# Chrome Extension Update Impact & Review Regression Intelligence (`obliging_persimmon_cki/chrome-extension-update-impact-review-regression-intelligence`) Actor

Compare Chrome Web Store reviews before and after an extension update and surface observational rating shifts, emerging complaints, worsening themes, coverage, and confidence.

- **URL**: https://apify.com/obliging\_persimmon\_cki/chrome-extension-update-impact-review-regression-intelligence.md
- **Developed by:** [Dung Huynh](https://apify.com/obliging_persimmon_cki) (community)
- **Categories:** Developer tools, Social media, Other
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

Pay per usage

This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have.

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

## 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

## Chrome Extension Update Impact & Review Regression Intelligence

### What this Actor does

This Actor does not simply scrape Chrome Web Store reviews. It compares public review quality before and after an extension update, then reports rating shifts, negative-review changes, emerging complaints, worsening or decreasing themes, feature requests, bounded evidence, coverage, and confidence.

Signals are observational. For example: “negative review signals increased after version 4.9.129 was published.” The Actor does not claim that a version caused a bug.

### Who it is for

Browser-extension developers, QA and support teams, product managers, agencies, researchers, and teams evaluating extension quality.

### Supported input

See [`sample-input.json`](sample-input.json) for the Store-test default. `extensions` accepts one to five Chrome Web Store IDs or listing URLs. The default is Dark Reader. `comparisonMode` supports `latest_update`, `custom_date`, and `recent_vs_previous`; `custom_date` requires `comparisonDate` in `YYYY-MM-DD` format. Each period contains 3–30 calendar days, and the deterministic analysis sample is capped at 10–200 reviews per period.

`language` selects the Chrome Web Store rendered locale/feed. Review-language detection is not independently verified, so non-English runs may include `LANGUAGE_FILTER_UNVERIFIED`.

### How comparison works

`latest_update` reads the current profile version and calendar update date. `custom_date` uses the supplied calendar date without claiming it is a published version. Both exclude the boundary day: with a July 15 boundary and seven-day windows, BEFORE is July 8–14 and AFTER is July 16–22. If the latest update is too recent, AFTER coverage is partial and the report includes `AFTER_WINDOW_INCOMPLETE`; it is not silently moved to another update. `recent_vs_previous` compares the two most recent complete calendar windows.

The collector uses the public profile over HTTP and the public rendered reviews page with bounded Playwright pagination. No Google login, CAPTCHA bypass, extension installation, source-code download, proxy, LLM, or user-supplied API key is required.

### Output

One Dataset item is emitted per requested extension, including failed extension items so other targets can finish. The report includes the current extension identity, boundary, BEFORE/AFTER metrics, impact direction and level, theme deltas, feature requests, short evidence excerpts, coverage, warnings, deterministic summary, and runtime statistics.

### Output fields

| Field                            | Meaning                                                               |
| -------------------------------- | --------------------------------------------------------------------- |
| `status`                         | `ok` or `failed` report status.                                       |
| `recordType`                     | Stable dataset record type.                                           |
| `extension.id`                   | Chrome Web Store extension ID.                                        |
| `extension.name`                 | Current listing name, when available.                                 |
| `extension.version`              | Current listing version, when available.                              |
| `extension.updatedDate`          | Current listing update date, calendar precision.                      |
| `boundary.effectiveMode`         | Comparison mode actually used after metadata fallback.                |
| `periods.before.reviewsAnalyzed` | Deterministic BEFORE sample size.                                     |
| `periods.after.reviewsAnalyzed`  | Deterministic AFTER sample size.                                      |
| `periods.before.averageRating`   | Mean star rating in BEFORE.                                           |
| `periods.after.averageRating`    | Mean star rating in AFTER.                                            |
| `impact.direction`               | `negative_shift`, `stable`, `positive_shift`, or `insufficient_data`. |
| `impact.level`                   | `low`, `medium`, `high`, or `unknown`.                                |
| `impact.ratingDelta`             | AFTER minus BEFORE average rating.                                    |
| `impact.negativeRateDelta`       | AFTER minus BEFORE share of 1–2 star reviews.                         |
| `impact.confidence.score`        | Evidence-quality score from 0 to 1; not causality probability.        |
| `impact.confidence.level`        | `low`, `medium`, or `high`.                                           |
| `emergingThemes`                 | New themes meeting bounded mention/share safeguards.                  |
| `worseningThemes`                | Existing themes with a material share increase.                       |
| `decreasingThemes`               | Themes with a material share decrease; not proof of improvement.      |
| `featureRequests`                | Bounded request titles, counts, and evidence.                         |
| `coverage.before.coverageStatus` | BEFORE `full`, `partial`, or `insufficient`.                          |
| `coverage.after.coverageStatus`  | AFTER `full`, `partial`, or `insufficient`.                           |
| `warnings`                       | Collection, source, locale, sample, or coverage warnings.             |
| `stats.reviewsScanned`           | Reviews retained from bounded source pagination.                      |
| `stats.reviewsAnalyzed`          | BEFORE plus AFTER analyzed samples.                                   |
| `stats.pagesFetched`             | Rendered review pages fetched.                                        |
| `stats.durationMs`               | Per-extension runtime.                                                |
| `summary`                        | Deterministic, non-causal human-readable summary.                     |
| `fetchedAt`                      | Run timestamp.                                                        |

