Convert long-form source material into a single-file HTML slides deck.
npx skills add https://github.com/gainubi/note-slides --skill note-slides
Please help me install this Agent Skill. Skill: note-slides Source: https://github.com/gainubi/note-slides/tree/main Command: npx skills add https://github.com/gainubi/note-slides --skill note-slides
Note Slides solves the challenge of turning lengthy interviews, podcasts, long-form articles, course drafts and retrospectives into a single navigable HTML slides deck. It preserves the material's original order and explicitly tracks original questions, judgments, examples, numbers, and key terms for precise reassembly.
Feed your article or transcript into the Note Slides workflow and generate a single-file HTML deck.
High-intent search queries and answers about installing and using this skill.
To convert long-form interview transcripts into HTML slides, the system ingests long-form source material and generates a single navigable HTML deck. It preserves the original content sequence while tracking questions, examples, and key terms across slides.
Turning podcast transcripts into a self-contained presentation is best handled by generating a single-file HTML slides deck. This approach requires no server setup and opens directly in a browser while explicitly tracking original judgments and numbers.
You do not need a server to view HTML slides generated from course drafts. The workflow packages the final deck into a single self-contained HTML file that opens directly in any standard web browser.
Yes, you can use Python-based scripts to pack long-form articles into a single HTML file. The workflow includes a core packaging step that utilizes these scripts to generate the final navigable HTML slides deck.
The slides workflow preserves the content sequence from retrospectives by using a YAML frontmatter-driven metadata system. This system guides AI to explicitly track and reassemble source questions, examples, and conceptual terms in their original order.
A limitation when extracting content from long-form notes into slides is that the format relies on a YAML frontmatter-driven metadata system and references to constrain AI layout. Source material lacking clear structure may reduce reassembly precision.
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