fabric is an open-source framework for augmenting humans using AI. It provides a modular framework for solving specific problems using a crowdsourced set of AI prompts that can be used anywhere.
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README.md

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/extractwisdom

extract-wisdom is a Fabric pattern that extracts wisdom from any text.


DescriptionFunctionalityInstallationExamplesMeta


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Description

extractwisdom addresses the problem of too much content and too little time.

Not only that, but it's also too easy to forget the stuff do read, watch, or listen to.

The tool extracts wisdom from any content that can be translated into text, for example:

  • Podcast transcripts
  • Academic papers
  • Essays
  • Blog posts
  • Really, anything you can get into text!

Functionality

When you use extractwisdom, it pulls the following content from the input.

  • IDEAS
    • Extracts the best ideas from the content, i.e., what you might have taken notes on if you were doing so manually.
  • QUOTES
    • Some of the best quotes from the content.
  • REFERENCES
    • External writing, art, and other content referenced positively during the content that might be worth following up on.
  • HABITS
    • Habits of the speakers that could be worth replicating.
  • RECOMMENDATIONS
    • A list of things that the content recommends Habits of the speakers.

Use cases

The output can help you in multiple ways, including:

  1. Decision Support: Allows you to quickly learn what's in a particular piece of content so you can decide if you want to consume the full source material or not.
  2. Note Taking: Can also be used as your note taker. It's designed to replicate the type of capture that you might have done if you took notes manually.

Examples

Here are some examples of how to use extractwisdom.

Installation

You can install extractwisdom by executing this command.

curl -sS https://raw.githubusercontent.com/danielmiessler/fabric/main/install.sh | bash
z foo              # cd into highest ranked directory matching foo
z foo bar          # cd into highest ranked directory matching foo and bar

Meta

  • Author: Daniel Miessler
  • Published: January 5, 2024