Agent skill

Skill Cross Platform Diff

by ZJU-REAL in ZJU-REAL/Easel

跨平台内容差异深度分析。分析同一话题/内容在不同平台(小红书、抖音、B站、知乎、 微博、公众号、X 等)的呈现差异:内容形式、受众偏好、话语体系、流量逻辑、变现路径。

Apache-2.0Auto-check passedWriting & Content

Install Skill Cross Platform Diff

skills CLI
$ npx skills add ZJU-REAL/Easel --skill skill-cross-platform-diff -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install ZJU-REAL/Easel skill-cross-platform-diff --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/ZJU-REAL/Easel.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/openclaw/skill-cross-platform-diff .claude/skills/skill-cross-platform-diff && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
skill-cross-platform-diff
GitHub stars
3.2k
Token cost
~761 tokens
SKILL.md length
125 words
Files
3 (incl. references)
Skills in repo
113
Repo updated
First seen
Licence
Apache-2.0

At a glance

跨平台内容差异深度分析。分析同一话题/内容在不同平台(小红书、抖音、B站、知乎、 微博、公众号、X 等)的呈现差异:内容形式、受众偏好、话语体系、流量逻辑、变现路径。

  • Works in 7 steps: 明确分析范围 → 加载平台知识 → 话题-平台交叉分析 → …
  • Tasks that involve Content repurposing
  • SKILL.md covers 输入, 输出, 执行步骤 and Profile 感知
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Skill Cross Platform Diff is an agent skill from ZJU-REAL/Easel. 跨平台内容差异深度分析。分析同一话题/内容在不同平台(小红书、抖音、B站、知乎、 微博、公众号、X 等)的呈现差异:内容形式、受众偏好、话语体系、流量逻辑、变现路径。 帮创作者理解"同一个内容在不同平台应该怎么做"。当用户说"小红书和抖音有什么区别"、 "这个话题在B站怎么做"、"跨平台差异"、"不同平台"、"各平台怎么做"、"平台特点"时触发。 和 skill-content-repurposing 的区别:repurposing 做格式适配和内容改写, cross-platform-diff 做深度差异分析和策略洞察。

Its SKILL.md is about 760 tokens, which your agent loads only when the skill is triggered. The skill folder holds 3 other files, including reference files (for example `EASEL-META.md` and `references/platform-traits.md`).

It sits in Writing & Content, covering Content repurposing. The repository describes itself as: An open-source AI agent for social media — discover trends, create content, publish everywhere, and learn what works across Xiaohongshu, Douyin, Zhihu, Bilibili, and more.🎨一个开源的… The licence is Apache-2.0.

When your agent uses it

  • Tasks that involve Content repurposing

Example prompts

  • “同一个内容在不同平台应该怎么做”
  • “小红书和抖音有什么区别”
  • “这个话题在B站怎么做”
  • “/skill-cross-platform-diff”

Workflow steps

7 steps, taken from the first numbered list in SKILL.md.

  1. 明确分析范围
  2. 加载平台知识
  3. 话题-平台交叉分析
  4. 差异提取
  5. 适配度评估
  6. 适配策略生成
  7. 输出报告

What it can do on your machine

Read from SKILL.md and the folder at commit fb80ae6. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Skill Cross Platform Diff loads about 761 tokens when it runs, and up to ~3k if it reads all its reference files. Until then it costs about 73 tokens; SKILL.md has 125 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~73
When it runs · the whole SKILL.md, loaded when a task matches
~761
With references · SKILL.md plus every file in references/, read only if the agent opens them
~3k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from ZJU-REAL/Easel at commit fb80ae6, republished under its Apache-2.0 licence (© ZJU-REAL). 125 words, ~761 tokens.

Download SKILL.mdSave it as .claude/skills/skill-cross-platform-diff/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.
name
skill-cross-platform-diff
description
跨平台内容差异深度分析。分析同一话题/内容在不同平台(小红书、抖音、B站、知乎、 微博、公众号、X 等)的呈现差异:内容形式、受众偏好、话语体系、流量逻辑、变现路径。 帮创作者理解"同一个内容在不同平台应该怎么做"。当用户说"小红书和抖音有什么区别"、 "这个话题在B站怎么做"、"跨平台差异"、"不同平台"、"各平台怎么做"、"平台特点"时触发。 和 skill-content-repurposing 的区别:repurposing 做格式适配和内容改写, cross-platform-diff 做深度差异分析和策略洞察。
layer
discover

