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Skill Trend Rider

OrganizationPopular
ZJU-REAL
skill-trend-rider

给定一个热点事件或话题，结合创作者账号定位，输出蹭热点的具体内容方案。 包含切入角度、内容形式、标题建议、风险提醒。 当用户说"这个热点怎么蹭"、"蹭热点"、"怎么结合"、"热点和我有关吗"、 "追热点"、"热点方案"、"借势"、"怎么追这个热点"、"热点怎么切"时触发。 和 skill-trending-topics 的区别：trending-topics 发现和筛选热点， trend-rider 拿到一个具体热点后规划怎么蹭、怎么切内容。

Overview

PublisherZJU-REAL
RepositoryEasel
Skill nameskill-trend-rider
Stars
3.5K
Forks
535
Bundled files
1
LicenseApache-2.0
Links
Skill sourceRepositoryHomepage
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by ZJU-REAL on GitHub. Read the source before you install it.

Installation

Install the Skill Trend Rider AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/ZJU-REAL/Easel/tree/main/skills/openclaw/skill-trend-rider
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/ZJU-REAL/Easel.git /tmp/Easel
mkdir -p .claude/skills
cp -r /tmp/Easel/skills/openclaw/skill-trend-rider .claude/skills/skill-trend-rider
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Skill Trend Rider in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Skill Trend Rider on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Skill Trend Rider is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

蹭热点方案

给一个热点事件，结合创作者定位，输出具体的蹭热点内容方案。

输入

参数必填说明
热点事件是热点话题/事件描述或关键词
目标平台否发布平台（有 Profile 时自动提取）
创作者赛道否如"科技数码"、"美妆"（有 Profile 时自动提取）

输出

markdown
# 蹭热点方案

## 热点概况
- 热点事件: {事件名}
- 热度等级: {S/A/B/C 级}
- 生命周期: {爆发期/高峰期/衰退期/长尾期}
- 预计热度窗口: {剩余 X 小时/天}

## 关联度判断
- 与创作者赛道的关联度: {高/中/低/无}
- 关联分析: {为什么相关或不相关}
- 蹭热点可行性: {适合蹭/勉强可蹭/不建议蹭}

## 内容方案（3 个角度）

### 方案 A: {角度名}（推荐指数: ★★★★★）
- 切入角度: {具体怎么切}
- 内容形式: {图文/短视频/直播/thread}
- 标题候选:
  1. {标题 A1}
  2. {标题 A2}
  3. {标题 A3}
- 内容大纲: {3-5 个要点}
- 制作时间: {预估}
- 预期效果: {流量预期和互动类型}

### 方案 B: {角度名}（推荐指数: ★★★★☆）
{同上结构}

### 方案 C: {角度名}（推荐指数: ★★★☆☆）
{同上结构}

## 发布策略
- 最佳发布时间: {具体时间窗口}
- 平台选择: {首发平台 + 分发顺序}
- 标签策略: {推荐话题标签}

## 风险提醒
- {风险点 1}: {规避建议}
- {风险点 2}: {规避建议}

## 不蹭的理由（关联度低时输出）
{为什么不建议蹭 + 替代建议}

执行步骤

  1. 热点解析

    • 解析热点事件的核心信息：事件主体、起因、发展、争议点
    • 判断热点类型：社会事件、娱乐八卦、行业动态、政策变化、节日节点、突发事件
    • 评估热点生命周期阶段：
      • 爆发期（0-4 小时）：速度优先，抢首发
      • 高峰期（4-24 小时）：角度优先，做差异化
      • 衰退期（1-3 天）：深度优先，做总结/反思
      • 长尾期（3 天+）：复盘优先，提炼方法论
    • 评估热度等级：S 级（全网刷屏）、A 级（行业热议）、B 级（圈层讨论）、C 级（小范围关注）

  2. 关联度评估

    • 分析热点与创作者赛道的交集：是否有自然关联、能否专业解读
    • 关联度分级：
      • 高关联：热点本身属于创作者赛道（如科技博主评测新手机发布）
      • 中关联：热点可从创作者角度解读（如职场博主解读裁员新闻）
      • 低关联：需要强行关联（如美食博主蹭航天热点）
      • 无关联：完全不搭边，蹭了反而减分
    • 关联度低于"中"时，明确建议不蹭，并说明原因