### Limitations and error semantics

Chrome Web Store exposes a current profile update date rather than a trustworthy historical release list. Review version attribution is not treated as reliable in V1, so comparisons are date-based. Calendar dates do not provide an exact rollout timestamp. Review IDs may be unavailable; in that case the Actor uses a deterministic SHA-256 content fallback. Source markup, localized labels, and review pagination can change; the report preserves partial coverage and warnings when bounded collection cannot reach the requested window.

Hard per-extension failures use bounded error codes such as `PROFILE_UNAVAILABLE`, `REVIEWS_UNAVAILABLE`, and `NO_REVIEWS`. Low samples still produce a report with `insufficient_data` impact when possible.

### Cost and publishing

Playwright is used for review pagination, so the Actor is configured at 512 MiB. Pricing is unchanged by this implementation and was not modified automatically. The measured release gate is recorded in [`BENCHMARK_NOTES.md`](BENCHMARK_NOTES.md) and [`docs/publish-readiness-report.md`](docs/publish-readiness-report.md). This Actor is published in Apify Store under `DEVELOPER_TOOLS`; no pricing change is part of this release.

### Local development

```sh
npm install
npm test
npm run build
npm run lint
npm run format:check
npm run validate:schema
```

The runtime entrypoint is `src/main.js`; use `apify run --purge --input-file storage/key_value_stores/default/INPUT.json` for a local Actor smoke. No external model is used.

### FAQ

#### Does this prove that an update caused a bug?

No. It identifies changes in public review signals around a calendar boundary. Engineers should reproduce and verify individual reports.

#### What does `insufficient_data` mean?

Fewer than eight analyzed reviews were available for at least one period, or the source could not provide enough coverage. The report remains useful as a transparent collection result but should not drive a strong directional conclusion.

#### Does the Actor collect reviewer profiles?

No. It collects only bounded review fields needed for aggregate analysis and short evidence excerpts.

### Benchmark results

Local and cloud results are recorded in [`BENCHMARK_NOTES.md`](BENCHMARK_NOTES.md). The companion [`sample-benchmark.json`](sample-benchmark.json) is a fixture-shaped benchmark record, while the publication decision is recorded in [`docs/publish-readiness-report.md`](docs/publish-readiness-report.md).

# Actor input Schema

## `extensions` (type: `array`):

Chrome Web Store extension IDs or full listing URLs.

## `comparisonMode` (type: `string`):

Compare reviews around the current listing update, a custom calendar date, or two recent complete periods.

## `comparisonDate` (type: `string`):

Required only for custom\_date mode. The update day is excluded from both periods.

## `windowDays` (type: `integer`):

Number of complete calendar days in each period.

## `maxReviewsPerPeriod` (type: `integer`):

Maximum deterministic sample analyzed after the collector reaches the requested historical boundary.

## `language` (type: `string`):

Chrome Web Store locale used for the rendered review feed, such as en or de. This is not independent language detection.

## `includeEvidence` (type: `boolean`):

Include bounded short review excerpts for emerging and worsening themes.

## Actor input object example

```json
{
  "extensions": [
    "eimadpbcbfnmbkopoojfekhnkhdbieeh"
  ],
  "comparisonMode": "latest_update",
  "windowDays": 7,
  "maxReviewsPerPeriod": 50,
  "language": "en",
  "includeEvidence": true
}
```

# Actor output Schema

## `dataset` (type: `string`):

One structured observational report per requested Chrome Web Store extension.

## `runStatistics` (type: `string`):

Machine-readable bounded collection and runtime counters.

# 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("obliging_persimmon_cki/chrome-extension-update-impact-review-regression-intelligence").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("obliging_persimmon_cki/chrome-extension-update-impact-review-regression-intelligence").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 obliging_persimmon_cki/chrome-extension-update-impact-review-regression-intelligence --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,obliging_persimmon_cki/chrome-extension-update-impact-review-regression-intelligence"
        }
    }
}

```

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/BhDejXtGevQbfkyIr/builds/BJ4weWWiPhLmCeJe0/openapi.json