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-trend-ridergit 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-trend-rider)<a href="https://agentmods.dev/skills/zju-real/easel/skill-trend-rider"><img src="https://agentmods.dev/badge/skills/zju-real/easel/skill-trend-rider/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-trend-rider"><img src="https://agentmods.dev/badge/skills/zju-real/easel/skill-trend-rider.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 | $0.00146 | $0.01922 |
| Opus 5 | $0.00073 | $0.00961 |
| Sonnet 5 | $0.00029 | $0.00384 |
| Haiku 4.5 | $0.00015 | $0.00192 |
Grade A, and why
skill-trend-rider 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.
How it starts
The opening of the file, as written. The whole thing — 154 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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
# 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
-
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)
-
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
-
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
- 运用 6 种蹭热点角度模型:
-
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
- 为每个角度生成完整方案:
-
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
-
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
- 逐条排查风险点:
What ships with it
1 file 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.
- 9d ago First seen · 154 lines · 146 tokens per session scan A c435b001ae58
skill-trend-rider is a skill published in the GitHub repository ZJU-REAL/Easel (841 stars, last pushed yesterday), licensed Apache-2.0. It adds 146 tokens to every session and 1,922 once invoked, about $0.0007 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 2026-09-03.
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