Simplify dense technical documentation into accessible explanations with before/after comparisons.
npx skills add https://github.com/try-works/role-model --skill eli5-try-works
Please help me install this Agent Skill. Skill: eli5 Source: https://github.com/try-works/role-model/tree/main/.agents/skills/eli5 Command: npx skills add https://github.com/try-works/role-model --skill eli5-try-works
ELI5 simplifies complex technical documentation into clear, accessible language, making it understandable for a broader audience.
Run ELI5 on the documentation folder located at /path/to/docs/folder/.
High-intent search queries and answers about installing and using this skill.
Simplifying technical documentation requires analyzing content to detect clarity issues and jargon. This Skill transforms dense technical content into accessible explanations, generating a before/after comparison report for developers, IT admins, and non-technical users.
Clarifying technical jargon involves detecting clarity issues and generating tech-adjacent metaphors for relatable analogies. This Skill transforms dense technical documentation into accessible explanations, making complex concepts understandable for non-technical users.
Generate a before/after comparison by running a simplification process on your documentation folder. This Skill analyzes content type, detects clarity issues, and outputs a report showing original content alongside simplified versions for easy documentation review.
Yes, the documentation simplification process requires Python, NLTK, and spaCy. These dependencies provide the necessary environment for analyzing content type, detecting clarity issues, and generating simplified explanations for technical documentation.
Yes, you can use this to simplify security and networking documentation. It analyzes complex product documentation, detects jargon and logic gaps, and generates accessible explanations using tech-adjacent metaphors for mixed audiences.
A limitation of automated jargon simplification is potential loss of exact technical accuracy. To mitigate this, the process includes an adversarial review step that evaluates the simplified explanations against the original technical content before finalizing the report.
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