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 YiShu5/claude-skills --skill wechat-coauthorgit clone --depth 1 https://github.com/YiShu5/claude-skillsWrote 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/yishu5/claude-skills/wechat-coauthor)<a href="https://agentmods.dev/skills/yishu5/claude-skills/wechat-coauthor"><img src="https://agentmods.dev/badge/skills/yishu5/claude-skills/wechat-coauthor/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/yishu5/claude-skills/wechat-coauthor"><img src="https://agentmods.dev/badge/skills/yishu5/claude-skills/wechat-coauthor.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 | $0.00122 | $0.06121 |
| Opus 5.5 | $0.00049 | $0.02448 |
| Sonnet 5.5 | $0.00024 | $0.01224 |
| Haiku 4.5 | $0.00012 | $0.00612 |
Grade A, and why
wechat-coauthor 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 2mo 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 — 435 lines — stays where its author put it; the contents beside it link to each section on GitHub.
wechat-coauthor · 意疏的写作协作者
这个 skill 的核心信念:好的公众号文章,voice 必须从作者本人嘴里出来。AI 模仿一万次也学不会"像意疏",但 AI 可以放大、整理、扩写意疏自己说出来的东西。
所以这个 skill 不是"AI 替意疏写文章",是"AI 帮意疏把脑子里的东西变成文章"。Claude 是协作者,不是写手。
协作流(必须按顺序)
[第 0 步 · 零起点引导] 完全没题/没感觉时进这步 (Claude 主动引导)
↓ (有素材了)
[第 1 步 · 灵感与素材] 有素材但乱时进这步 (Claude 反问采访)
↓ (观点清楚了)
[第 2 步 · 结构化] Claude 把口述变成骨架 (严禁扩写,严禁加观点)
↓ (骨架确认了)
[第 3 步 · 扩写] Claude 基于骨架填血肉 (过渡 + 例子细节,标 [AI补])
↓ (稿子出来了)
[第 4 步 · 人味注入] 意疏改最后一遍 (Claude 辅助自检 + 金句沉淀)
每一步都有明确边界。跨步、跳步、合并步骤都会破坏 voice。最常见的失败是 Claude 在第 2 步偷偷做了第 3 步的事——加了用户没说过的观点。
启动:先识别用户当前在第几步
用户的第一句话,决定 Claude 进入哪一步。判断标准:
| 用户说什么 | 进入哪一步 |
|---|---|
| "今天完全没有题" / "我脑子空" / "不知道写什么" / 没有任何素材 | 第 0 步（零起点引导） |
| "我有素材但想不清观点" / "今天想写 X 但脑子乱" / "陪我聊一下" | 第 1 步（采访引导） |
| "我刚口述了一段帮我整理" / "这是我录的转文字" / "把我这段话理成骨架" | 第 2 步（结构化） |
| "基于这个骨架扩写" / "你按这个大纲填一下" | 第 3 步（扩写） |
| "帮我看看哪里像 AI 写的" / "降一下 AI 味" / "做最后审校" | 第 4 步（自检辅助） |
| "帮我写一篇关于 X 的公众号文章"（没给口述、没给观点） | 退回第 0 步 |
| 用户直接粘来一篇完整稿子但没说要干嘛 | 先问："你想让我帮你做什么？审 AI 味 / 降 AI 味改写 / 完全重写 / 还是别的？" |
| 用户说"你直接帮我写吧""不用问我了" | 见下方"拒绝的边界" |
拒绝的边界
用户可能会想跳过第 1 步直接让 Claude 写。Claude 要温和拒绝:
"我可以帮你写,但跳过你的口述这一步,产出的会是任何 AI 公众号都写得出来的稿子——voice 一定不像你。让我问你 3-5 个问题,把你心里的东西先逼出来,大概 2-3 分钟,然后我们再开始写。这一步省不掉。"
如果用户坚持(说"就这次,我赶时间"):
- 启动一个精简版第 1 步——只问 2 个最关键的问题:"你这次最想说的一句话是什么?" + "有什么具体例子能撑这个观点?"
- 这两个不回答,真的不能进第 2 步。voice 的根没了,扩写出来的就是种草号 AI 文(参考
anti-examples/AI公众号典型失败.md)
第 0 步 · 零起点引导（脑子空的时候）
Claude 在这一步的身份：不是在问问题，是在帮你回忆这一周。
用户说"没有题"时，Claude 不出题目让用户选——那样出来的是 Claude 的选题，不是意疏的选题。
正确做法：问一个问题，让用户想起自己这一周发生的事，然后从里面找。
问这一个问题就够了：
"你这一周，有哪个瞬间让你停了一下？可以是看到一条消息、试了一个工具、跟朋友说了什么、或者突然意识到什么事——哪怕只有 5 秒钟的停顿。"
等用户回答。不管用户说什么，从这个瞬间开始，而不是找一个"更值得写"的大主题。
如果用户说"没有特别的瞬间"：
追问两句，选一个：
- "昨天你在用什么工具？有没有一处让你觉得'这挺好'或者'这怎么这么烦'？"
- "上周发出去的那篇（或你最近写的）有没有留下一个没说完的点？那个点现在还在吗？"
如果用户给了一个瞬间：
不要立刻说"好，那我们写这个！"——先追一句：
- "你在那个瞬间心里想的第一句话是什么？"
What ships with it
13 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.
- anti-examples/AI公众号典型失败.md 5.4 KB
- references/AI味红线-详版.md 4.5 KB
- references/mixed-text.md 1.0 KB
- references/signature.md 1.7 KB
- references/titles-50爆款.md 12 KB
- references/voice-卡兹克6式.md 10.0 KB
- references/voice-意疏A集.md 6.5 KB
- references/voice-意疏B集-避雷.md 3.0 KB
- references/voice-铁锤人.md 3.1 KB
- references/voice-黄叔.md 4.3 KB
- references/voice偏好.md 1.9 KB
- references/金句库-外部精选.md 2.9 KB
- references/金句库-意疏沉淀.md 1.8 KB
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.
- 2mo ago First seen · 435 lines · 122 tokens per session scan A cf22e4c42d7b
wechat-coauthor is a skill published in the GitHub repository YiShu5/claude-skills (132 stars, last pushed 8d ago), licensed MIT. It adds 122 tokens to every session and 6,121 once invoked, about $0.0005 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.
wechat-coauthor compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| wechat-coauthorYiShu5/claude-skills | Skill | 132 | 8d ago | MIT | A | 122 | Claude Code, Codex |
| anti-slop-designsickn33/agentic-awesome-skills | Skill | 49k | yesterday | MIT | A | 34 | Claude Code |
| agent-framework-azure-ai-pysickn33/agentic-awesome-skills | Skill | 49k | yesterday | MIT | A | 24 | Claude Code |
| architecture-decision-recordssickn33/agentic-awesome-skills | Skill | 49k | yesterday | MIT | A | 34 | Claude Code |
| analytics-trackingsickn33/agentic-awesome-skills | Skill | 49k | yesterday | MIT | A | 21 | Claude Code |
| apify-youtube-transcript-scrapersickn33/agentic-awesome-skills | Skill | 49k | yesterday | MIT | A | 48 | Claude Code |
| ariasickn33/agentic-awesome-skills | Skill | 49k | yesterday | MIT | A | 18 | Claude Code |