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cell-ai-writing-diagnosis细胞 AI 写作诊断

Agent Skill

用于辅助文档、README、Markdown、说明文和内容稿件的整理与改写。它适合让 Agent 提炼结构、补齐章节、统一术语、检查链接或把零散材料整理成可读文档。使用时应保留项目已有事实、命令和路径,不要把未确认的信息写成确定结论;涉及对外文案时,还需要控制语气,避免过度营销或夸大能力。

总安装

3,744

周安装

150

GitHub Stars

公开资料未说明

下载量

1,212
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:cell-ai-writing-diagnosis(细胞 AI 写作诊断)
来源仓库:https://github.com/cellinlab/cell-ai-writing-diagnosis
安装命令:
openclaw skills install cell-ai-writing-diagnosis
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install cell-ai-writing-diagnosis

简介

cell-ai-writing-diagnosis 检测 AI 生成文本是否过于流畅或无作者特征。

  • 适合在 OpenClaw 中审查草稿的真实性和原创性。
  • 通过 clawhub 安装,提供中文文本指纹分析报告。
  • 使用前应上传待检文本片段并设置敏感度阈值。cell-ai-writing-diagnosis 属于开发类 Skill,可作为该场景下的辅助能力补充。
  • 建议核对原始文档了解判定标准和人工复核建议。

SKILL.md

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 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 before proposing next questions or edits.

Output Format

Default to 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

- Read for the common AI-writing fingerprints, examples, and false-alarm notes.

- Read for what to ask before revising and how to move from diagnosis to rewrite.

- Use for the standard diagnosis report.

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

89.73%
按下载量换算1,088

安全审计

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通过

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通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

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