# Steam Review Intelligence 🎮 Reviews → AI Dev Report (`datakura/steam-review-intelligence`) Actor

Scrape Steam reviews ($0.10/1K) and turn them into an actionable AI report for game studios: complaint taxonomy, feature/patch requests, refund-risk & review-bomb signals, competitor mentions, and recommended actions.

- **URL**: https://apify.com/datakura/steam-review-intelligence.md
- **Developed by:** [Datakura Studio](https://apify.com/datakura) (community)
- **Categories:** AI, Developer tools, E-commerce
- **Stats:** 2 total users, 0 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $1.95 / ai insight report

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

## Steam Review Intelligence 🎮 — Reviews → AI Dev Report

**Stop reading thousands of Steam reviews by hand.** This Actor scrapes a game's Steam reviews and turns them into an actionable intelligence report written for game studios, publishers, and indie devs — complaint taxonomy, feature & patch requests, refund-risk signals, review-bomb detection, competitor mentions, and a prioritized action list.

Point it at any Steam AppID and get back both the **raw reviews** (for your own analysis) and a **ready-to-read AI report** (for your next stand-up).

***

### What you get

**1. Raw reviews** — every review as structured JSON: recommendation, playtime, helpful votes, language, timestamp, and full text.

**2. AI Insight Report** — the reviews distilled into decisions:

| Section | What it tells you |
|---|---|
| **Executive summary** | Recent sentiment vs lifetime score, and the 2–3 things that actually matter |
| **Complaint taxonomy** | Grouped themes with counts, severity, and a representative quote each |
| **Feature / patch requests** | What players keep asking for, ranked by frequency |
| **Refund-risk signals** | The first-session failures (crashes, FPS) that trigger refunds |
| **Review-bomb detection** | Separates current-build feedback from legacy grudges & protest votes |
| **Competitor mentions** | Which rival titles players compare you to, and why |
| **Recommended actions** | 5 concrete, prioritized moves for the team |

### Example output (real report)

Run on **Cities: Skylines II** (200 most recent English reviews):

> **Summary:** Recent sentiment (75% positive) is far above the lifetime "Mixed" score (57%), driven by goodwill toward the new developer. Residual negativity concentrates in three fixable areas: performance on mid-tier hardware (the #1 complaint), the mod platform experience, and DLC pricing. A large share of current negative reviews are launch-era grudges rather than reactions to the current build — making reputation-repair unusually high-leverage right now.
>
> **Top complaints:** Performance/optimization (31, high) · Crashes & save corruption (16, high) · Content thinner than predecessor (9) · DLC pricing resentment (8) · Traffic AI (7)
>
> **Recommended action #1:** Make empty-map FPS and first-session crashes the optimization KPI — profile the first 60 minutes on mid-tier hardware. This is the refund funnel, not the graphics ceiling.

### Input

| Field | Description |
|---|---|
| `appId` | Steam AppID (e.g. `949230`) or a `store.steampowered.com/app/<id>/` URL |
| `maxReviews` | How many recent reviews to analyze |
| `reviewType` | `all`, `positive`, or `negative` |
| `language` | Review language filter (e.g. `english`, `all`) |
| `generateReport` | Generate the AI report (on by default) |

### Pricing (pay per event — you only pay for what you get)

| Event | Price |
|---|---|
| AI insight report | **$1.95** per report |
| Reviews scraped | **$0.10** per 1,000 |
| Actor start | $0.02 per run |

No subscription, no rental fee, platform compute included free. A typical run (500 reviews + 1 report) costs about **$2**.

> **Tip:** if you set a "Max charge per run" limit, make it at least **$2.20** for a full run with the AI report. The Actor always respects your limit — it scrapes and charges only what fits, and skips the report (never charging for it) if the limit can't cover it.

### Use it from an AI agent (MCP)

This Actor is callable as an MCP tool via [Apify's MCP server](https://mcp.apify.com) — let your agent pull review intelligence on demand.

### FAQ

**Where does the data come from?** Steam's official public review API. Only publicly visible reviews; no personal data behind logins.

**How many reviews can I get?** Steam exposes reviews via cursor pagination — you can pull thousands per game.

**Something broke?** Open an issue on this Actor's page. Fixes ship within 24 hours.

***

*Built by datakura — data extraction tools that turn messy sources into decision-ready output.*

# Actor input Schema

## `appId` (type: `string`):

Numeric Steam AppID (e.g. <code>730</code>) or a full store URL (e.g. <code>https://store.steampowered.com/app/730/CounterStrike\_2/</code>).

## `maxReviews` (type: `integer`):

Maximum number of reviews to scrape (most recent first). Keep the default to try the Actor cheaply.

## `reviewType` (type: `string`):

Filter by recommendation.

## `reviewLanguage` (type: `string`):

Steam language code (e.g. <code>english</code>, <code>japanese</code>, <code>schinese</code>) or <code>all</code>.

## `generateReport` (type: `boolean`):

Turn scraped reviews into an actionable studio report: complaint taxonomy with counts & quotes, feature/patch requests, refund-risk & review-bomb signals, competitor mentions, and 5 recommended actions. Charged per report.

## `anthropicApiKey` (type: `string`):

Optional: bring your own Anthropic API key for the AI report. If omitted, the Actor's built-in key is used (no extra setup needed).

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

Proxy settings. Steam has no hard throttle; the default Apify Proxy is fine.

## Actor input object example

```json
{
  "appId": "730",
  "maxReviews": 200,
  "reviewType": "all",
  "reviewLanguage": "all",
  "generateReport": true,
  "proxyConfiguration": {
    "useApifyProxy": true
  }
}
```

# 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 = {
    "appId": "730"
};

// Run the Actor and wait for it to finish
const run = await client.actor("datakura/steam-review-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 = { "appId": "730" }

# Run the Actor and wait for it to finish
run = client.actor("datakura/steam-review-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 '{
  "appId": "730"
}' |
apify call datakura/steam-review-intelligence --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,datakura/steam-review-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/dOhItZgytlV2s2fWA/builds/jMHPalJdbd7xS6arg/openapi.json