# Greenhouse Job Edit Feed — Public Trial (`resolute_client/greenhouse-job-edit-feed`) Actor

Monitor 1–3 public Greenhouse boards for job-post changes. Get before/after title, location, URL, and normalized description. Baseline and no-change snapshots are charged. Public-post visibility only; hiring intent, filled status, paid demand, and profitability are unknown.

- **URL**: https://apify.com/resolute_client/greenhouse-job-edit-feed.md
- **Developed by:** [Kais](https://apify.com/resolute_client) (community)
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $10.00 / 1,000 board snapshots

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/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 Edit Feed — Public Trial

Track public Greenhouse job-post changes on 1–3 boards. Each record is keyed by (board, post_id) and includes the event type, source URL, observation time, run ID, and before/after values for title, location, URL, and normalized description text with a SHA-256 hash. This uses public job-post data only; it does not access private ATS data, applicants, or applications.

### Run it

Start with this input:

{"boards":\["webflow"],"namespace":"career-watchlist-demo"}

boards accepts 1–3 unique Greenhouse board tokens. namespace is required and must contain letters, numbers, underscore, or hyphen. The persistent baseline is isolated by the authenticated Apify account, namespace, and exact board scope. Account identity cannot be overridden through input. Use the same scope serially: the first complete run records baseline, and a later run reports content changes to the same post ID. Replaying unchanged data produces no change rows. A different namespace or board scope starts a new baseline.

### Output

Dataset rows contain event, board, integer post_id, before, after, changed_fields when relevant, source_url, observed_at, source_run_id, and deterministic event_id. before and after contain the public job fields and normalized description_text / description_hash. Output links expose the dataset events and a SUMMARY record; treat a run as complete only when SUMMARY.allBoardsCompleted and SUMMARY.datasetVerified are both true.

Actual Development baseline example: run sQQraqxCG4TgAjEpJ checked the public Webflow board, committed 23 existing jobs, and emitted 23 baseline rows. One row used board webflow and integer post_id 7951430; its before value was null and its after value included title, location, URL, updated_at, normalized description text, and description hash. This is one author QA run, not a customer run or a live edit. A baseline is existing inventory, not a new-job alert. added is a previously unseen ID after initialization; updated changes the existing record. timestamp_only does not notify. One complete absence is missing_candidate; only a second complete absence is closed. Returning posts are reappeared or reopened. A closed post is absent from complete public snapshots; this does not mean it was filled or hired.

Description comparison removes HTML tags and script/style content, decodes entities, and collapses whitespace. Case, Unicode, and text order remain significant; the Actor does not judge semantic equivalence. HTTP, parse, duplicate-ID, missing-description, or incomplete-count errors preserve the prior baseline and report board_error where output storage is available.

### Trial charges

The displayed Actor event price is $0.01 per successfully completed board snapshot, including the first baseline and an unchanged/no-change check, plus a $0.001 Actor-start event at 256 MB. There is no per-job or per-dataset-row event fee. The expected event-charge ceiling is $0.011 for one board and $0.031 for three boards, within the $0.05 default maximum charge per run. Platform-displayed prices are authoritative. Failed board fetch/parse work has no custom board-snapshot fee; a start fee may still apply. If storage fails after a confirmed charge, completion stays false and retry uses the same checkpoint without charging that snapshot again. Unknown charges require reconciliation and are never blindly resubmitted.

### Limits and evidence

The Actor accepts at most 1,000 current jobs per board, an 8 MiB raw API response, a 256 KiB raw description, a 4 MiB persistent board state, and an 8 MiB recovery checkpoint. Oversized or incomplete snapshots stop without advancing the baseline. Public requests have a 12-second timeout and snapshot work is limited to 110 seconds at 256 MB. No proxy escalation, paid external API, or AI is used.

This is a technical trial, not evidence of customer demand or profitability. The completed cloud checks covered one account and two namespaces; they did not test a real second customer or observe a live job-description edit. Synthetic fixtures cover description changes and other unobserved cases. The Actor does not infer hiring intent, filled roles, ghost jobs, or original publication dates, and makes no exclusivity claim.

# Actor input Schema

## `boards` (type: `array`):

1-3 public Greenhouse board tokens. Exact scope changes establish a new baseline.

## `namespace` (type: `string`):

Persistent baseline namespace, isolated by the authenticated runtime customer and exact board scope; no caller tenant overrides.

## Actor input object example

```json
{
  "boards": [
    "webflow"
  ],
  "namespace": "career-watchlist-demo"
}
```

# Actor output Schema

## `events` (type: `string`):

No description

## `summary` (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 = {};

// Run the Actor and wait for it to finish
const run = await client.actor("resolute_client/greenhouse-job-edit-feed").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 = {}

# Run the Actor and wait for it to finish
run = client.actor("resolute_client/greenhouse-job-edit-feed").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 '{}' |
apify call resolute_client/greenhouse-job-edit-feed --silent --output-dataset

```

## MCP server setup

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

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/vh4unYJcWiEzaoV8c/builds/iug4ZsOWS8Cp74CgY/openapi.json