fabric/extract-wisdom/dmiessler/extract-wisdom-1.0.0/README.md

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<img src="https://beehiiv-images-production.s3.amazonaws.com/uploads/asset/file/2012aa7c-a939-4262-9647-7ab614e02601/extwis-logo-miessler.png?t=1704502975" alt="extwislogo" width="400" height="400"/>

# `/extractwisdom`

`extract-wisdom` is a [Fabric](https://github.com/danielmiessler/fabric) pattern that _extracts wisdom_ from any text.

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[Description](#description) •
[Installation](#installation) •
[Examples](#examples) •
[Meta](#meta)

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> **NOTE**<br />
> These are not the correct instructions yet, so hold off until this note is removed.

## Description

**`extractwisdom` addresses the problem of **too much content** out there for us to consume.**

`extract-wisdom` _extracts wisdom_ from any content that can be translated into text. Some examples include:

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

It pulls multiple types of value out of any content it's provided, including:

- _IDEAS_: The best ideas from the content, i.e., what you might have taken notes on if you were taking manual notes
- _QUOTES_: Some of the best quotes from the content
- _HABITS_: Habits of the speakers that could be worth replicating
- _RECOMMENDATIONS_: A list of things that the content recommends

## Use cases

1. **Decision Support:** `extractwisdom` 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:** `extractwisdom` can also be used as your note taker. It's designed to

It can also be used as a set of notes.

## Examples

Here are some examples of how to use `extractwisdom`.

## Installation

You can install `extractwisdom` by executing this command.

```sh
curl -sS https://raw.githubusercontent.com/danielmiessler/fabric/main/install.sh | bash
```

```sh
z foo              # cd into highest ranked directory matching foo
```

```sh
z foo bar          # cd into highest ranked directory matching foo and bar
```

## Meta

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