跨平台内容差异分析

分析同一话题在不同中文社媒平台的呈现差异,输出平台适配策略。

输入

字段必填说明
话题/内容主题是要分析的话题、关键词或一段内容
目标平台推荐要对比的平台列表(默认全平台扫描)
分析目的推荐"我想把这个内容发到各平台" / "想了解平台差异" / "选择主攻平台"
已有内容可选如果用户已有某平台的内容,可作为对比基准
赛道 / 行业可选不同赛道在各平台的差异可能不同

支持的平台:小红书、抖音、B站、知乎、微博、公众号、视频号、X/Twitter、快手。

输出

markdown
# 跨平台差异分析:[话题/主题]

## 分析概要
- 分析话题:[话题]
- 对比平台:[平台列表]
- 分析时间:[日期]

## 平台差异全景

### 对比矩阵
| 维度 | 小红书 | 抖音 | B站 | 知乎 | 微博 | 公众号 |
|------|--------|------|-----|------|------|--------|
| 主力内容形式 | | | | | | |
| 核心受众画像 | | | | | | |
| 话语体系/语气 | | | | | | |
| 流量分发逻辑 | | | | | | |
| 内容生命周期 | | | | | | |
| 变现路径 | | | | | | |
| 该话题适配度 | | | | | | |

### 平台逐一分析

#### [平台名]
- **该话题在此平台的典型呈现**:内容形式、风格、角度
- **受众期待**:这个平台的用户看到这个话题时期待什么
- **话语体系**:用词习惯、语气、表达方式
- **流量逻辑**:该话题如何获取流量(搜索 / 推荐 / 社交传播)
- **成功案例特征**:该话题在此平台表现好的内容有什么共性
- **避坑指南**:该话题在此平台容易踩的坑
- **变现可能**:该话题在此平台的商业化路径

(每个目标平台各一节)

## 核心差异洞察
1. [最重要的跨平台差异发现]
2. [第二重要的发现]
3. ...

## 平台选择建议
- **主攻推荐**:[最适合的 1-2 个平台 + 原因]
- **辅助布局**:[值得同步运营的平台 + 策略]
- **不推荐**:[不适合的平台 + 原因]

## 适配策略
针对每个推荐平台,给出从"原始内容"到"平台适配内容"的转化要点:
- 标题改写方向
- 内容结构调整
- 语气和用词转换
- 格式和长度要求
- 标签/话题策略
- 发布时间建议

## 注意事项
- 平台规则和算法变化的时效性说明
- 分析依据(平台公开信息 + 行业认知)

执行步骤

  1. 明确分析范围

    • 确认话题/主题和目标平台
    • 若用户未指定平台,默认分析主流 6 个平台:小红书、抖音、B站、知乎、微博、公众号
    • 确认分析目的(了解差异 / 选平台 / 做适配)
  2. 加载平台知识

    • 读取 references/platform-traits.md 获取各平台基础特征
    • 这是底层知识,不直接输出,用于支撑分析
  3. 话题-平台交叉分析

    • 对每个目标平台,分析该话题在此平台的适配情况:
      • 内容形式:该话题在此平台通常以什么形式呈现(图文 / 短视频 / 长视频 / 问答 / 文章)
      • 受众期待:此平台用户看到这个话题时想获得什么(知识 / 娱乐 / 种草 / 讨论 / 共鸣)
      • 话语体系:此平台讨论这个话题的用词、语气、风格
      • 流量来源:该话题在此平台主要通过什么渠道获取流量
  4. 差异提取

    • 做平台间横向对比,识别关键差异点
    • 重点关注:同一话题在不同平台的"信息需求差异"(同一个关键词,用户在知乎搜和在小红书搜的目的完全不同)
    • 总结差异规律(如"越深度的平台越需要论据,越碎片的平台越需要情绪")
  5. 适配度评估

    • 结合话题特性和平台特征,给出各平台的适配度评级
    • 评估维度:内容天然匹配度、竞争饱和度、变现可行性、运营成本
    • 给出主攻/辅助/不推荐的分层建议
    适配度评分(每项 1-5 分)
    维度1 分3 分5 分
    内容匹配该话题在此平台几乎无人关注有一定受众但非主流该平台此类内容流量大、互动高
    竞争饱和头部账号垄断,新人几乎无机会有竞争但仍可差异化内容稀缺,供不应求
    变现可行该平台此类内容无商业模式可接广告但品牌少品牌方活跃,变现路径清晰
    运营成本需要持续高频更新+运营互动中等运营投入内容长尾效应强,运营压力小
  6. 适配策略生成

    • 对推荐的平台,给出具体的内容适配策略
    • 不做内容改写(那是 repurposing 的职责),而是给出"转化方向指引"
    • 包括标题方向、结构调整、语气转换、格式要求、标签策略
  7. 输出报告

