Skill: cellinlab/cell-ai-writing-diagnosis (version 0.1.0)

--- name: ai-writing-diagnosis description: AI-writing fingerprint diagnosis for Chinese text. Use when Codex needs to inspect a draft for overly smooth, formulaic, generic, or authorless writing patterns; quote the exact passages that feel machine-made; distinguish real problems from false alarms; and suggest what to fix first without immediately rewriting the whole piece. metadata: {"openclaw":{"homepage":"https://github.com/cellinlab/cell-skills/tree/main/skills/ai-writing-diagnosis"}} --- # AI Writing Diagnosis ## Overview Use this skill when the user suspects a draft feels too AI-generated, too smooth, too tidy, or too generic. The default task is diagnosis, not rewrite. The goal is to show: - where the text starts feeling machine-made - which pattern is causing that feeling - whether the problem actually harms the piece - what the user should fix first if they want stronger human presence ## Quick Start 1. Read the full text once for overall feel. 2. Ask what genre it is if that changes the judgment materially. 3. Mark the strongest suspicious passages in reading order. 4. Explain each issue concretely with the quoted text. 5. End with the dominant pattern and the highest-leverage fix. If the piece is mostly fine, say so. Do not force problems into the report. ## Default Contract Assume the following unless the user says otherwise: - write in Chinese - diagnose first, rewrite later - judge the text in reading order - quote the exact text when calling out a problem - do not treat every clean sentence as "AI flavor" - care about whether the pattern hurts expression, not whether it merely looks polished ## Workflow ### Step 1: Establish the Reading Context Determine: - the genre: article, short post, script, memo, email, thread, or caption - whether the user wants diagnosis only - whether the user is worried about "AI flavor" in general or a specific part Genre matters. A short script may tolerate more compact slogans than a long essay. ### Step 2: Read for Global Texture Before annotating details, notice the overall signal: - too smooth - too symmetric - too abstract - too certain - too generic - or actually fine ### Step 3: Annotate the Text in Order For each suspicious passage: - quote the line or short segment - explain what feels off - tag the pattern type - note severity based on how much it harms the piece Read [references/pattern-catalog.md](references/pattern-catalog.md) when classification is not obvious. ### Step 4: Distinguish Real Problems from False Alarms Examples: - a crisp structure in a professional memo is not automatically AI - a short social post may intentionally use slogan-like compression - one binary contrast sentence is not a problem by itself Do not confuse "I notice a pattern" with "this must be fixed." ### Step 5: Suggest the Highest-Leverage Fix End with: - the dominant pattern or two - the first places worth revising - whether the user should self-edit or hand it to `$celf-style-writer` If the user explicitly wants rewriting help, read [references/rewrite-guidance.md](references/rewrite-guidance.md) before proposing next questions or edits. ## Output Format Default to [assets/report-template.md](assets/report-template.md). At minimum, include: - total number of notable hits - quoted passages in order - concrete explanation for each hit - dominant pattern summary - priority fix suggestion ## Hard Rules Do not: - rewrite the whole piece unless the user asks - call everything AI just because it is neat - diagnose without quoting the offending passage - confuse stylistic preference with a real flaw - offer fake certainty when the signal is weak Always: - read in sequence - quote specific text - explain what the pattern is doing to the reading experience - note when a hit may be a false alarm - end with the most useful revision priority ## Resource Map - [references/pattern-catalog.md](references/pattern-catalog.md) - Read for the common AI-writing fingerprints, examples, and false-alarm notes. - [references/rewrite-guidance.md](references/rewrite-guidance.md) - Read for what to ask before revising and how to move from diagnosis to rewrite. - [assets/report-template.md](assets/report-template.md) - Use for the standard diagnosis report.

path: agents/openai.yaml
content: interface:
  display_name: "AI 写作诊断"
  short_description: "逐段指出文本里真正像 AI 的地方，而不是一上来全篇重写"
  default_prompt: "Use $ai-writing-diagnosis to inspect this Chinese draft for AI-writing fingerprints: quote the suspicious passages in reading order, explain exactly what feels too smooth, formulaic, generic, or authorless, and tell me what to fix first without rewriting the whole piece."


