skill-content-repurposing

skill-content-repurposing is a skill for Claude Code, Codex from ZJU-REAL/Easel. It costs 159 tokens per session (1,291 once invoked), scanned A, original, Apache-2.0.

A tool that turns one long piece of content into separate posts or scripts for different platforms. It can work from text, a web link, or a video or audio transcript.

In plain words
What is it for?
Use it to adapt articles, video scripts, livestream transcripts, or podcasts into content for Xiaohongshu, Douyin, Bilibili, Weibo, and other platforms. It also creates a plan showing the source material's key points and the resulting pieces.
Why use it?
It removes the repetitive work of rewriting the same ideas for each platform's length, format, and audience expectations. It keeps the main argument and useful details while creating platform-specific versions.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to adapt articles, video scripts, livestream transcripts, or podcasts into content for Xiaohongshu, Douyin, Bilibili, Weibo, and other platforms. It also creates a plan showing the source material's key points and the resulting pieces.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/zju-real/easel/skill-content-repurposing
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add ZJU-REAL/Easel --skill skill-content-repurposing
Clone the repo
git clone --depth 1 https://github.com/ZJU-REAL/Easel

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for skill-content-repurposing

README.md
[![agentmods](https://agentmods.dev/badge/skills/zju-real/easel/skill-content-repurposing/github.svg)](https://agentmods.dev/skills/zju-real/easel/skill-content-repurposing)
Your own site
<a href="https://agentmods.dev/skills/zju-real/easel/skill-content-repurposing"><img src="https://agentmods.dev/badge/skills/zju-real/easel/skill-content-repurposing/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for skill-content-repurposing

Your own site · 80×15
<a href="https://agentmods.dev/skills/zju-real/easel/skill-content-repurposing"><img src="https://agentmods.dev/badge/skills/zju-real/easel/skill-content-repurposing.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 159 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,291 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00159 $0.01291
Opus 5 $0.00079 $0.00646
Sonnet 5 $0.00032 $0.00258
Haiku 4.5 $0.00016 $0.00129

Measured 9d ago against content hash a4bc7efea461, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

skill-content-repurposing scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/openclaw/skill-content-repurposing/SKILL.md · 112 lines

How it starts

The opening of the file, as written. The whole thing — 112 lines — stays where its author put it; the contents beside it link to each section on GitHub.

跨平台内容改编

将一篇长内容拆解为多平台原生素材,根据各平台特性适配格式、长度与语气,实现「一次创作,全域分发」。

输入

用户 prompt 中提供源内容,支持以下形式:

  • 文本:直接提供社媒帖子、公众号文章、视频脚本等文本
  • URL:提供内容链接(通过 WebFetch 抓取)
  • 视频/音频转录稿:提供短视频口播稿或直播文字版
  • 混合:源内容 + 指定目标平台

示例 prompt:

Execute /skill-content-repurposing
源内容:<B站视频脚本>
目标平台:小红书、抖音、微博

输出

输出包含两部分:

1. 改编计划

{
  "source_type": "blog_post",
  "source_word_count": 2000,
  "core_elements": {
    "thesis": "核心论点",
    "key_points": ["要点1", "要点2", "要点3"],
    "quotable_lines": ["金句1", "金句2"],
    "data_points": ["数据1"]
  },
  "target_platforms": ["twitter", "linkedin", "xiaohongshu"],
  "total_pieces": 8
}

2. 各平台改编内容

每个平台输出独立的、符合该平台原生格式的内容。具体转换规则参见 references/conversion-recipes.md

内容金字塔

本 SKILL 遵循三层内容金字塔方法论:

层级 说明 示例
支柱内容 (Pillar) 深度长内容 B站长视频、公众号长文、播客、直播回放
衍生内容 (Derivative) 中等长度,提取支柱内容的子主题 小红书图文、知乎回答、抖音口播脚本
微内容 (Micro) 短小精悍,单点突破 微博热评、抖音15秒、小红书封面金句卡

一篇支柱内容可衍生 15–25 个跨平台素材。SKILL 根据源内容类型自动规划金字塔拆解方案。

执行步骤

  1. 识别源内容类型

    • 判断源内容属于支柱层的哪种类型(B站视频 / 公众号文章 / 直播 / 播客)
    • 统计字数、段落数,评估内容密度
  2. 提取核心元素

    • 提炼核心论点(thesis)
    • 提取 3–5 个关键要点(key points)
    • 标记可引用金句(quotable lines)
    • 抓取数据点和案例(data points)
  3. 映射目标平台

    • 有 Profile:从 Profile 的 platforms 字段读取目标平台列表
    • 无 Profile:使用用户指定的平台,或默认为 小红书 + 抖音 + 微博
    • 根据 references/platform-specs.md 确定每个平台的格式要求
  4. 逐平台生成改编内容

    • 根据 references/conversion-recipes.md 中的转换配方执行改编
    • 每条内容必须是该平台的原生内容——不是简单截断或复制粘贴
    • 适配长度限制、语气风格、标签策略、格式规范
  5. 输出排期建议

    • 建议各平台的发布顺序和时间间隔
    • 原则:支柱内容先发 → 衍生内容次日起陆续发 → 微内容穿插填充

改编原则

  • 平台原生:每条内容读起来像是专门为该平台写的,不是机械裁剪
  • 核心一致:所有改编内容传达同一核心信息,不跑题不矛盾
  • 独立成立:每条内容单独阅读也完整有价值,不依赖用户看过源内容
  • 格式适配:严格遵守各平台的长度、格式、标签规则(见 references/platform-specs.md

Profile 感知

  • 有 Profile
    • platforms 字段读取目标平台列表,自动确定改编方向
    • tone / voice 字段读取语气风格,统一应用到所有改编内容
    • audience 字段读取目标受众,调整内容深度和表达方式
    • hashtag_strategy 字段读取标签偏好
  • 无 Profile
    • 要求用户指定目标平台(未指定则默认 小红书 + 抖音 + 微博)
    • 使用通用专业语气
    • 提示:"如提供账号 Profile(含平台和受众信息),可获得更精准的改编效果"

Read the full file on GitHub · 112 lines

Files

What ships with it

3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 9d ago First seen · 112 lines · 159 tokens per session scan A a4bc7efea461

Subscribe to this mod's changes

skill-content-repurposing is a skill published in the GitHub repository ZJU-REAL/Easel (494 stars, last pushed 2d ago), licensed Apache-2.0. It adds 159 tokens to every session and 1,291 once invoked, about $0.0008 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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