See the latest build of the project at: https://www.devi-a.com/FatalFrequenciesFrontend
This project was started as part of my work at the Expressive Intelligence Studio at the University of California, Santa Cruz. For the project, I was interested in exploring how we can use computational tools to help better visualize and provide suggestions for game masters of tabletop roleplaying games. This allows GMs to track what has happened in the game world, and uses knowledge of the current state (as well as a Prolog knowledge database) to provide suggestions for what can happen next.
This project uses the Fatal Frequencies scenario from the Gumshoe One-2-One system for this prototype. It features the characters, information, and clues from the game, as well as a sample of Prolog queries that could be useful to GMs. All text, including scene information and characters are taken from Fatal Frequencies, and are not my own creation. They are used here purely for research and demonstration purposes. To find more of this content and support the original authors, check out Cthulhu Confidential here: https://pelgranepress.com/product/cthulhu-confidential/
Download this repository, then run a localhost server in the folder's directory to get it up and running. For instance, if you have Python3 installed, enter the command python -m http.server, then navigate in your browser to http://localhost:8000/.
The majority of the content from the module has been extracted and rewritten in Prolog. You can access and edit this file in order to see the information in the game, and to add new Prolog queries to the website.
All graphs are rendered using Mermaid (https://mermaid-js.github.io/mermaid/#/). The initial starting graphs are preset based on the module's information, but can change based on input (for instance, nodes changing color when scenes are completed). The scene nodes are also clickable links.
The GM suggestions screen features Prolog queries that pull out patterns of characters, scenes, and clues that match specific queries. While this includes some examples here, in order to add more, you will want to write the Prolog query in the database.prolog file and add the call to that query in the main.js file.