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-reviewWrote 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-review)<a href="https://agentmods.dev/skills/aiworkskills/wechat-article-skills/aws-wechat-article-review"><img src="https://agentmods.dev/badge/skills/aiworkskills/wechat-article-skills/aws-wechat-article-review/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-review"><img src="https://agentmods.dev/badge/skills/aiworkskills/wechat-article-skills/aws-wechat-article-review.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 | $0.00155 | $0.03884 |
| Opus 5 | $0.00077 | $0.01942 |
| Sonnet 5 | $0.00031 | $0.00777 |
| Haiku 4.5 | $0.00015 | $0.00388 |
Grade A, and why
aws-wechat-article-review 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 — 202 lines — stays where its author put it; the contents beside it link to each section on GitHub.
审稿与合规
公众号发布前合规守门员 —— 敏感词、错别字、平台规范一次性筛查，输出可执行修改清单。
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 为纯本地规则/清单审稿，零网络、零凭证、不调用任何外部脚本。
- 凭证：无
- 网络：无
- 文件读：仓库内
.aws-article/config.yaml、.aws-article/writing-spec.md（如有）、.aws-article/presets/review-rules.yaml（如有）、本篇draft.md/article.html/article.yaml - 文件写：本篇
article.md定稿、审稿记录 - shell：无（不调用任何脚本）
往期推荐链接的自动补齐由 publish skill 处理（那里才有微信 API 凭证与
getdraft.py）；本 skill 只做「若embeds.related_articles.manual非空则按其排占位符」与「若为空则在审稿输出中提示需 publish 补齐或手填」，不直接调任何网络脚本。
配套 skill（informational）
本 skill 是 aws-wechat-article-* 一条龙公众号套件的审稿环节（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、writing-spec、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 内的纯本地规则/清单审稿仍可用。
完整 9 slug 清单见 源码仓库。
路由
「能不能发」若含代为发布或从稿到发出整条收尾 → aws-wechat-article-main。
对文章做系统性检查，发现问题并引导修改。
两种审稿模式
| 模式 | 时机 | 检查重点 |
|---|---|---|
| 内容审 | writing 之后、formatting 之前 | 内容质量、写作规范、敏感词、配图标记 |
| 终审 | publish 之前 | 排版完整性、图片就位、发布要素齐全 |
自动识别：有 article.html → 终审模式，否则 → 内容审模式。
工作流
审稿进度：
- [ ] 第1步：环境检查 + 本篇约束与规范
- [ ] 第2步：逐项检查
- [ ] 第3步：输出审稿结果
- [ ] 第4步：修改循环 🔄
- [ ] 第5步：确认通过 → **文末 embed（⛔ BLOCKING）** → 保存 `article.md` 定稿
智能体行为约束（与定稿强相关）
- 禁止在未完成 第5步「文末 embed」（见下 ⛔ BLOCKING）的情况下，将稿件称为「已定稿」、写入
article.md、或进入 排版（format.py）。 - 禁止用「用户没提」「节省时间」等理由跳过文末占位符；唯一例外：用户书面声明本篇不要任何嵌入元素（名片/小程序/链接），则须在审稿记录中写明「用户声明跳过 embed」，且仍须确认不是误操作。
- 一条龙 / 完整流程（main SKILL）中，内容审产出的
article.md必须已含文末 embed（按合并规则或合法省略），再进入排版。
What ships with it
5 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 300b5a62d547
- 11d ago First seen · 202 lines · 155 tokens per session scan A e57da5623952
aws-wechat-article-review is a skill published in the GitHub repository aiworkskills/wechat-article-skills (589 stars, last pushed today), licensed Apache-2.0. It adds 155 tokens to every session and 3,884 once invoked, about $0.0008 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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