article-proofreading

article-proofreading is a skill for Claude Code, Codex from TashanGKD/tashan-writing-system. It costs 80 tokens per session (3,951 once invoked), scanned A, a copy of smart-search, MIT.

A Chinese-language editing checklist based on a specific reviewer’s standards for examining article drafts. It checks artificial-sounding phrasing, problematic titles, absolute claims, confusing structure, and incomplete endings.

In plain words
What is it for?
It is for reviewing Chinese article drafts, listing issues across five separate checks, and proposing corrections with priorities.
Why use it?
It gives writers a consistent way to find wording and structure problems instead of relying only on a general proofreading pass.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit It is for reviewing Chinese article drafts, listing issues across five separate checks, and proposing corrections with priorities.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/tashangkd/tashan-writing-system/article-proofreading
Install

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.

Any agent
npx skills add TashanGKD/tashan-writing-system --skill article-proofreading
Clone the repo
git clone --depth 1 https://github.com/TashanGKD/tashan-writing-system

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for article-proofreading

README.md
[![agentmods](https://agentmods.dev/badge/skills/tashangkd/tashan-writing-system/article-proofreading/github.svg)](https://agentmods.dev/skills/tashangkd/tashan-writing-system/article-proofreading)
Your own site
<a href="https://agentmods.dev/skills/tashangkd/tashan-writing-system/article-proofreading"><img src="https://agentmods.dev/badge/skills/tashangkd/tashan-writing-system/article-proofreading/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.

agentmods 80×15 button for article-proofreading

Your own site · 80×15
<a href="https://agentmods.dev/skills/tashangkd/tashan-writing-system/article-proofreading"><img src="https://agentmods.dev/badge/skills/tashangkd/tashan-writing-system/article-proofreading.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 80 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,951 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 86% copy Near-identical to another mod in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00080 $0.03951
Opus 5 $0.00040 $0.01975
Sonnet 5 $0.00016 $0.00790
Haiku 4.5 $0.00008 $0.00395

Measured 9d ago against content hash 1a1689e6a3a5, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

article-proofreading 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 9d 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.

Origin

This is a copy

86% identical to smart-search — 393 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

skills/article-proofreading/SKILL.md · 344 lines

How it starts

The opening of the file, as written. The whole thing — 344 lines — stays where its author put it; the contents beside it link to each section on GitHub.

文章审稿 Skill

基于郑总历次亲手修改、明确批注的审稿标准。五轮检查,每轮独立列问题清单,最后给出优先级。

参考文档:_内部总控/AI思维碎片/写作习惯与风格手册.md


知识导航表(执行前必须理解的概念根)

层级 文档 需要理解的概念
D0 认知根(必读) _内部总控/AI思维碎片/写作习惯与风格手册.md 郑总审稿标准的完整来源:AI腔定义/标题4种错误/绝对表达清单/结语要求(本 Skill 的知识根)
D3 规范参考 本 Skill 本身就是规范定义,无需外部规范参考
D4 运行时数据 目标文章草稿(用户提供) 被审稿的文章(审查对象)

核心概念速查: ① AI腔 = 「此外」「总之」「值得注意的是」「不仅如此」「综上所述」等AI写作套话 ② 标题4种错误 = 过度承诺/空泛标题/AI腔标题/不够具体 ③ 审稿顺序不变:AI腔→标题→绝对表达→结构层次→结语,五轮独立,不合并


第一轮:AI腔检测

1.1 翻译感词汇

逐句扫描,标记所有让人感觉是从英文直译的词:

常见AI腔词 改法
人层 人类层
工具层(指代"人"所在的层次时) 视语境调整
首先/其次/最后 作为枚举句式 直接说内容,不用序数铺垫

判断原则:读出声来感觉别扭、或是翻译腔的,就标记。


1.2 元评论过渡句(零信息量的宣告)

❌ 直接删除下列句式,不要任何替换,直接说内容:

  • "核心推论只有一句话:"
  • "这张表说明一件事:"
  • "有以下几点值得关注:"
  • "这里有X条标准……"
  • "值得注意的是,"
  • "总的来说,"(在段落中间出现时)
  • "不难发现,"

✅ 替换方式:删掉这句话,下一句直接用"所以,""因此,"开头,或无连接词直接开始。

为什么是AI腔:这类句子是在"宣告接下来要说什么",本身没有任何信息量。真正有力的表达直接说出内容,不需要预热。


1.3 防守性修饰(替读者预设反驳)

❌ 检查并删除以下模式:

  • "这不是X,而是Y"——当Y是在为自己的判断辩护时
  • "这不是未来的预测,而是正在发生的结果"
  • "很多人可能会认为……但实际上……"(不必要的假想敌)
  • "这一点很重要"(让读者评判,不要自己标注)
  • "不可否认……但……"

✅ 正确做法:直接陈述结论,不加防守。读者自会判断。

例外"不是X,而是Y" 用于积极的对比陈述(如"不是界面做简洁,而是设计路径的根本颠倒")可以保留——区分在于它是断言,不是辩护。


1.4 "这里有" 套话

❌ 删除:

  • "这里有一条核心原则……"
  • "这里有五条判断标准……"
  • "接下来我们来看……"

✅ 直接进入实质内容。


第二轮:标题质量(四种错误类型)

对每个章节/小节标题,依次用四个问题判断:

2.1 是结论,还是话题/方法描述?

检测:标题能否独立表达一个观点?还是只在描述"这节讲什么"?

❌ 错误例:产品机会的来源:三类永恒坐标 × AI 带来的成本变化 → 说的是"我用什么框架分析",不是"分析得出什么"

✅ 正确例:旧瓶颈正在消失,把它们做好是把错的做对 → 表达一个判断,读者读到标题就知道该相信什么

识别错误标题的特征

  • "X 的来源:A × B"(描述分析框架)
  • "X 的结构:A、B、C"(描述内容组成)
  • "X 的维度/原则/方法"(描述分类方式)

2.2 是机制,还是本质/原则?

检测:标题里有"设计/使用/实现/建立/优化"等动词 → 往往是机制描述,不是结论。

❌ 错误例:为人与智能体同时设计两层界面 → 说的是"如何做"(机制)

✅ 正确例:产品设计的第一性原理:Human-Readable + Agent-Operable → 说的是"这个机制揭示了什么设计原则"(本质)

改法:把"如何做"升级为"这样做意味着什么、揭示了什么"。


2.3 是定性,还是从定性推出的原则?

检测:标题只是给某个概念贴了一个标签(定性),而没有给出从这个定性推导出的行动原则。

❌ 错误例:产品的本质变了:人与其数字员工协作的介质 → "介质"是定性(说"是什么"),信息量低

✅ 正确例:产品设计的第一性原理:Human-Readable + Agent-Operable → 从"介质"这个定性推出的设计原则,信息量更高

Read the full file on GitHub · 344 lines

Changes

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.

  1. 9d ago First seen · 344 lines · 80 tokens per session scan A 1a1689e6a3a5

Subscribe to this mod's changes

article-proofreading is a skill published in the GitHub repository TashanGKD/tashan-writing-system (2 stars, last pushed 5mo ago), licensed MIT. It adds 80 tokens to every session and 3,951 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. It is 86% identical to smart-search, differing in 393 lines, and is treated as a copy.

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