Official descriptionOpen source3d ago
Aureliolo/steamgauge
Reads every Steam review of a game on your own computer: what players praise and criticise, how often, and…
View on GitHub ↗Direct link · no redirect page
Official descriptionReads 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 assistants.
- Star count
- 1 ★ · Aureliolo/steamgauge · read from the GitHub search API · (checked 2026-10-16 20:00:20)
- Source
- read directly from its GitHub page · type: open-source project
- Harvest history
- first seen 2026-10-14 · last seen 2026-10-16 · seen 3× · listed by 1 sources
- Score
- score 103 · 1 ★ · 1 sources · repo
FAQ (answers come from our records)
How do I install it?
We did not find an install command for this repository (our install coverage is only about 4%). Check its README or releases page.
Who is it for?
We filed it under these tags: 开源项目. The tags come from the entry itself, not a taxonomy we imposed.
Who maintains it?
repository
Aureliolo/steamgauge；first catalogued 2026-10-14；last seen 2026-10-16。There is no official certification or quality rating here — we record sources and dates only.Third-party quality signals
SteamGauge
以下摘录自该仓库的 README（片段） · 在 GitHub 读完整 README →
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:
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 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.
| | Repository | DOI |
|---|---|---|
| Reader | Aureliolo/game-review-reader | 10.57967/hf/10732 |
| Reader, small | Aureliolo/game-review-reader-small | 10.57967/hf/10734 |
| Labelled claims | Aureliolo/game-review-claims | 10.57967/hf/10735 |
| Search encoder | Aureliolo/steamgauge-search-encoder | |
| Search reranker | Aureliolo/steamgauge-search-reranker | |
The search models are fp16 ONNX exports of Qwen3-Embedding-0.6B and Qwen3-Reranker-0.6B with
their weights unchanged. 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
reviews say.
Install
The installer and the portable archive for each system are in the
latest release. A package manager
installs it too:
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 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.
| | Repository | DOI |
|---|---|---|
| Reader | Aureliolo/game-review-reader | 10.57967/hf/10732 |
| Reader, small | Aureliolo/game-review-reader-small | 10.57967/hf/10734 |
| Labelled claims | Aureliolo/game-review-claims | 10.57967/hf/10735 |
| Search encoder | Aureliolo/steamgauge-search-encoder | |
| Search reranker | Aureliolo/steamgauge-search-reranker | |
The search models are fp16 ONNX exports of Qwen3-Embedding-0.6B and Qwen3-Reranker-0.6B with
their weights unchanged. 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
- Source
- github · https://github.com/Aureliolo/steamgauge
- Browse by field
- Open source
- Traction
- 1 ★
- added
- yesterday
More in Open source
Filed under
Every tag opens the full list for that filter. Counts are the live catalogue figures.