finance leadership. You need the new roles each week, not the 700 that have been open since spring.

**A founder watching three competitors.** Hiring is the cheapest public view into where a rival is investing. A new cluster of machine-learning roles at one competitor tells you something no press release will.

All three need the same thing: the difference between this week and last week, delivered without re-sorting a full board.

### Why this one

- **You pay for new jobs, not for looking.** Billing is per job returned. A run in which nothing changed returns no jobs and costs only the run start fee.
- **Direct from the board API.** It calls `boards-api.greenhouse.io`, the endpoint Greenhouse's own embeds use. A redesigned careers page does not break it.
- **Your history lives in your account.** The list of jobs already seen is a key-value store in the Apify account that runs the actor, not in ours.
- **Safe against a spending cap.** If you set a maximum cost per run and it is hit, the jobs that were not delivered stay marked as new, so the next run still returns them.

### What you get

One row per newly detected posting. The columns are the same on every run:

| Field | Meaning |
| --- | --- |
| `job_id` | Greenhouse's numeric posting id, as text. This is the key the baseline uses. |
| `title` | The job title as posted. |
| `location` | The location name on the posting, for example "San Francisco" or "Remote". |
| `departments` | Always an empty array in practice. See the note below. |
| `posted_at` | Greenhouse's first-published time, falling back to last-updated. Returned as Greenhouse formats it, with its own UTC offset. |
| `url` | The apply page on the company's Greenhouse board. |
| `company_board_id` | The board token the row came from. |
| `first_seen_timestamp` | When this monitor first recorded the posting. |

**About `departments`.** Greenhouse's job-list endpoint does not include departments. On the four boards we checked on 2026-10-08 (stripe, airbnb, gitlab, figma) not one of 1,260 postings carried them, so the column is an empty list. This also means a keyword filter cannot match on department names. If you need departments, use the lookup actor listed under related actors; it makes the extra request this monitor skips.

### How the baseline works and how to reset it

The monitor keeps one record per board. Each record maps a job id to the moment it was first seen.

1. **Run one.** The store has no record for the board, so every open posting that passes your keyword filters counts as new and is returned and billed. On Stripe's board the first run returned 726 jobs, which is about $0.73.
2. **Run two onward.** The monitor fetches the board again and returns only job ids missing from the record. A posting that is closed and then reposted under a new id comes back as new.
3. **Where it is stored.** In a named key-value store, `greenhouse-delta-store` unless you set `deltaName`. Inside it, the key is `baseline-<board token>`, for example `baseline-stripe`.
4. **Keeping users apart.** Two schedules with different `deltaName` values keep completely separate baselines, even for the same board. Use one name per person or per sheet.
5. **Seeding without a bill.** Turn on `skipFirstRun` and the first run only writes the baseline, limited to the postings your keyword filter lets through, and returns nothing, so you pay for new jobs from run two on.
6. **Resetting.** To make one board look brand new again, open Storage, then Key-value stores, open the store, and delete the `baseline-<token>` key. To reset every board, delete the store. The next run is a first run again.

**Filters, caps and the baseline.** The stored record lists only postings that were actually handed to you. A posting hidden by `includeKeywords` or `excludeKeywords` is never written to it, so widening the filter later delivers that posting as new on the next run. The same goes for postings cut by `maxResults`, postings left unbilled when a spending limit stops the run, and a whole batch whose write to the dataset failed: none of them is recorded, so none is lost. Reset is only needed when you want already delivered postings again.

### Pricing

- **Job posting returned**: $1 per 1,000 job postings

Plus a $0.00005 start fee per run. Each event above is billed independently, only when it actually returns data — misses (`found:false`) are never charged.

Because the unit is the job, the first run is the expensive one. A 700-job board costs roughly $0.70 once, and a typical weekly delta of a handful of postings costs a fraction of a cent. Setting `skipFirstRun` removes the first-run charge entirely.

### How to use

1. **In the Apify Console.** Open the actor page and click **Start** — the `company_board_id` field is already pre-filled with a working example. Results land in the run's dataset as soon as each item is found.
2. **Via the API.** Call it directly with a POST request — no Console needed once you have an API token:
   ```bash
   curl "https://api.apify.com/v2/acts/accountable_eel~greenhouse-job-delta-monitor/run-sync-get-dataset-items?token=<YOUR_TOKEN>" \
     -X POST \
     -H "Content-Type: application/json" \
     -d '{"company_board_id":["stripe"]}'
   ```
3. **On a schedule.** Save this actor as an Apify **Task** with the input you want, then add a **Schedule** (hourly, daily, weekly) so it runs on its own — no server of your own required.

