Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/aiworkskills/wechat-article-skillsnpx agentmods add skills/aiworkskills/wechat-article-skills/aws-wechat-article-topicsWrote 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/aiworkskills/wechat-article-skills/aws-wechat-article-topics)<a href="https://agentmods.dev/skills/aiworkskills/wechat-article-skills/aws-wechat-article-topics"><img src="https://agentmods.dev/badge/skills/aiworkskills/wechat-article-skills/aws-wechat-article-topics/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/aiworkskills/wechat-article-skills/aws-wechat-article-topics"><img src="https://agentmods.dev/badge/skills/aiworkskills/wechat-article-skills/aws-wechat-article-topics.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 | $0.00175 | $0.03964 |
| Opus 5 | $0.00088 | $0.01982 |
| Sonnet 5 | $0.00035 | $0.00793 |
| Haiku 4.5 | $0.00017 | $0.00396 |
Grade A, and why
aws-wechat-article-topics 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 — 191 lines — stays where its author put it; the contents beside it link to each section on GitHub.
选题与标题
公众号选题 & 爆款标题 AI 助手 —— 热点追踪、选题调研、起标题、写摘要、系列排期一次搞定。
套件说明 · 本 skill 属
aws-wechat-article-*一条龙套件（共 9 个 slug，入口aws-wechat-article-main）。跨 skill 的相对引用依赖同一skills/目录，建议一并clawhub install全套。源码：https://github.com/aiworkskills/wechat-article-skills
能力披露（Capabilities）
本 skill 主要由 Agent 驱动（对话式选题调研、标题生成），脚本层仅用于更新本篇元数据。
- 凭证：无
- 网络：Agent 可能使用
web_search/web_fetch（Claude Code 内置能力，非本 skill 脚本层发起） - 文件读：仓库内
.aws-article/config.yaml、本篇article.yaml、.aws-article/products/{产品名}/*.md（业务介绍 .md，直接挂在产品根；选题涉及用户业务时必读） - 文件写：本篇目录下
topic-card.md、research.md；更新本篇article.yaml - shell：可能调用同仓库的
{python} {baseDir}/../aws-wechat-article-publish/scripts/article_init.py（{python}= 本机 Python 3 解释器，见 main SKILL 第 0 步：Windows 用py -3 -X utf8，macOS / Linux 用python3）
配套 skill（informational）
本 skill 是 aws-wechat-article-* 一条龙公众号套件的选题环节（入口 aws-wechat-article-main）。工作流中的若干步骤会读取同级 ../aws-wechat-article-main/references/*.md 等共享文档（首次引导、env/config 示例等）。
- 套件完整装齐到同一
skills/根目录时，跨 skill 引用都能读到。 - 单独安装本 skill 时，跨 skill 引用的步骤会在读取阶段遇到
file not found；本 skill 内的纯本地步骤仍可用。
完整 9 slug 清单见 源码仓库。
路由
要成文并发到公众号、或「今天发什么」需整条编排时 → aws-wechat-article-main。
通过调研生成高质量选题，支持单篇和系列。
配置检查 ⛔
任何操作执行前，必须按 首次引导 执行其中的 「检测顺序」。检测通过后才能进行以下操作（或用户明确书面确认「本次不检查」）：
四种输入模式
根据用户输入自动识别模式：
| 模式 | 触发条件 | 示例 |
|---|---|---|
| A. 明确选题 | 用户给了具体话题 | 「写一篇 AI Agent 的文章」 |
| B. 有方向 | 给了领域但没具体题目 | 「AI 最近有什么好写的」 |
| C. 无方向 | 只说要选题 | 「这周写什么」「帮我找几个选题」 |
| D. 系列策划 | 提到系列/专栏/连载 | 「做个 AI 入门系列」「写 10 篇专栏」 |
工作流
选题进度：
- [ ] 第1步：配置检查（见本节「配置检查」）
- [ ] 第2步：全局账号三键（`.aws-article/config.yaml` 的 `article_category` / `target_reader` / `default_author`）⛔ 与 [main](../aws-wechat-article-main/SKILL.md)「2) 全局账号约束」一致；缺则**问用户确认后**再写入，**禁止**从 `article.yaml` 擅自填充，**先于**方向确认与调研
- [ ] 第3步：确认是否已有选题或写作方向 ⛔
- [ ] 第4步：调研
- [ ] 第5步：生成选题
- [ ] 第6步：生成标题与大纲
- [ ] 第7步：展示并等待用户选择 ⛔
- [ ] 第8步：输出选题卡片（新建本篇目录时须具备或更新本篇 article.yaml）
What ships with it
4 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 Changed 85f88da43b18
- 11d ago First seen · 191 lines · 175 tokens per session scan A 969ab720dabc
aws-wechat-article-topics is a skill published in the GitHub repository aiworkskills/wechat-article-skills (589 stars, last pushed today), licensed Apache-2.0. It adds 175 tokens to every session and 3,964 once invoked, about $0.0009 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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