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-writingWrote 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-writing)<a href="https://agentmods.dev/skills/aiworkskills/wechat-article-skills/aws-wechat-article-writing"><img src="https://agentmods.dev/badge/skills/aiworkskills/wechat-article-skills/aws-wechat-article-writing/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-writing"><img src="https://agentmods.dev/badge/skills/aiworkskills/wechat-article-skills/aws-wechat-article-writing.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 | $0.00218 | $0.09003 |
| Opus 5 | $0.00109 | $0.04501 |
| Sonnet 5 | $0.00044 | $0.01801 |
| Haiku 4.5 | $0.00022 | $0.00900 |
Grade A, and why
aws-wechat-article-writing 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 today.
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 — 339 lines — stays where its author put it; the contents beside it link to each section on GitHub.
长文写作
公众号长文 AI 写作引擎 —— 从提纲或话题生成完整初稿，支持改写、续写、润色，多模型可切。
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 调用 write.py 生成文章初稿，会把文章内容发送给用户配置的 LLM 端点。使用前请阅读以下全部行为说明：
- 凭证读取：
write.py读取仓库根aws.env的WRITING_MODEL_API_KEY - 凭证外发：该 API key 以
Authorization: Bearer <key>头发送到用户在config.yaml.writing_model.base_url配置的外部端点（常见为 DeepSeek / OpenAI / Anthropic 等 Chat Completions 兼容 API）。请使用专用 key 并配置可信端点或内部代理 - 内容外发：Prompt 内包含本篇
article.yaml/topic-card.md/ 合并配置 / 用户通过--reference指定的参考文档.md全文 → 整体 POST 给上述端点 - 文件读（仓库内）：
.aws-article/config.yaml、本篇article.yaml、topic-card.md、.aws-article/products/{产品名}/*.md（业务介绍 .md，直接挂在产品根） - 文件读（仓库外）：若仓库内
.aws-article/缺失，write.py会从用户家目录~/.aws-article/读取writing-spec.md与presets/（只读预设，不读凭证） - 文件写：仅本篇目录下
draft.md、article.md - shell：仅
{python} {baseDir}/scripts/write.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）
可使用 write.py prompt 子命令只输出 prompt JSON 不调用 LLM，由 Agent 代写 —— 想避免把内容发给第三方时用这条路径。
配套 skill（informational）
本 skill 是 aws-wechat-article-* 一条龙公众号套件的写稿环节（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、articlescreening schema 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
从零发文、一条龙、完整流程 → aws-wechat-article-main。
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」）：
从选题到发布的前置规则（阻断、禁止擅自降级、「本次例外」等）见 aws-wechat-article-main/SKILL.md；本 skill 只描述写稿步骤。
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.
- today Changed · +28 lines b99ac7c03470
- 4d ago Changed · +39 lines be1babc3131a
- 5d ago Changed 6926f007ee9e
- 11d ago First seen · 272 lines · 218 tokens per session scan A a60f38d5c6ce
aws-wechat-article-writing is a skill published in the GitHub repository aiworkskills/wechat-article-skills (589 stars, last pushed today), licensed Apache-2.0. It adds 218 tokens to every session and 9,003 once invoked, about $0.0011 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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