# Evidence-Grade Web Page Diff (`bmiller1009/website-evidence-monitor`) Actor

Capture normalized public web-page snapshots and compare later versions with deterministic, evidence-grade text diffs.

- **URL**: https://apify.com/bmiller1009/website-evidence-monitor.md
- **Developed by:** [Sentinel Signal](https://apify.com/bmiller1009) (community)
- **Categories:** Developer tools, Automation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $20.00 / 1,000 page 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?

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

## Evidence-Grade Web Page Diff

Evidence-Grade Web Page Diff captures a stable, normalized text snapshot of one public HTTPS page. A later run can compare that page with a caller-supplied snapshot and return bounded paragraph additions and removals for policy pages, terms, disclosures, public notices, or other text where a deterministic record matters.

This is a stateless page-diff product, not a persistent monitoring service. API-IFY does not retain named baselines or schedule future comparisons; callers retain and resubmit the snapshot, optionally using Apify schedules.

### Input

Provide a public HTTPS `url`. To compare a page, also provide the complete `WEBSITE_SNAPSHOT` object from an earlier run as `baseline`. The Actor verifies that baseline text matches its SHA-256 hash and that the prior source matches the final fetched page. Set `includeNormalizedText` when the dataset item should include the normalized body in addition to the reusable snapshot.

```json
{
  "url": "https://example.com/policy",
  "includeNormalizedText": false
}
```

Only HTTPS port 443 is supported. URL credentials, private targets, mixed public/private DNS responses, and redirects to private destinations are rejected. Before fetching the page, the Actor evaluates `robots.txt` for its configured user agent. A disallow rule produces a restricted, uncharged result.

### Output

Every charged successful run writes `WEBSITE_SNAPSHOT` to the default key-value store before publishing the dataset result. It contains `schemaVersion`, final `sourceUrl`, capture time, content hash, and normalized text. Normalized text is limited to 2,000,000 characters so every emitted snapshot remains valid as a future baseline; larger pages are rejected without charge. The default dataset receives a stable API-IFY envelope with the current and baseline hashes, change state, magnitude, classification, bounded additions and removals, and analyzer provenance. Navigation, scripts, styles, templates, footers, common consent banners, and hidden content are removed before comparison.

A new snapshot produces a result projection like this:

```json
{
  "status": "success",
  "result": {
    "classification": "snapshot",
    "currentHash": "af0270fac35233692c0ada7bb34efaf6bf81304c0d738eb645366f23d4fff70e",
    "snapshotKey": "WEBSITE_SNAPSHOT"
  }
}
```

See [`examples/sample-input.json`](examples/sample-input.json) and [`examples/sample-output.json`](examples/sample-output.json) for complete schema-valid contracts.

`RUN_SUMMARY` reports result status, HTTP requests and retries, bytes processed, duration, budget skips, and charged events. Invalid baselines, unsupported pages, robots restrictions, unsafe targets, and fetch failures produce explicit uncharged dataset records.

### Pricing

A new snapshot charges one `page-snapshot` event. A successful baseline comparison charges one `page-diff` event. The Actor checks the remaining event budget before network retrieval. Failed or restricted results are not charged. Current event prices are displayed by Apify.

### Privacy and operational behavior

API-IFY keeps no separate website database. Data is written only to the run's default Apify dataset and key-value store, where the caller controls retention and access. Published structures are sanitized for authorization values, API keys, tokens, passwords, secrets, private keys, and sensitive URL query parameters. The full request URL exists only in memory while retrieval is performed.

To run recurring comparisons, configure an Apify schedule and pass the previously retained snapshot into the next run. For support, provide the run ID, result `itemId`, and public page URL without credentials. Contact Sentinel Signal Systems through the support link on the Actor page.

# Actor input Schema

## `url` (type: `string`):

Public HTTPS page to capture and normalize.

## `baseline` (type: `object`):

A WEBSITE\_SNAPSHOT object from an earlier run.

## `includeNormalizedText` (type: `boolean`):

Include normalized page text in the dataset result as well as the reusable snapshot.

## Actor input object example

```json
{
  "url": "https://example.com/",
  "includeNormalizedText": false
}
```

# Actor output Schema

## `results` (type: `string`):

No description

## `snapshot` (type: `string`):

No description

## `runSummary` (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 = {
    "url": "https://example.com/"
};

// Run the Actor and wait for it to finish
const run = await client.actor("bmiller1009/website-evidence-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 = { "url": "https://example.com/" }

# Run the Actor and wait for it to finish
run = client.actor("bmiller1009/website-evidence-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 '{
  "url": "https://example.com/"
}' |
apify call bmiller1009/website-evidence-monitor --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,bmiller1009/website-evidence-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/s37g00WdMuDqABDnJ/builds/o31PClM354blqcA2Q/openapi.json