# Federal Register Regulatory Change Monitor (`quanmatrix/federal-register-regulatory-change-monitor`) Actor

Monitor new U.S. Federal Register documents as structured compliance and regulatory-intelligence data.

- **URL**: https://apify.com/quanmatrix/federal-register-regulatory-change-monitor.md
- **Developed by:** [Rafael Barreto Haddad](https://apify.com/quanmatrix) (community)
- **Categories:** Developer tools
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $14.00 / 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.
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?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
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.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — 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

## Federal Register Regulatory Change Intelligence Monitor

Monitor Federal Register topics as a recurring regulatory intelligence workflow. The Actor queries the official FederalRegister.gov API, keeps bounded state between runs when enabled, detects newly observed or materially updated documents, and returns one structured monitoring report per watch term. It is designed for compliance, legal operations, government affairs, procurement, policy research, and strategy teams that need to know what changed rather than repeatedly export raw search results.

### Why use this Actor

A conventional Federal Register scraper answers “what documents exist?” This Actor is built around a different operational question: “what changed since the last check, and which changes deserve attention first?” Persistent state converts repeated runs into a monitoring workflow. Each report includes counts, change status, newly detected documents, updated documents, source links, agencies, publication dates, abstracts, and a deterministic materiality score. The materiality heuristic uses document type and explicit language such as effective dates, deadlines, compliance requirements, penalties, final rules, and requests for comment. It is a triage tool, not legal advice.

### Key features

- Persistent run-to-run state for new and updated document detection.
- Official FederalRegister.gov API source with no browser automation.
- One decision-ready report per monitored term rather than one paid row per source document.
- Optional agency-name filtering after retrieval.
- Materiality ranking for current and changed documents.
- Bounded lookback, document limits, and state size for predictable execution.
- Structured errors instead of silent partial failures.
- No external LLM or paid third-party data dependency.

### Input

Provide `terms` as the watchlist. Optional `agencyFilters` narrow results by agency-name fragments. `lookbackDays` controls the historical search window, `maxDocumentsPerWatch` bounds inspected documents, `persistState` enables change detection across runs, and `includeUnchanged` optionally returns a compact sample of current unchanged documents. A useful production pattern is one Task per regulatory territory with scheduled execution.

### Output

Each dataset item is a monitoring report for one term. Core fields include `status`, `matchedDocuments`, `sourceReportedCount`, `changeCount`, `newCount`, `updatedCount`, `changes`, and `highestMateriality`. `INITIALIZED` means the watch has no previous state, `CHANGED` means new or updated documents were detected, and `NO_CHANGE` means the current fingerprints match the prior run for the retrieved set.

### Example

Input: `{"terms":["artificial intelligence"],"lookbackDays":30,"persistState":true}`. The first run establishes state and returns `INITIALIZED`. Later runs compare document fingerprints and surface new or updated Federal Register records with agency, publication date, links, abstract, and materiality score.

### Use cases

Use it for AI regulation, cybersecurity rules, privacy policy, banking regulation, healthcare regulation, environmental policy, labor rules, federal procurement, energy regulation, digital assets, or any other recurring Federal Register topic. Teams can schedule Tasks, feed structured reports into databases, send alerts from downstream automation, or use the dataset as a machine-readable regulatory watch surface.

### Pricing

Pay per event. One primary event is charged for each decision-ready watch report written to the default dataset. There is no separate start fee in the QuanMatrix pricing design. The product is intentionally report-priced rather than raw-document-priced so repeated monitoring remains understandable and aligned with the output users actually consume.

### Limitations

The materiality score is a deterministic triage heuristic and does not replace legal review. Federal Register API availability, search behavior, and metadata determine what can be detected. Agency filters are applied to the retrieved result set, so very broad terms combined with narrow agencies can require a larger document limit. A document disappearing outside the configured lookback window is not treated as a regulatory withdrawal. Persistent state is bounded and intended for recurring operational watchlists, not permanent archival storage.

# Actor input Schema

## `terms` (type: `array`):

Topics, products, rules, technologies, or regulated activities to monitor.

## `agencyFilters` (type: `array`):

Optional agency-name fragments. Leave empty for all agencies.

## `lookbackDays` (type: `integer`):

How far back each monitoring check searches.

## `maxDocumentsPerWatch` (type: `integer`):

Maximum documents inspected per term.

## `persistState` (type: `boolean`):

Compare later runs with the previous state to detect new or updated documents.

## `includeUnchanged` (type: `boolean`):

Also include a compact current-document sample in each report.

## Actor input object example

```json
{
  "terms": [
    "artificial intelligence"
  ],
  "agencyFilters": [],
  "lookbackDays": 30,
  "maxDocumentsPerWatch": 50,
  "persistState": true,
  "includeUnchanged": false
}
```

# Actor output Schema

## `dataset` (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("quanmatrix/federal-register-regulatory-change-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 = {}

# Run the Actor and wait for it to finish
run = client.actor("quanmatrix/federal-register-regulatory-change-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 '{}' |
apify call quanmatrix/federal-register-regulatory-change-monitor --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,quanmatrix/federal-register-regulatory-change-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/mSgiDsw0X7639AxJ9/builds/we4tGeoxmon9C9hb1/openapi.json