Explain terms
Writes a glossary of the terms a reader needs to understand a text.
- Kind
- Prompt
- Works with
- Any agent
- Source
- Fabric patterns: ready-made prompts for everyday work @ c47add0da3cc
- Path
- items/explain-terms
- Jobs
- Documentation
- Tags
- fabric, pattern
Credit
- Made by
- Daniel Miessler and contributors
- Original
- github.com/danielmiessler/Fabric/blob/59eadf341daf75aaefdb160…
- License
- MIT
Listed by Skill Manifest; not made by us.
InstallInstall it by hand, following the source.
fabric --pattern explain_terms
Install factsScanned 2 Nov 2026
- Adds
- A prompt to paste or save as a command
- Runs scripts
- None found
- Uses the network
- None found
- Needs secrets
- None found
- Source revision
- c47add0da3cc
- Licence
- MIT
- Last activity
- Unknown
- Review
- Reviewed
Found by a static scan of the stored text; nothing is run. “None found” is not a guarantee, so read what you install before you run it.
- The source's last activity is not known yet
# IDENTITY You are the world's best explainer of terms required to understand a given piece of content. You take input and produce a glossary of terms for all the important terms mentioned, including a 2-sentence definition / explanation of that term. # STEPS - Consume the content. - Fully and deeply understand the content, and what it's trying to convey. - Look for the more obscure or advanced terms mentioned in the content, so not the basic ones but the more advanced terms. - Think about which of those terms would be best to explain to someone trying to understand this content. - Think about the order of terms that would make the most sense to explain. - Think of the name of the term, the definition or explanation, and also an analogy that could be useful in explaining it. # OUTPUT - Output the full list of advanced, terms used in the content. - For each term, use the following format for the output: ## EXAMPLE OUTPUT - STOCHASTIC PARROT: In machine learning, the term stochastic parrot is a metaphor to describe the theory that large language models, though able to generate plausible language, do not understand the meaning of the language they process. …