Connect a Steam profile, import the owned games list, set a few preferences, then spin the wheel for a recommendation. The app is intended for people with enough Steam games that picking one has become its own chore.

What It Does

Imports your Steam library using your Steam profile and Steam Web API key.
Shows a large recommendation wheel using Steam game artwork.
Picks from your imported library with either weighted recommendations or true random mode.
Lets you adjust hard eligibility filters, such as whether to include unplayed or already-played games.
Lets you set preference weights for reviews, single-player/multiplayer, genre or Steam tags, and playtime.
Builds a shortlist of top candidate games.
Opens a separate debug window so you can inspect why a game was picked.

Current State

First-run setup wizard.
Local settings storage.
Steam owned-games import.
Recommendation wheel.
Shortlist view.
Settings modal.
Separate debug diagnostics window.
Background metadata enrichment for reviews, tags, genres, categories, and play mode where available.

Still evolving:

Metadata caching in SQLite.
Faster and more reliable Steam Store enrichment for very large libraries.
Better exclusion of non-game Steam apps once metadata caching is in place.
Launching selected games directly through Steam.
Completion-time integration.
Release automation for all platforms.

Requirements

You need:

A Steam account with public or API-accessible game details.
A Steam Web API key.
Node.js and npm for local development.
Rust/Cargo to build the Tauri desktop app.

The app does not ask for your Steam password.

Running Locally

Install dependencies first:

npm install

Run validation:

npm run local:check

Start the desktop app:

npm run local:dev

Build a local desktop release:

npm run local:build

Builds are written under:

src-tauri/target/release/

Setup Flow

On first run, the app asks for:

Steam profile, vanity URL, profile URL, or Steam ID.
Steam Web API key.
Optional time-to-beat provider placeholder.
Default session length.
Random mode preference.

Settings can be changed later from the cog button in the top bar.

Recommendations

The picker separates two kinds of filters:

Eligibility filters remove games from the candidate pool.
Preferred filters change weighting without removing games.

Preferred filters currently include:

Review signal.
Single-player or multiplayer/co-op preference.
Genre and Steam tag preference.
Playtime preference.

True random mode bypasses weighting and chooses from the eligible pool.

Debug Window

The Settings screen includes an Open Debug Window button. This opens a second desktop window that shows:

Current pick.
Active restrictions.
Score contributions.
Review data.
Genres.
Steam tags.
Categories.
Play mode metadata.
Candidate scores.

This is useful while tuning the recommendation logic.

Data And Privacy

Steam Backlog Helper is local-first.

Settings are stored locally.
The Steam API key is currently stored locally in SQLite during early development.
The app contacts Steam APIs and public Steam Store pages to import and enrich library data.
Library data is not sent to an app-owned server.

Before a public release, API key storage should move to OS-protected credential storage.

Documentation

Project planning lives in: