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 agentmods add skills/ethanyoq/skill-hub/wechat-articlenpx skills add EthanYoQ/Skill-hub --skill wechat-articlegit clone --depth 1 https://github.com/EthanYoQ/Skill-hubWrote 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/ethanyoq/skill-hub/wechat-article)<a href="https://agentmods.dev/skills/ethanyoq/skill-hub/wechat-article"><img src="https://agentmods.dev/badge/skills/ethanyoq/skill-hub/wechat-article.svg" alt="Measured on agentmods" 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 | $0.00088 | $0.02757 |
| Opus 5 | $0.00044 | $0.01378 |
| Sonnet 5 | $0.00018 | $0.00551 |
| Haiku 4.5 | $0.00009 | $0.00276 |
Grade A, and why
wechat-article 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 5d 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 — 379 lines — stays where its author put it; the contents beside it link to each section on GitHub.
WeChat Article Creator - 微信公众号创作技能
写作风格
遵循傅盛写作风格：
- 口语化：像跟朋友聊天，不是学术论文
- 故事感：用具体事例代替空洞理论
- 有态度：表达观点，不做和稀泥
- 简化复杂：善用类比让难懂的东西变简单
工作流程
1. 策划阶段（Planning）
当接到写作需求，先询问以下信息：
我帮你策划一下这篇文章，先问几个问题：
1. 主题是什么？（用1句话说）
2. 目标读者是谁？
3. 你想表达什么核心观点或故事？
4. 有哪些数据或案例可以用？
标题策略
引导用户选择以下标题类型：
- ❌ 结论式：「XX 的 3 个方法」（太平淡）
- ✅ 悬念式：「我为什么放弃了年薪 50W 的工作」
- ✅ 反问式：「你真的了解 AI 吗？」
- ✅ 数字式：「50% 的人都误解了这个道理」
- ✅ 对比式：「BAT vs 创业公司，差在哪里」
关键：标题要能激发好奇心或共鸣，而不是直接给出答案。
收集完信息后，在 drafts/ 目录创建策划文档：
# 文章计划
## 基本信息
- 标题：[待定标题]
- 主题：[核心主题]
- 目标读者：[读者画像]
- 核心观点：[1-2句话]
## 大纲
1. 开头：[如何引入]
2. 观点1：[+案例]
3. 观点2：[+案例]
4. 观点3：[+案例]
5. 结尾：[总结+行动建议]
## 素材库
- 案例1：[具体故事]
- 案例2：[具体故事]
- 数据支撑：[关键数据]
2. 写作阶段（Writing）
按照以下结构创作文章，保存为 drafts/article_[主题].md：
结构模板
# [文章标题]
> 作者：[作者名]
> 日期：[发布日期]
## [开头] (100-150 字)
[用故事、数据或问题勾起兴趣]
[直白说明文章解决什么问题]
---
## [主体] (800-1500 字)
### [观点 1 小标题]
[具体案例或故事]
[解释观点]
### [观点 2 小标题]
[具体案例或故事]
[解释观点]
### [观点 3 小标题]
[具体案例或故事]
[解释观点]
---
## [结尾] (100-150 字)
[总结核心观点]
[留下思考或行动建议]
写作要点
1. 用故事代替说教
❌ 不好："风险管理很重要，应该制定应急预案"
✅ 好的：
去年我创业的团队就是因为没有备选方案，
一个核心员工离职就差点垮掉。
从那以后，我学会了给每个岗位预留 backup。
2. 善用类比和比喻
❌ "分布式系统很复杂"
✅ "分布式系统就像一家连锁餐厅， 每个分店要相互协作又要独立运营， 稍微一个环节没协调好，整个体验就崩了。"
3. 数据支撑但不堆砌
❌ "根据 IDC 报告，全球 AI 市场 2023 年增长 45%，预计 2025 年达到 1000 亿美元规模..."（太干）
✅ "AI 市场在疯狂增长——每年翻番。 但这个增长背后，真正赚钱的公司不超过 5 家。"
4. 直接说观点，避免模棱两可
❌ "有人认为...也有人认为...各有各的道理"
✅ "老实说，我觉得 XX 这个做法是错的，原因是..."
5. 用短句和换行
❌ "今天我想和大家分享一个非常重要的观点，那就是在创业的过程中，我们需要不断地学习和适应市场变化..."
✅
今天我想说一个观点。
创业最怕的不是失败。
是失败后还不知道为什么失败。
我见过太多团队折戟沙滩，
最后都说一句话："我们当时真傻。"
3. 排版优化
微信公众号排版格式
# 大标题（用于文章标题）
## 小标题（用于章节分隔）
**加粗强调**关键词
> 引用重要观点或数据
- 列表项 1
- 列表项 2
- 列表项 3
---
分隔线（用于大的内容分隔）
排版建议
- 段落长度：3-5 行为宜，太长难读
- 缩进：微信不需要首行缩进，用空行分隔段落
- 标题层级：最多用 2 层（##），不要嵌套太深
- 加粗：只强调 1-2 个最重要的词
- 引用：用于数据、金句或重要观点
- 列表：最多 5 项，太多改成段落
What ships with it
6 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.
- 5d ago First seen · 379 lines · 88 tokens per session scan A 8004330f5a19
wechat-article is a skill published in the GitHub repository EthanYoQ/Skill-hub (9 stars, last pushed yesterday), licensed MIT. It adds 88 tokens to every session and 2,757 once invoked, about $0.0004 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 2026-08-31.
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live-preview
Mid-build visual verification loop. Takes screenshots of components during construction, not just after. Catches visual regressions and invisible features before they compound. Requires Playwright or similar screenshot tool.
marshal
Meta-orchestrator that takes any direction — broad, specific, or vague — and autonomously chains skills and context into actionable work. Gathers context from codebase, docs, and memory. Only asks the user when it genuinely cannot proceed. Single-session orchestrator.
systematic-debugging
4-phase root cause analysis: observe, hypothesize, verify, fix. Enforces investigation before any code changes. Emergency stop after 2 failed fixes. Prevents shotgun debugging and fix cascades.