Easel is an open-source content workspace and AI agent for managing social media from trend discovery through planning, content creation, publishing, and performance analysis. It is intended for social media creators and maintains separate account profiles, content projects, platform adaptations, and publishing records. The catalogue skills support these content and publishing workflows.
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.
npx skills add ZJU-REAL/Easel --skill skill-cross-platform-diffgit clone --depth 1 https://github.com/ZJU-REAL/EaselWrote 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.
[](https://agentmods.dev/skills/zju-real/easel/skill-cross-platform-diff)<a href="https://agentmods.dev/skills/zju-real/easel/skill-cross-platform-diff"><img src="https://agentmods.dev/badge/skills/zju-real/easel/skill-cross-platform-diff/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.
<a href="https://agentmods.dev/skills/zju-real/easel/skill-cross-platform-diff"><img src="https://agentmods.dev/badge/skills/zju-real/easel/skill-cross-platform-diff.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00179 | $0.01890 |
| Opus 5.5 | $0.00072 | $0.00756 |
| Sonnet 5.5 | $0.00036 | $0.00378 |
| Haiku 4.5 | $0.00018 | $0.00189 |
Grade A, and why
skill-cross-platform-diff 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 1mo 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.
How it starts
The opening of the file, as written. The whole thing — 149 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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
# 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
-
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）
-
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
- 读取
-
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
- 对每个目标平台，分析该话题在此平台的适配情况：
-
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"）
-
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
What ships with it
2 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.
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.
- 1mo ago First seen · 149 lines · 179 tokens per session scan A e33aaa2de4ea
skill-cross-platform-diff is a skill published in the GitHub repository ZJU-REAL/Easel (4,032 stars, last pushed yesterday), licensed Apache-2.0. It adds 179 tokens to every session and 1,890 once invoked, about $0.0007 per session on Opus 5.5. 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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