UPDATE
Important update: Full English version now available
I have replaced the original beta download with a new English version:
https://drive.google.com/file/d/1G64Qs1s...sp=sharing This version takes part in the OpenAI Hackathon.
The first beta was primarily designed as a generic CSV importer. However, it did not fully represent the actual application and its curated data structure.
The new version is based directly on my complete personal dashboard and has now been translated into English. It includes the full example library of approximately 1,445 games and retains the more detailed information and filtering options of the original application.
The updated version includes:
Everything runs locally in the browser. There is no backend, no account and no cloud upload. The most recently loaded library may be stored locally in your browser.
I would especially appreciate feedback on:
Hi everyone,
Like many adventure fans, I've accumulated a backlog that's far bigger than I'll ever finish.
The question I kept asking myself wasn't:
Before you even think about exporting your own library, you can simply explore mine. The download already includes a real-world example library with around 1,400 games, so you can immediately see how the dashboard works and decide whether it's worth trying with your own collection.
If you like the idea, I'd love to hear how it works with libraries that look different from mine.
What it does
Game Library Explorer is a single HTML file.
Open it in your browser, load a CSV of your game library, and it becomes a searchable, filterable dashboard.
For example, you can quickly answer questions like:
Compatibility
So far I've tested it with:
Only a Title column is required. Everything else is optional.
Even a manually created spreadsheet works as long as it contains one row per game.
Why not just use SteamDB or Playnite?
Because they're solving a different problem.
SteamDB is focused on Steam.
Playnite is an excellent launcher and library manager.
Game Library Explorer focuses on exploring an existing library.
The biggest difference is personal curation.
Instead of relying only on store tags, you can organize your library the way you think about it.
For example:
Feedback welcome
Everyone is welcome to try it, whether your library contains 50 games or 5,000.
If you decide to test it, I'd be especially interested in feedback about:
If something is confusing, breaks, or simply feels awkward to use, I'd really like to know.
Real-world libraries always contain edge cases that synthetic test data doesn't.
Creating a CSV
Future plans
The current version is intentionally simple:
For now I'd rather make the core functionality as solid as possible.
Download old version
https://drive.google.com/file/d/1gsnM7ae...yy34u/view
Thanks to anyone willing to give it a try.
I'm much more interested in bug reports than compliments. If something doesn't work with your library, that's exactly the kind of feedback I'm looking for.
Important update: Full English version now available
I have replaced the original beta download with a new English version:
https://drive.google.com/file/d/1G64Qs1s...sp=sharing This version takes part in the OpenAI Hackathon.
The first beta was primarily designed as a generic CSV importer. However, it did not fully represent the actual application and its curated data structure.
The new version is based directly on my complete personal dashboard and has now been translated into English. It includes the full example library of approximately 1,445 games and retains the more detailed information and filtering options of the original application.
The updated version includes:
- the complete curated category structure
- separate playtime estimates for the main story and completionist playthroughs
- ratings and price information where available
- Steam tags
- platform and playing-status information
- search, sorting and combined filters
- the preloaded example library
- CSV upload with automatic and manual column matching, so you can also test it with your own library
Everything runs locally in the browser. There is no backend, no account and no cloud upload. The most recently loaded library may be stored locally in your browser.
I would especially appreciate feedback on:
- whether the application is intuitive to use
- whether the filters help you find suitable games
- whether the English terminology is clear
- whether CSV files from different launchers or library managers import correctly
- any genuine bugs or compatibility problems
Hi everyone,
Like many adventure fans, I've accumulated a backlog that's far bigger than I'll ever finish.
The question I kept asking myself wasn't:
Quote:"What games do I own?"It was:
Quote:"What adventure game do I already own that I haven't played yet, isn't too long, and is actually worth playing tonight?"Steam, GOG and Playnite are excellent at managing libraries, but they weren't quite answering that question the way I wanted. So I built a lightweight, local-first explorer focused on helping me rediscover my own collection.
Before you even think about exporting your own library, you can simply explore mine. The download already includes a real-world example library with around 1,400 games, so you can immediately see how the dashboard works and decide whether it's worth trying with your own collection.
If you like the idea, I'd love to hear how it works with libraries that look different from mine.
What it does
Game Library Explorer is a single HTML file.
Open it in your browser, load a CSV of your game library, and it becomes a searchable, filterable dashboard.
For example, you can quickly answer questions like:
- What unplayed Point & Click adventures under five hours do I own?
- What highly rated games have I completely forgotten about?
- What cozy games do I have?
- Which detective games haven't I finished yet?
- playtime
- rating
- status
- platform
- genres
- tags
- your own custom categories
- No installation
- No user account
- No cloud service
- Your library never leaves your computer
Compatibility
So far I've tested it with:
- Playnite exports
- representative Steam-style CSVs
- representative GOG-style CSVs
- title
- playtime
- rating
- status
- genres
- tags
- platform
Only a Title column is required. Everything else is optional.
Even a manually created spreadsheet works as long as it contains one row per game.
Why not just use SteamDB or Playnite?
Because they're solving a different problem.
SteamDB is focused on Steam.
Playnite is an excellent launcher and library manager.
Game Library Explorer focuses on exploring an existing library.
The biggest difference is personal curation.
Instead of relying only on store tags, you can organize your library the way you think about it.