path: assets/report-template.md
content: # AI 写作诊断报告

**命中 X 处值得注意的问题**

## 第 1 处

> 

- 问题说明：
- 指纹类型：
- 严重度：

## 第 2 处

> 

- 问题说明：
- 指纹类型：
- 严重度：

## 第 3 处

> 

- 问题说明：
- 指纹类型：
- 严重度：

## 总体判断

- 主导问题：
- 是否存在误伤可能：
- 优先修改位置：

## 下一步建议

- 


path: references/pattern-catalog.md
content: # AI 写作高频指纹目录

## 1. 过度光滑

表现：

- 句子全都太稳
- 没有犹豫、摩擦、跳点或人的停顿感

风险：

- 读起来正确，但没有人味

## 2. 模板式开场

表现：

- 一开头就在概括意义
- 读者还没进入具体情境，就被告知“这件事很重要”

风险：

- 太像标准答案

## 3. 高频二元翻转

表现：

- 频繁使用“不是 X，而是 Y”或同类结构

风险：

- 一两次可以，密度高了就很像机器在显得聪明

## 4. 排比和节奏过匀

表现：

- 连续几句长度、结构、力道几乎一样

风险：

- 句子像流水线出来的，不像人自然说话

## 5. 抽象名词堆积

表现：

- 价值、认知、系统、底层逻辑、能量感之类词很多
- 场景、动作、对象很少

风险：

- 看起来懂很多，实际上抓不住内容

## 6. 虚假确定性

表现：

- 所有判断都像定论
- 完全看不到边界、条件和犹豫

风险：

- 失真，且容易让人感觉不像真人思考过程

## 7. 替读者造靶子

表现：

- 虚构一个很笨的反方声音，再轻松击倒

风险：

- 论证看似有层次，实则像自问自答

## 8. 概念命名过密

表现：

- 动不动给一个普通现象起新名词

风险：

- 像在表演洞察，而不是在传达理解

## 9. 金句化收束过多

表现：

- 每段都想用一句漂亮话收尾

风险：

- 文本过度抛光，失去自然推进

## 10. 连接词翻译腔

表现：

- 过多使用“事实上”“值得注意的是”“某种意义上”“基于此”

风险：

- 书面且泛，容易显得不像人在说话

## 11. 细节假具体

表现：

- 句子像有细节，但细看只是伪具体
- 比如“某个瞬间”“很多时候”“一种复杂感受”

风险：

- 既不抽象得干净，也不具体得真实

## 12. 过整齐的结尾祝福

表现：

- 文章其实已经结束，却又补一段温柔总结或鼓励

风险：

- 像模型在找一个“正确结束姿势”

## 误伤提醒

以下情况不要轻易误判：

- 体裁本来就需要更工整，例如正式说明、商务邮件、提纲
- 作者本身就喜欢克制表达
- 一次性的修辞动作不等于高密度模板化


path: references/rewrite-guidance.md
content: # 从诊断走向修改

## 1. 默认不要直接重写

先问自己：

- 作者原本想突出什么
- 哪个模式最伤文本
- 是局部修，还是要换整段逻辑

## 2. 先追问意图

常见追问：

- 你这里是想显得更有力，还是更有层次？
- 这句漂亮话里，真正不能丢的意思是什么？
- 这里有没有一个你真实见过的场景，可以替代抽象结论？
- 你愿不愿意保留一点犹豫，而不是把它写成定论？

## 3. 修改优先级

优先改：

- 开头第一段
- 重复出现的句式模式
- 抽象词堆最多的段落
- 最后那段多余的总结

后改：

- 少量单句措辞
- 不影响整体阅读的弱信号

## 4. 何时交给 celf-style-writer

更适合交接给 `$celf-style-writer` 的情况：

- 用户不只是想去掉 AI 味，还想要更强的活人气质
- 用户希望文字更像 Cell 风格
- 当前问题已经不只是指纹，而是整篇没有作者姿态


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)