Generate structured reading notes from text, documents, webpages, and video URLs.
npx skills add https://github.com/jpcaparas/skills --skill reading-notes-jpcaparas
Please help me install this Agent Skill. Skill: reading-notes Source: https://github.com/jpcaparas/skills/tree/main/skills/reading-notes Command: npx skills add https://github.com/jpcaparas/skills --skill reading-notes-jpcaparas
This Skill turns various types of resources like notes, documents, webpages, and videos into structured reading notes, research leads, and homework todos, streamlining the process of information capture and review.
Use the reading-notes skill to transform the content of your research document into notes and todos.
High-intent search queries and answers about installing and using this skill.
Extracting reading notes and todos from a webpage or video URL involves parsing the resource content to produce structured summaries, topics, ideas, open questions, and actionable tasks.
Yes, you can export summarized research notes into multiple formats including Markdown, DOCX, PDF, CSV, XLSX, and JSON for streamlined information capture and review across different platforms.
Yes, you need Python3 and specific text processing libraries installed in your environment to generate structured notes from documents and text resources using this Skill.
The best way to summarize a long article into key points and actionable tasks is using a resource parsing tool that automatically identifies topics, extracts ideas, and generates research leads and homework todos.
Yes, this resource summarization tool works with both pasted text and video URLs, handling various input resources like notes, documents, and webpages to capture and review information.
jayhjenkinsNormalize files, URLs, and pasted text into citation-ready metadata with checksums.
jiunbaeExtract and convert text, tables, images, and metadata across PDF, DOCX, XLSX, PPTX formats.
aresbitSummarize URLs, local files, and video transcripts into concise summaries.
koasis89Create and manage notes using OMX persistent memory features.