Paste a bare token such as `stripe`, or the full careers URL. Both `boards.greenhouse.io/stripe` and `job-boards.greenhouse.io/stripe` are recognised.

### Input

```json
{
  "company_board_id": [
    "stripe"
  ]
}
```

Greenhouse board token or full URL (e.g. "stripe" or "https://boards.greenhouse.io/stripe"). Charged per job posting returned. Boards with no result are free. Accepted formats: stripe, https://boards.greenhouse.io/stripe.

The other settings are `includeKeywords` and `excludeKeywords` (case-insensitive, matched against title and location), `maxResults` (a cap on rows per run; postings beyond it stay new for the next run), `testRun` (only the first five boards), `onlyFound` (hide the rows for boards that could not be read), `deltaMode` (on by default; turn it off to return every job on every run), `deltaName` and `skipFirstRun`.

### Sample output

| query | found | status | job_id | title | location | departments | posted_at | url | company_board_id | first_seen_timestamp | scrapedAt |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| stripe | true | OK | <job id> | <title> | <location> | <departments> | <posted date> | <apply url> | <board token> | <first seen timestamp> | 1970-01-01T00:00:00.000Z |

A board that does not exist comes back as one `found: false` row with the status `NOT_FOUND`. Any other API failure is reported with the status `ERROR`. Neither is billed.

### Use it from Clay, n8n, Make, or an AI agent

This actor runs synchronously over plain HTTP — call it directly from a script, a workflow tool, or an AI agent, no Apify Console needed once you have an API token.

```bash
curl "https://api.apify.com/v2/acts/accountable_eel~greenhouse-job-delta-monitor/run-sync-get-dataset-items?token=<YOUR_TOKEN>" \
  -X POST \
  -H "Content-Type: application/json" \
  -d '{"company_board_id":["stripe"]}'
```

**n8n.** Add an HTTP Request node: Method `POST`, URL `https://api.apify.com/v2/acts/accountable_eel~greenhouse-job-delta-monitor/run-sync-get-dataset-items?token=<YOUR_TOKEN>`, Body Content Type `JSON`, JSON Body `{"company_board_id":["stripe"]}` (swap in an expression from an earlier node for a real value).

**Clay.** Add an "HTTP API" column: Method `POST`, URL `https://api.apify.com/v2/acts/accountable_eel~greenhouse-job-delta-monitor/run-sync-get-dataset-items?token=<YOUR_TOKEN>`, Body `{"company_board_id":["{{job posting}}"]}`, mapping the row's job posting into the `company_board_id` array.

**MCP.** In Claude, Cursor, or any MCP client with the Apify MCP server, ask for "Greenhouse Job Delta Monitor | Apify" — the agent will find and run this actor.

### Tips

- **An empty dataset is the normal result of a quiet run.** There is no "nothing new" row. To tell a quiet run from a broken one, look at the run status and the final log line, which reports how many rows were emitted.
- **Find the token in the careers URL.** For `boards.greenhouse.io/acme`, the token is `acme`. It is usually the company name, but not always.
- **Start with `testRun`.** It limits the run to the first five boards while you confirm that your tokens resolve.
- **Pipe the rows somewhere that alerts.** The useful setup is a schedule, then a webhook into n8n or Make, then a Slack or email step that fires only when the dataset is non-empty.
- **Mind the first run on big boards.** Run a large list with `skipFirstRun` on, or accept a one-time charge of about a tenth of a cent per open posting.

### vs. alternatives

| | What it costs | What you get | Trade-off |
| --- | --- | --- | --- |
| **This actor** (`greenhouse-job-delta-monitor`) | $0.001 per job returned, $0.00005 per run, nothing for a quiet run | New postings only, with a first-seen timestamp, kept in your own store | Greenhouse only, no departments, and the first run bills the whole board unless you seed it |
| **Greenhouse Jobs Lookup** (`greenhouse-jobs-lookup`) | Billed per company, listed at $0.012 per board found | The whole board each time, with departments, richer filters and its own optional new-only mode | When your list is short or you want departments, this is the better choice. It also wins on a board that posts 12 or more new jobs between runs, because one board costs the same however many jobs it holds. |
| **Greenhouse's own API** | Free | The same JSON | You write the seen-list, the retries, the scheduling and the flattening yourself |

Prices for the sibling actor are the figures on its page at the time of writing; check it before relying on the comparison.

