content-digest_skill

This skill transforms long-form content into concise social posts and detailed narratives, extracting core insights and delivering two platform-ready formats.
  • Python

79

GitHub Stars

1

Bundled Files

2 months ago

Catalog Refreshed

4 months ago

First Indexed

Readme & install

Copy the install command, review bundled files from the catalogue, and read any extended description pulled from the listing source.

Installation

Preview and clipboard use veilstrat where the catalogue uses aiagentskills.

npx veilstrat add skill zephyrwang6/myskill --skill content-digest

  • SKILL.md16.4 KB

Overview

This skill transforms long-form content (YouTube videos, podcasts, interviews, articles) into two ready-to-publish formats: concise social posts and in-depth narrative articles. It extracts core insights, selects the most non-obvious points, and outputs short-form posts with numbered emoji lists and long-form pieces with a clear story arc. Use it to repurpose long transcripts into platform-appropriate content quickly.

How this skill works

Provide a URL or paste the full transcript/text and the skill reads the source end-to-end. It extracts a large set of viewpoints, filters for counterintuitive and high-depth insights, then selects 10–15 core insights. Those insights are used to generate a short-form social summary (300–800 characters with numbered emoji-style points) and a long-form narrative (1500–3000+ characters) that share the same insight foundation. If the input is unclear, it asks for the source or desired format.

When to use it

  • You have a podcast episode or YouTube interview and need a social-media-ready summary and a feature article.
  • You want to turn long research articles or reports into short, attention-grabbing posts plus an analytical long read.
  • You need consistent repurposing of recurring interviews for newsletter, blog, and social channels.
  • You want to surface non-obvious, second-order insights from long transcripts rather than a surface summary.
  • You require quotes, numbers, and narrative structure preserved for attribution and storytelling.

Best practices

  • Provide the full transcript or a direct link to the content for best results.
  • Specify desired output: short-form, long-form, or both; default is both if unspecified.
  • If available, include timing, guest name, or key timestamps to preserve accuracy of quotes and examples.
  • Expect the skill to surface counterintuitive and high-depth takeaways rather than obvious bullet points.
  • Review and add any missing context or proprietary details before publishing to ensure factual accuracy.

Example use cases

  • Convert a 90-minute interview into a 10-point social post and a 2,000-character feature for the company blog.
  • Turn a technical conference talk into a narrative case study with quotes, data points, and a clear climax and resolution.
  • Repurpose a long-form investigative article into a short-thread for Twitter/X and a companion long-form analysis for LinkedIn.
  • Create monthly podcast highlight posts that keep consistent style and reuse the same curated insights across formats.

FAQ

A YouTube/podcast/article URL or the full transcript/text. Specify short, long, or both if you have a preference.

How many insights will the outputs use?

Both short and long formats are built from the same 10–15 curated, high-depth insights selected from the full extraction process.

Will quotes and numbers be preserved?

Yes. The process preserves direct quotes and specific data when present in the source; include timestamps or context to maximize accuracy.

Built by
VeilStrat
AI signals for GTM teams
© 2026 VeilStrat. All rights reserved.All systems operational