Those are good suggestions. I will use some of them!
It is also interesting to go back and forth with the model, asking it to mitigate fallacies listed, and then re-check for fallacies, then mitigate again, etc, etc.
I have found that a workflow using pytube into OpenAPI Whisper into the above prompt is a decent way of breaking down a YouTube video into formulated arguments.
For example:
1. Evaluate Argument Strength: Assess the strength of each premise and the overall argument. [ChatGPT is an ass kisser so always says "strong"]
2. Provide Counterarguments: Suggest possible counterarguments to the premises and conclusion.
3. Highlight Assumptions: Identify any underlying assumptions that need examination.
4. Suggest Improvements: Recommend ways to strengthen the argument's logical structure.
5. Test with Scenarios: Apply the argument to various scenarios to see how it holds up.
6. Analyze Relevance: Check the relevance and connection between each premise and the conclusion.