### FAQ

#### Why did my second run come back empty?

Because nothing new was posted. The monitor returns only job ids it has not recorded, and a board with no changes yields zero rows and no charge beyond the run start fee.

#### Does it tell me when a job is taken down?

No. It only reports additions. A closed posting simply stops appearing in the board response.

#### What happens if I add a company to the list later?

That board has no record yet, so its first run returns every open job. Add it with `skipFirstRun` on if you would rather not be billed for its backlog.

#### Can I run it without delta mode?

Yes. Set `deltaMode` to false and every run returns every job your filter keeps, billed in full, still stamped with the time each was first seen.

### Related actors

- [Greenhouse Jobs Lookup](https://apify.com/accountable_eel/greenhouse-jobs-lookup) is the per-company lookup with departments and filters, for a snapshot rather than a feed.
- [ATS Jobs Unified Lookup](https://apify.com/accountable_eel/ats-jobs-unified-lookup) works out which applicant-tracking system a company uses when you do not know.

# Actor input Schema

## `company_board_id` (type: `array`):

Greenhouse board token or full URL (e.g. "stripe" or "https://boards.greenhouse.io/stripe"). Charged per job posting returned. Boards with no result are free. Accepted formats: stripe, https://boards.greenhouse.io/stripe. You're only charged for the ones we actually find — a miss costs nothing.

## `testRun` (type: `boolean`):

Turn this on to test your input on a small sample before running the full list. Turn it off to process everything.

## `onlyFound` (type: `boolean`):

Only keep rows where something was actually found. Misses are always free, whether or not you show them here.

## `includeKeywords` (type: `array`):

Optional. Only keep results that mention at least one of these words (e.g. a job title, a city, a product name). Leave empty to keep everything.

## `excludeKeywords` (type: `array`):

Optional. Drop any result that mentions one of these words. Leave empty to skip nothing.

## `maxResults` (type: `integer`):

Optional. Stop the run once this many results have been found — useful for a quick, cheap sample. Leave blank for no limit.

## `deltaMode` (type: `boolean`):

When true, compare active jobs against stored baseline and only emit new jobs.

## `deltaName` (type: `string`):

Optional Key-Value store name for persisting seen job IDs baseline.

## `skipFirstRun` (type: `boolean`):

If true and state store is empty, populates baseline without emitting rows.

## `columns` (type: `array`):

Choose which pieces of information to include in each result row. All are included by default.

## `maxConcurrency` (type: `integer`):

Parallel requests. Keep conservative — this target has no browser fallback, so getting blocked costs more than slow-and-steady.

## `proxyConfiguration` (type: `object`):

Apify Proxy config. Residential recommended for anti-bot-sensitive targets.

## Actor input object example

```json
{
  "company_board_id": [
    "stripe"
  ],
  "testRun": false,
  "onlyFound": false,
  "includeKeywords": [],
  "excludeKeywords": [],
  "deltaMode": true,
  "deltaName": "",
  "skipFirstRun": false,
  "columns": [
    "job_id",
    "title",
    "location",
    "departments",
    "posted_at",
    "url",
    "company_board_id",
    "first_seen_timestamp"
  ],
  "maxConcurrency": 5,
  "proxyConfiguration": {
    "useApifyProxy": true
  }
}
```

# 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 = {
    "company_board_id": [
        "stripe"
    ],
    "includeKeywords": [],
    "excludeKeywords": []
};

// Run the Actor and wait for it to finish
const run = await client.actor("accountable_eel/greenhouse-job-delta-monitor").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 = {
    "company_board_id": ["stripe"],
    "includeKeywords": [],
    "excludeKeywords": [],
}

# Run the Actor and wait for it to finish
run = client.actor("accountable_eel/greenhouse-job-delta-monitor").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "company_board_id": [
    "stripe"
  ],
  "includeKeywords": [],
  "excludeKeywords": []
}' |
apify call accountable_eel/greenhouse-job-delta-monitor --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,accountable_eel/greenhouse-job-delta-monitor"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/VnFzs89igE69rhdFL/builds/MJc1X1OJbA1hRAgYt/openapi.json