  3. 切入角度挖掘

    • 运用 6 种蹭热点角度模型：
      • 专业解读：从专业视角分析热点（适合知识型创作者）
      • 经验关联：分享自己与热点相关的亲身经历（适合人设型创作者）
      • 工具/方法论：借热点引出实用方法论（适合干货型创作者）
      • 反向观点：提出与主流不同的观点（适合争议型创作者，风险高）
      • 情绪共鸣：表达与大众一致的情绪（适合情感型创作者）
      • 延伸联想：从热点延伸到更大话题（适合深度型创作者）
    • 根据创作者定位，筛选最匹配的 3 个角度

  4. 内容方案生成

    • 为每个角度生成完整方案：
      • 内容形式选择：根据平台特性和角度匹配最佳形式
      • 标题候选：每个方案 3 个标题，覆盖不同情绪钩子
      • 内容大纲：3-5 个核心要点，确保逻辑完整
      • 制作时间估算：根据形式复杂度给出预估
    • 3 个方案按推荐指数排序，综合考虑关联度、制作难度、预期效果

  5. 发布策略规划

    • 根据热点生命周期确定最佳发布时间窗口
    • 多平台分发策略：首发平台、二次分发顺序、各平台内容适配
    • 话题标签策略：官方话题标签 + 长尾标签组合

  6. 风险评估

    • 逐条排查风险点：
      • 政治敏感性：是否涉及政策、国际关系、意识形态
      • 法律风险：是否涉及未定性的事件、侵权、隐私
      • 舆论反转：事件是否可能反转导致翻车
      • 道德争议：蹭该热点是否会引发"吃人血馒头"质疑
      • 平台规则：是否触碰平台内容红线
    • 每个风险点附带具体规避建议

  7. 输出交付

    • 按输出格式生成完整方案
    • 关联度判定为"无"时，跳过方案生成，直接输出"不蹭的理由"并建议替代方向

Profile 感知

有 Profile 时：

  • 读取 identity.md 获取赛道定位，精确判断热点关联度
  • 读取 audience.md 获取粉丝画像，评估粉丝对该热点的关注度
  • 读取 style.md 匹配内容形式和表达方式
  • 读取 platforms.md 确定首发平台和分发策略
  • 读取 tone.md（如有）确保标题和大纲语气一致

无 Profile 时：

  • 关联度评估退回通用模式，要求用户自行提供赛道信息
  • 内容方案不做平台特化，给出通用版本
  • 提示"提供 Profile 可获得更精准的关联度判断和角度匹配"

规则

  1. 关联度为"无"时必须建议不蹭，不可强行生成方案
  2. 每个方案的标题必须包含热点关键词，确保搜索可见
  3. 风险提醒必须诚实，不可为了让用户蹭热点而淡化风险
  4. 涉及负面事件（灾难/事故/逝世）的热点，禁止推荐"情绪共鸣"以外的切入角度
  5. 标注时效性紧迫度，爆发期热点需提醒用户"现在就做"
  6. 方案之间的角度不可重复，必须提供真正不同的切入点

自研溯源与参考方向见同目录 EASEL-META.md。

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Skill Trend Rider AI skill do?

给定一个热点事件或话题，结合创作者账号定位，输出蹭热点的具体内容方案。 包含切入角度、内容形式、标题建议、风险提醒。 当用户说"这个热点怎么蹭"、"蹭热点"、"怎么结合"、"热点和我有关吗"、 "追热点"、"热点方案"、"借势"、"怎么追这个热点"、"热点怎么切"时触发。 和 skill-trending-topics 的区别：trending-topics 发现和筛选热点， trend-rider 拿到一个具体热点后规划怎么蹭、怎么切内容。

Why use Skill Trend Rider on TypingMind?

Because you install it once and use it with any model. Skill Trend Rider is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Skill Trend Rider in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/ZJU-REAL/Easel/tree/main/skills/openclaw/skill-trend-rider. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Skill Trend Rider?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Skill Trend Rider?

As many as you like. As long as a model supports skills, you can use Skill Trend Rider with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Skill Trend Rider AI skill free?

Yes. It is published on GitHub by ZJU-REAL under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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