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steamgauge

Reads every Steam review of a game on your own computer: what players praise and criticise, how often, and the reviews behind every figure. A desktop app, with a command line and an MCP server for AI

Aureliolo/steamgaugecommunitylistedunreviewed
Use tool

Set up

Runs on your computer. Pick your agent and operating system.

This project does not publish an install method we can turn into a config. Follow the README instead.

README

synced Oct 21, 2026

SteamGauge

CI CodeQL Scorecard Rust Tauri 2 Training on Python Licence Latest release Downloads SLSA Build L3 SBOM SPDX Sigstore attested

A tool for finding out what players of a game actually think, rather than what the loudest reviews say.

Install

The installer and the portable archive for each system are in the latest release. A package manager installs it too:

# Windows, with winget: the installer
winget install Aureliolo.SteamGauge
# Windows, with Scoop: the portable program, with a Start menu shortcut
scoop install https://github.com/Aureliolo/steamgauge/releases/latest/download/steamgauge.json

# macOS on Apple Silicon, with Homebrew: this repository is the tap
brew tap aureliolo/steamgauge https://github.com/Aureliolo/steamgauge
brew install --cask aureliolo/steamgauge/steamgauge

Install has the rest: the installer and archive for each system, what each system needs, the first launch, verifying a download and upgrading.

Documentation

The documentation is published at https://aureliolo.github.io/steamgauge/ and lives in docs/.

  • Install: the files for each system, the first launch, checking a download and updating.
  • How it works: what it downloads, how it reads a review, and what each figure counts.
  • Accuracy: how often the reader is right, against what, in which languages, and what the figures cannot tell you.
  • AI assistants: the app's MCP server and the assistants it adds itself to.
  • MCP tools: every prompt and tool the MCP server offers and what each is given.
  • Command line: every command of the steamgauge program.
  • Architecture: how the parts fit and the rules they keep, for anyone changing SteamGauge.
  • Privacy: what stays on your computer and the four places the app connects to.

Models and dataset

The readers, the search models and the labelled claims are on Hugging Face, each release tagged v1, v2 and so on. The app fetches every file from one pinned commit and checks its length and SHA-256 before using it.

RepositoryDOI
ReaderAureliolo/game-review-reader10.57967/hf/10732
Reader, smallAureliolo/game-review-reader-small10.57967/hf/10734
Labelled claimsAureliolo/game-review-claims10.57967/hf/10735
Search encoderAureliolo/steamgauge-search-encoder
Search rerankerAureliolo/steamgauge-search-reranker
WriterAureliolo/steamgauge-writer

The search models are fp16 ONNX exports of Qwen3-Embedding-0.6B and Qwen3-Reranker-0.6B with their weights unchanged. The writer is Qwen3-4B-Instruct-2507 with its weights rounded to four bits. The dataset holds no review text and nothing about the authors: each labelled review carries a SHA-256 fingerprint of its text, and training/fetch_text.py fetches the reviews from Steam and puts the text back on your own machine.

Licence

Apache License 2.0. See LICENSE.

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