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Generaldvcrn

content-rewriter

Cross-platform content repurposer. Takes one piece of content and rewrites it for multiple Chinese social media platforms, adapting tone, format, length, and style.

Stars
15
Source
dvcrn/openclaw-skills-marketplace
Updated
2026-05-29
Slug
dvcrn--openclaw-skills-marketplace--content-rewriter
View on GitHubRaw SKILL.md

// install — copy + paste into any project

mkdir -p .claude/skills && curl -fsSL https://raw.githubusercontent.com/dvcrn/openclaw-skills-marketplace/HEAD/plugins/alexandrali1989-cell--content-rewriter/skills/content-rewriter/SKILL.md -o .claude/skills/content-rewriter.md

Drops the SKILL.md into .claude/skills/content-rewriter.md. Works with Claude Code, Cursor, and any agent that loads SKILL.md files from .claude/skills/.

Content Rewriter — 内容多平台改写器

Repurpose one piece of content across multiple platforms with native formatting.

When to Activate

Trigger when the user mentions: 改写, rewrite, 转载, cross-post, 多平台分发, repurpose, 内容复用.

Workflow

  1. Accept original content + list of target platforms
  2. Rewrite for each target platform independently

Rewriting Rules

→ 小红书 (from any platform)

  • Shorten to 300-800 characters
  • Add emoji every 2-3 sentences
  • Title: "number + keyword + emoji" format
  • Short paragraphs (1-3 sentences each)
  • Add 5-10 hashtags
  • Tone: bestie sharing / personal experience

→ 知乎 (from any platform)

  • Expand to 1000-2000 characters
  • Add logical structure (thesis → evidence → conclusion)
  • Include data citations and case studies
  • Tone: professional but approachable
  • Open with a direct answer to the core question

→ 公众号 (from any platform)

  • 1500-3000 characters
  • Add subtitles for sections
  • Open with empathy (pain point / story)
  • Close with elevation
  • Tone: deep but readable

→ 抖音 Script (from any platform)

  • Compress to 200-500 character oral script
  • First 3 seconds must hook
  • Conversational, avoid written language
  • Mark pauses and tone shifts
  • End with comment-driving CTA

Output Format

Generate each platform version as a standalone, ready-to-publish piece. Label each with platform name and word count.

Guidelines

  • Rewriting ≠ translating — match platform-native voice
  • Each version must be independently publishable
  • Check platform-specific banned words