    • 按模板生成完整分析报告
    • 保存到 outputs/

Profile 感知

有 Profile 时:

  • 读取 identity.md(赛道定位)、platforms.md(当前主攻平台)、audience.md(受众画像)
  • 平台选择建议对齐账号现有能力("你擅长长图文,B站和知乎比抖音更适合你")
  • 适配策略考虑账号已有的内容资产("你公众号的深度文章可以拆成小红书的卡片组")
  • 变现路径建议结合 Profile 中的商业化目标

无 Profile 时:

  • 退到通用模式,做客观的平台差异分析
  • 平台选择建议基于话题特性而非账号特性
  • 不做"你适合什么"的个性化判断,只做"这个话题适合什么平台"

自研溯源与参考的学术研究/开源项目见同目录 EASEL-META.md。

© ZJU-REAL, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 2 other files (references) in skills/openclaw/skill-cross-platform-diff of ZJU-REAL/Easel.

  • SKILL.md
  • EASEL-META.md
  • references/platform-traits.md

Open the folder on GitHubat commit fb80ae6

Compare with similar skills

Skill Cross Platform Diff next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Skill Cross Platform Diff compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Skill Cross Platform Diff this skillZJU-REAL/Easel3.2k—~761Automated safety check: PassApache-2.0
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Social Contentfreekmurze/dotfiles1k23 repos~2.1kAutomated safety check: PassNone
Changelog Social RecapFlorianBruniaux/claude-code-ultimate-guide6.1k—~1.8kAutomated safety check: NotesCC-BY-SA-4.0
WeChat Article Rewritingaiworkskills/wechat-article-skills6671 repos~2.2kAutomated safety check: PassApache-2.0
YoutubeAgriciDaniel/claude-youtube431—~3.1kAutomated safety check: PassMIT

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Questions about Skill Cross Platform Diff

What does Skill Cross Platform Diff do?

跨平台内容差异深度分析。分析同一话题/内容在不同平台(小红书、抖音、B站、知乎、 微博、公众号、X 等)的呈现差异:内容形式、受众偏好、话语体系、流量逻辑、变现路径。. Skill Cross Platform Diff is an agent skill from ZJU-REAL/Easel.

When should I use Skill Cross Platform Diff?

Skill Cross Platform Diff fits situations like: tasks that involve Content repurposing.

How do I install Skill Cross Platform Diff in Claude Code?

Run `npx skills add ZJU-REAL/Easel --skill skill-cross-platform-diff -a claude-code`. Or copy the skill folder (skills/openclaw/skill-cross-platform-diff in ZJU-REAL/Easel) into .claude/skills/skill-cross-platform-diff in your project. Claude Code loads it when a task matches its description.

How do I install Skill Cross Platform Diff in Codex?

Run `npx skills add ZJU-REAL/Easel --skill skill-cross-platform-diff -a codex`. Or copy the skill folder (skills/openclaw/skill-cross-platform-diff in ZJU-REAL/Easel) into .agents/skills/skill-cross-platform-diff in your project. Codex loads it when a task matches its description.

Can I use Skill Cross Platform Diff in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add ZJU-REAL/Easel --skill skill-cross-platform-diff -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/skill-cross-platform-diff, .gemini/skills/skill-cross-platform-diff, .github/skills/skill-cross-platform-diff and .opencode/skills/skill-cross-platform-diff in your project.

What does Skill Cross Platform Diff need to run?

SKILL.md names no scripts, command-line tools or credentials: Skill Cross Platform Diff is instructions for the agent only.

Does Skill Cross Platform Diff access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Skill Cross Platform Diff safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Skill Cross Platform Diff use?

Skill Cross Platform Diff is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Skill Cross Platform Diff use?

About 761 tokens (SKILL.md is roughly 3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 2.2k tokens, read only when the agent opens those files.

What are the alternatives to Skill Cross Platform Diff?

Skills that share tags, products or a category with Skill Cross Platform Diff: Social (coreyhaines31/marketingskills, 54k stars), Social Content (freekmurze/dotfiles, 1k stars), Changelog Social Recap (FlorianBruniaux/claude-code-ultimate-guide, 6.1k stars) and WeChat Article Rewriting (aiworkskills/wechat-article-skills, 667 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Skill Cross Platform Diff?

ZJU-REAL (a GitHub organization) maintains it in ZJU-REAL/Easel, which has 3,230 GitHub stars. The repository holds 113 skills in this directory. The repository was last updated on October 7, 2026.

Source: ZJU-REAL/Easel on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.