Walrus Headline Creation
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Please install @user_7290fc8d/walrus01 by following https://skillhub.cn/install/skillhub.md.
About this skill
Problem
Turning hot topics into publishable posts often fails at filtering, rewriting, and quality control. A raw model output can sound mechanical, leak names, overstate impact, or omit source references.
How It Works
Walrus Headline Creation runs a five-step pipeline for content production:
- Source selection: uses Weibo Trending or AI Headlines, with trending topics as default, prioritizing heat, positive framing, and relevance to developers.
- Rewriting: preserves data, dates, organizations, and technical terms while reshaping the piece into a headline-article structure.
- Humanizing: invokes a humanizer pass to reduce stiff transitions, formulaic phrases, and overly balanced sentences.
- Review: checks facts, logic, style, safety, and anonymization, then outputs the final draft with a short audit summary.
It fits quick conversion of trending or AI news into publishable articles. It is not a real-time fact-checking or investigative tool, and it assumes the required source and polishing skills are available.
Use Cases
- An operations editor reviews 15 Weibo trending items and picks a positive, developer-relevant topic with a short rationale.
- A content editor rewrites an AI industry news item into a headline post, preserving data, organizations, and source while removing names.
- A self-media writer cleans up an AI-style draft into natural transitions, mixed sentence lengths, and less formulaic phrasing.
- Before publishing, the team checks facts, logic, AI tone, and name exposure, then outputs the final draft and audit summary.
Best For
- content operators responsible for Weibo trending selection and headline rewriting
- tech editors who need to turn AI industry news into publishable posts
- self-media writers who want to reduce AI-style phrasing in first drafts
- content reviewers checking facts, logic, and style before publication
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