For example:
- detective games
- winter games
- historical games
- cozy games
- short evening games
Feedback welcome
Everyone is welcome to try it, whether your library contains 50 games or 5,000.
If you decide to test it, I'd be especially interested in feedback about:
- Steam, GOG, Playnite or other library exports
- large libraries
- non-English titles
- duplicate games across multiple stores
- Unicode / encoding issues
- unusual CSV layouts
- unexpected filter results
If something is confusing, breaks, or simply feels awkward to use, I'd really like to know.
Real-world libraries always contain edge cases that synthetic test data doesn't.
Creating a CSV
- Playnite: Library → Export Library
- Steam: community tools such as steam-library-exporter or steam2csv
- GOG: community tools or a simple spreadsheet
Future plans
The current version is intentionally simple:
- one HTML file
- no backend
- no user accounts
- no cloud storage
For now I'd rather make the core functionality as solid as possible.
Download old version
https://drive.google.com/file/d/1gsnM7ae...yy34u/view
Thanks to anyone willing to give it a try.
I'm much more interested in bug reports than compliments. If something doesn't work with your library, that's exactly the kind of feedback I'm looking for.
This post was last modified: 07-22-2026, 12:28 PM by Wild Boar.
How AI tools were used
Being specific here on purpose, since the two components used different tools:
Game_Library_Explorer_EN.html was originally built with GPT-5.6 and Codex handling implementation, debugging, refactoring, and the interface. The project idea, feature design, data model, and testing were mine (Nadine). The category system was reworked after the initial build (see below), so "game categorization" is no longer solely mine — noting that here rather than leaving the original claim standing.
The Python pipeline (data enrichment) was built with Claude (Anthropic) doing the majority of the hands-on work — designing the four scripts, writing the disambiguation rules below, running full-file integrity verification after every batch edit, and catching/fixing a self-introduced data bug before it reached the live file. ChatGPT was used for parallel research batches (resolving ambiguous HowLongToBeat matches). Gemini contributed an alternative architectural idea (evaluating the third-party tool Playnite) that led to a structured test plan rather than a rewrite. This half of the project does not use Codex or GPT-5.6 — noting that explicitly rather than leaving it ambiguous.
The category system in Game_Library_Explorer_EN.html was reworked after the initial build, using neither Codex/GPT-5.6 nor the pipeline tools above. Claude derived and applied missing category tags systematically from each game's existing raw Steam tags (fixing cases where a game had the right underlying Steam data but was missing the matching curated filter — e.g. a survival-crafting game not showing up under "Survival"), added new category filters only where at least 10-20 games in the library genuinely supported them, and never removed or guessed a category. For the 268 games with no raw Steam tag data at all — where that method structurally can't work — ChatGPT researched each one individually against its Steam/GOG store page or a comparable source, citing the source per game and flagging anything it couldn't verify instead of guessing. Both passes were restricted to a fixed, pre-existing vocabulary of 76 category labels; nothing was invented.
Being specific here on purpose, since the two components used different tools:
Game_Library_Explorer_EN.html was originally built with GPT-5.6 and Codex handling implementation, debugging, refactoring, and the interface. The project idea, feature design, data model, and testing were mine (Nadine). The category system was reworked after the initial build (see below), so "game categorization" is no longer solely mine — noting that here rather than leaving the original claim standing.
The Python pipeline (data enrichment) was built with Claude (Anthropic) doing the majority of the hands-on work — designing the four scripts, writing the disambiguation rules below, running full-file integrity verification after every batch edit, and catching/fixing a self-introduced data bug before it reached the live file. ChatGPT was used for parallel research batches (resolving ambiguous HowLongToBeat matches). Gemini contributed an alternative architectural idea (evaluating the third-party tool Playnite) that led to a structured test plan rather than a rewrite. This half of the project does not use Codex or GPT-5.6 — noting that explicitly rather than leaving it ambiguous.
The category system in Game_Library_Explorer_EN.html was reworked after the initial build, using neither Codex/GPT-5.6 nor the pipeline tools above. Claude derived and applied missing category tags systematically from each game's existing raw Steam tags (fixing cases where a game had the right underlying Steam data but was missing the matching curated filter — e.g. a survival-crafting game not showing up under "Survival"), added new category filters only where at least 10-20 games in the library genuinely supported them, and never removed or guessed a category. For the 268 games with no raw Steam tag data at all — where that method structurally can't work — ChatGPT researched each one individually against its Steam/GOG store page or a comparable source, citing the source per game and flagging anything it couldn't verify instead of guessing. Both passes were restricted to a fixed, pre-existing vocabulary of 76 category labels; nothing was invented.
Playnite doesn't have CSV export built in, but there's a free extension called "Library Exporter Advanced" that does it:
In Playnite, go to Add-ons → Browse
Search for "Library Exporter Advanced" (not "CSV Export" — that's not the exact name, even though it does export to CSV)
Install it, then restart Playnite
Run the extension and save your CSV
Once you have the file, just use the "Import CSV" button in Game Library Explorer to load it. Let me know if you get stuck on any of these steps!
In Playnite, go to Add-ons → Browse
Search for "Library Exporter Advanced" (not "CSV Export" — that's not the exact name, even though it does export to CSV)
Install it, then restart Playnite
Run the extension and save your CSV
Once you have the file, just use the "Import CSV" button in Game Library Explorer to load it. Let me know if you get stuck on any of these steps!