Comparing Scene Action Generator and Verb Fuel

Scene Action Generator

Verb Fuel

This post will introduce and compare the Scene Action Generator tool and Verb Fuel resource. In the next post I'd like to play around with both the tool and the resource just for fun.

I use the word generator and tool for the Scene Action Generator because, to me, the categorization and groupings brings additional use and function that the alphabetized resource does not. The alphabetized resource is a fuel in the sense that is a just an uncategorized pool of words ready to add further meaning.

Pages

• Scene Action Generator is 2 pages, without any graphical cover, title page, nor table of contents.
• Verb Fuel is 12 pages with a cover, title page, and table of contents.

So, Verb Fuel leaving out the cover to table of contents, content wise, is 8 pages or four times more pages than the two pages of Scene Action Generator.

Content found in the table 

• Scene Action Generator has 6 broad categorized action types and in total has 144 rolled results–some of which have more than one keywords to pick from. An attempt was made to group somewhat similar words, especially for less drama-action–especially if they mean somewhat similar dynamics to scene action flow. Counting up all of the verbs on the table, there is just over 280 verbs categorized and grouped on the table
• Verb Fuel has 1,000 alphabetized rolled results. Each result has one verb or a contraction that contains a verb.

Example from the books

This is the example from Scene Action Generator.

• For example, a 1d12 roll resulting in 5 means a ‘social’ action type. Another 1d12 roll resulting in a 12 would indicate a either an ‘involve’ or ‘engage’ action. This might means that something is happening that involves or is engaged by more than one person. People or something else is joining in on the conflict in the scene.

This is the example from Verb Fuel.

• Example of using the Verb Fuel random verb table: The player rolls for a verb, rolling 0, 7, and 4 or = 074. Looking up 74 on the verb chart is the word “begin”. What does “begin” mean? That depends on what actually is beginning. Or maybe tense is important, maybe the action is not in the present tense. Maybe something began in the past. Or maybe something will begin in the future.

Sources

Scene Action Generator & Verb Fuel have the same origin actually. Verb Fuel radically changed in October to a more inspiring source.

• If I remember correctly, Scene Action Generator began as a concept by looking over lists of verbs for my fantasy languages. I wished for a very large list of verbs to helped build scenes randomly. Then after releasing the Plot Generator keywords, the list expanded and changed a bit until it went dormant for months. After resurrecting the project in October of 2018, I tried to think up the most popular adventure tasks. Categories of the verbs gradually emerged–which meant moving around words. And finally, story tasks verbs were collected until 144 results were filled.
• Verb Fuel actually began with the same initial idea to build a very large list of verbs to help build scenes randomly. Further than Scene Action Generator, the first hope was to build a list to 500 verbs. I can't remember when, but I came across a community content licensed source of words. Experimenting with that source, I began to figure out that what I wanted was more ownership of the resulting list. In October 15th of 2019, sick of community content source possibly limiting what I could do with the end result of the list, I came across a 1000 word public domain source of American English words. It was however unclassified and lacked parts of speech. However, fueled knowing that I could own the rights to the final product, unlike the community content source, I started from the beginning. I put parts of speech selectively onto this 900 words gleaned from the public domain source document using three dictionaries.
  
  When finished, about 400 verbs emerged. This initial list is too abstract academic, business, religious, and US government related. It lacked common everyday verbs that is more useful for stories. I started to add more common verbs. The 400 verb list quickly became 617. I did a quick draft to see if I could make a product late in October. The final list wasn't fully satisfying to me. I let it set for a week and then tried again, finding a few more sources of great verbs. After reaching 1000, I let it set a few days. Going back through the list, I replaced some verbs with better verbs.