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 skills add staruhub/ClaudeSkills --skill geek-skills-wechat-article-writergit clone --depth 1 https://github.com/staruhub/ClaudeSkillsWrote 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/staruhub/claudeskills/geek-skills-wechat-article-writer)<a href="https://agentmods.dev/skills/staruhub/claudeskills/geek-skills-wechat-article-writer"><img src="https://agentmods.dev/badge/skills/staruhub/claudeskills/geek-skills-wechat-article-writer/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/staruhub/claudeskills/geek-skills-wechat-article-writer"><img src="https://agentmods.dev/badge/skills/staruhub/claudeskills/geek-skills-wechat-article-writer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high YARA Match · line 4 YARA rule matched a hack tool or exploit indicator (offensive tools, reconnaissance, privilege escalation, or exploit frameworks).Fix: Remove offensive tool references and exploit code. Legitimate agent skills should not contain penetration testing tools, exploit frameworks, or reconnaissance utilities.
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 | $0.00198 | $0.04043 |
| Opus 5 | $0.00099 | $0.02021 |
| Sonnet 5 | $0.00040 | $0.00809 |
| Haiku 4.5 | $0.00020 | $0.00404 |
Grade A, and why
wechat-article-writer 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 13d 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 — 300 lines — stays where its author put it; the contents beside it link to each section on GitHub.
微信公众号文章创作助手
概述
帮助用户创作高质量的微信公众号文章。核心能力是风格灵活适配——同一个skill既能写企业官号的正式文案，也能写个人IP的技术博客。根据用户需求自动匹配最合适的风格和结构。
先选执行模式
用户未指定时默认 article。需要跨模式时按
references/PIPELINE-CONTRACT.md 的文件接口交接，不靠对话隐含状态。
| 模式 | 输入 | 必须输出 | 停止位置 |
|---|---|---|---|
article |
素材/选题 | article.md |
正文完成 |
image-prompts |
article.md |
image-manifest.json，正文含稳定锚点与占位符 |
提示词完成，不生图 |
layout |
article.md + 可选 manifest |
layout.html |
HTML 完成，不发布 |
full-pipeline |
素材/选题 | article + manifest + HTML | 三件套完成，不生图、不发布 |
manifest 必须通过 schemas/image-manifest.schema.json 和
scripts/validate_image_manifest.py。排版优先调用宿主的“排版输出” Skill；
其接口不可用时，使用 scripts/render_wechat_layout.py 的确定性降级实现。
第一步：风格识别与素材分析
输入处理
- 网站链接 → 使用 web_fetch 获取完整内容
- 文本素材 → 直接分析
- 图像素材 → 识别内容提取关键信息
风格自动识别
根据用户的描述自动判断风格，无需每次手动选择：
| 信号 | 匹配风格 |
|---|---|
| "公司号"、"官方"、"企业宣传"、"品牌" | 🏢 官方文案 |
| "我的公众号"、"技术博客"、"个人分享"、"实操"、提到"卡兹克" | 🧑💻 技术博客 |
| "活动回顾"、"分享会"、"社区"、"meetup" | 🎤 活动回顾 |
| "评测"、"对比"、"体验报告" | 🔍 评测对比 |
| 无法判断 → 询问用户："这篇文章发在企业官号还是个人号？风格偏正式还是轻松？" |
快速需求确认
仅在信息严重不足时询问（不超过2个问题）：
- 目标读者？（普通用户 / 技术开发者 / 行业人士 / 家长学生）
- 文章长度？（短文800-1500字 / 中文1500-3000字 / 长文3000+字）
信息充足时直接开始创作。
第二步：内容研究
使用 web search 补充内容（所有风格都适用）：
根据文章类型选择搜索策略：
技术类文章：
- 搜索技术文档、GitHub仓库、开发者博客、官方changelog
- 搜索技术社区讨论（StackOverflow、知乎技术话题、V2EX）
- 查找竞品/同类工具的对比信息
- 示例查询："Claude Code Skills 2.0 更新 eval benchmark"、"OpenClaw 部署 架构"
企业/产品类文章：
- 搜索行业报告、市场数据、权威分析
- 搜索竞品功能和用户评价
- 查找真实案例和成功故事
- 示例查询："AI语言学习 行业报告 2025 2026"、"口语评测 竞品 流利说 ELSA"
活动/社区类文章：
- 搜索活动相关技术背景
- 查找社区/组织的历史和定位
- 了解演讲主题的技术细节
第三步：按风格创作
🏢 风格A：企业官方文案
适用于：产品发布、企业动态、品牌宣传、行业白皮书
语气：专业可信、有温度但有距离感。参考 references/style-guide.md。
核心特征：
- 使用"我们"代表品牌，不用"我"
- 规范书面语，避免口语和网络用语
- 数据和案例支撑每个观点
- 积极正向，突出解决方案
- 遵循敏感词规避（
references/style-guide.md第七节）
结构：
- 引人开头（100-200字）→ 痛点/热点/故事切入
- 核心内容（3-5个小标题展开）→ 每段300-500字，穿插数据案例
- 有力结尾（100-150字）→ 总结 + CTA行动号召
标题风格：参考 references/title-formulas.md，偏向权威型、数字型、福利型。
示例语气：
在数字化转型的浪潮中，语言学习正在经历一场深刻变革。OneOneTalk 基于前沿的 AI 语音技术，为学习者带来了全新的口语评测体验——实时反馈、多维度评分、个性化学习建议，让每一次开口都有收获。
What ships with it
12 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.
- assets/emoji-library.txt 8.3 KB
- assets/template-structure.md 8.3 KB
- evals/routing-evals.json 2.8 KB
- references/linguistic-background.md 3.2 KB
- references/PIPELINE-CONTRACT.md 4.3 KB
- references/quality-checklist.md 9.9 KB
- references/style-guide.md 10 KB
- references/title-formulas.md 8.3 KB
- references/writing-techniques.md 7.2 KB
- schemas/image-manifest.schema.json 3.1 KB
- scripts/render_wechat_layout.py 6.5 KB runs code
- scripts/validate_image_manifest.py 8.1 KB runs code
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.
- 13d ago First seen · 300 lines · 198 tokens per session scan A ef711ded96be
wechat-article-writer is a skill published in the GitHub repository staruhub/ClaudeSkills (712 stars, last pushed 1mo ago), licensed MIT. It adds 198 tokens to every session and 4,043 once invoked, about $0.0010 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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