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 | $0.03041 |
| Opus 5.5 | $0.00062 | $0.01216 |
| Sonnet 5.5 | $0.00031 | $0.00608 |
| Haiku 4.5 | $0.00015 | $0.00304 |
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 1mo 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 — 165 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。
- 凭证：无
- 网络：无
- 文件读：
.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/imgs/ - 文件写：本篇
draft-stripped.md（中间产物）、article.md（定稿）、review.md - shell：只在第 5 步调
{python} .../aws-wechat-article-writing/scripts/write.py strip-citations，第 2 步调同一脚本的check子命令。两者都是纯本地正则/计数，不联网、不读凭证、不调 LLM。
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 只按已有manual排占位符，不直接调任何网络脚本。
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。
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（含机器自检）
- [ ] 第3步：输出审稿结果
- [ ] 第4步：修改循环 🔄
- [ ] 第5步：⛔ 剥离引用标注 → 文末 embed → 保存 article.md 定稿
智能体行为约束 ⛔
- 禁止在未完成第 5 步「文末 embed」的情况下，把稿件称为「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，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。
- 一条龙流程中，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。
第1步：环境检查 + 读取约束 ⛔
任何操作前先按 首次引导 · 检测顺序 执行，通过后才继续（或用户明确书面确认「本次不检查」）。单独启用本 skill 时的口径见 branches.md「四」。
然后读取：
.aws-article/writing-spec.md（如有）.aws-article/presets/review-rules.yaml（如有，见 branches.md「二」）- 本篇合并配置（与 writing、
format.py一致）：先.aws-article/config.yaml顶层（不含writing_model/image_model），再叠本篇article.yaml（同键本篇优先；仅embeds.related_articles与全局深度合并，其余embeds仍以全局为准）。审稿以合并结果为准（review_output_format、custom_sensitive_words、forbidden_words、target_reader、tone、image_density等）。字段说明见 articlescreening-schema.md。
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.
- 1mo ago Changed · -37 lines 576abd50eb53
- 1mo ago Changed 300b5a62d547
- 1mo 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 (713 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 155 tokens to every session and 3,041 once invoked, about $0.0006 per session on Opus 5.5. 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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