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 jaylpp/pandajay-skills --skill hotspot-leveragegit clone --depth 1 https://github.com/jaylpp/pandajay-skillsWrote 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/jaylpp/pandajay-skills/hotspot-leverage)<a href="https://agentmods.dev/skills/jaylpp/pandajay-skills/hotspot-leverage"><img src="https://agentmods.dev/badge/skills/jaylpp/pandajay-skills/hotspot-leverage/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/jaylpp/pandajay-skills/hotspot-leverage"><img src="https://agentmods.dev/badge/skills/jaylpp/pandajay-skills/hotspot-leverage.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00140 | $0.01992 |
| Opus 5 | $0.00070 | $0.00996 |
| Sonnet 5 | $0.00028 | $0.00398 |
| Haiku 4.5 | $0.00014 | $0.00199 |
Grade A, and why
hotspot-leverage 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 10d 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 — 167 lines — stays where its author put it; the contents beside it link to each section on GitHub.
热点杠杆术：把刷屏的东西变成你的流量
你正在帮用户分析一个热点事件，并生成可落地的引流和变现策略。
第一步：收集信息（先检后问）
1.1 检查用户业务档案
在提问之前，必须先用 Glob 工具搜索项目根目录下的 user-profile.md 文件。
如果找到 user-profile.md：用 Read 工具读取文件内容，直接使用其中的业务信息。不要再问用户任何业务相关问题，直接跳到 1.3 搜索热点。
如果没有找到：执行 1.2 收集，收集完后必须自动保存。
1.2 收集用户业务信息（仅首次，后续自动跳过）
用 AskQuestion 或对话方式，一次性收集以下信息：
- 你是做什么的？（身份定位，如自媒体博主、产品开发者、独立开发者、电商卖家等）
- 你有哪些产品或服务？（具体产品名和核心功能）
- 你的目标用户是谁？（细分人群画像）
- 你目前的引流渠道有哪些？（公众号、小红书、社群、短视频等）
- 你已有的内容方向是什么？（AI 编程、职场效率、育儿、设计等）
收集完后，必须立即用 Write 工具将业务档案保存到项目根目录的 user-profile.md，格式如下：
# 用户业务档案
- **身份定位**：[填写]
- **产品/服务**：[填写]
- **目标用户**：[填写]
- **引流渠道**：[填写]
- **内容方向**：[填写]
- **更新时间**：[填写日期]
保存后告知用户：「已自动保存你的业务档案到 user-profile.md，下次不会再重复询问。如需更新，直接编辑该文件即可。」
1.3 搜索热点（强制执行，不可跳过）
热点的本质是「新」，模型训练数据大概率没有。在分析之前必须先搜索，不能凭猜测分析。
用 WebSearch 或浏览器工具执行以下搜索，每次至少搜 2-3 轮：
第一轮：搞清楚这是什么
- 搜索「[热点名称] 是什么」，理解热点的基本信息、起源、玩法
- 如果是产品/工具，搜索官网或体验链接，尽可能亲自查看
第二轮：搞清楚火到什么程度
- 搜索「[热点名称] 刷屏 / 火了 / 热搜」，了解当前传播规模和阶段
- 判断热度状态：刚起势 / 正在爆发 / 已过峰值 / 已退潮
第三轮：搞清楚别人在怎么聊
- 搜索「[热点名称] 公众号 / 小红书 / 分析」，看主流内容角度有哪些
- 目的是找到「已经被写烂的角度」，帮用户避开红海，找到差异化切入点
第四轮（可选）：排雷
- 搜索「[热点名称] 争议 / 翻车 / 风险」，确认是否有版权、舆论、政策风险
- 如果有风险，必须在策略中明确提醒用户
搜索完成后，将关键发现整理为一段简要的「热点速写」，包含：这是什么、为什么火、现在处于什么阶段、别人已经在聊什么角度、有没有风险。
1.4 确认用户补充信息
在搜索之后，快速确认用户侧的信息（如果提问中已包含则跳过）：
- 用户已有的想法或素材？（已经想到的思路、手上有的资源）
- 时间紧迫度？（需要今天就发还是可以花几天准备）
第二步：热点拆解（三问框架）
这是整个分析的核心思维模型。按顺序回答三个问题。必须基于第一步搜索到的真实信息，不可编造细节。
问题一：为什么火？
基于搜索结果，分析热点爆发的底层逻辑：
- 情绪驱动：戳中了什么情绪？（焦虑、自嘲、好奇、愤怒、共鸣）
- 社交货币：为什么人们愿意转发？（展示身份、引发讨论、表达立场）
- 参与门槛：用户参与的成本有多低？（时间、金钱、技能门槛）
- 时间窗口：这个热度预计能持续多久？
输出一句话总结，格式为「它火在 [核心原因]，因为 [底层逻辑]」。
问题二：结构是什么？
基于搜索到的产品/内容信息，拆解可复用结构。如果是技术产品（网站、工具、代码），可以进一步查看源码或产品结构：
- 内容层：哪些部分是「内容」，可以被替换？
- 骨架层：哪些部分是「框架」，可以被复用？
- 机制层：有没有裂变机制、互动机制、成瘾机制？
目标是找到「哪些部分可以换皮，哪些部分可以直接搬」。
问题三：跟用户的业务怎么结合？
基于用户的业务档案，逐一匹配：
- 用户的哪个产品可以借这个热点？
- 用户的哪个渠道最适合发这个内容？
- 用户的哪类用户会对这个话题最感兴趣？
第三步：生成策略（从快到慢，三档方案）
必须给出三档方案，让用户根据自己的时间和资源选择：
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.
- 10d ago First seen · 167 lines · 140 tokens per session scan A ae27efb52e37
hotspot-leverage is a skill published in the GitHub repository jaylpp/pandajay-skills (11 stars, last pushed 3mo ago), licensed MIT. It adds 140 tokens to every session and 1,992 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 2026-08-30.
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