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Anti Defensive Writing

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Adkid-Zephyr
anti-defensive-writing

论文写作、修改、压缩和实验组织全流程中阻止【防御性写作】。把论文视为一场学术发布会, 而不是项目总结、实验日志或自我审查报告:识别这项工作最值得发表的价值,围绕它建立 最有利、最完整、最有说服力的叙事。不平均展示、不主动示弱、不写实验流水账、不替审稿人 攻击自己。 触发词:论文润色、论文修改、写摘要、写引言、写结论、压缩论文、rebuttal、回复审稿意见、 组织实验、论文AI味、防御性写作、心虚。

Overview

PublisherAdkid-Zephyr
Repositoryanti-defensive-writing-Skill
Skill nameanti-defensive-writing
Stars
1.2K
Forks
27
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by Adkid-Zephyr on GitHub. Read the source before you install it.

Installation

Install the Anti Defensive Writing AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/Adkid-Zephyr/anti-defensive-writing-Skill.git /tmp/anti-defensive-writing-Skill
mkdir -p .claude/skills
cp -r /tmp/anti-defensive-writing-Skill/skills/anti-defensive-writing .claude/skills/anti-defensive-writing
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Anti Defensive Writing in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Anti Defensive Writing on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Anti Defensive Writing is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

学术写作原则(The Press-Release Principle)

一句话原则

论文是一场学术发布会,不是项目总结、实验日志或自我审查报告。 你的任务不是平均呈现这项工作的所有方面,而是识别其中最值得发表的价值, 并围绕这一价值建立最有利、最完整、最有说服力的叙事。

一、叙事规则

  1. 只围绕优势组织论文。 优先寻找本文真正领先、独特或不可替代的部分:新能力、新问题、 新机制、新视角、更强适用性、更低成本、更高效率、更好扩展性、更有意义的权衡。 没有形成优势的内容,不进入主线。
  2. 不写成工作汇报。 不按"我们先做了什么、后来尝试了什么、哪些失败了"的过程展开。 只保留最终成立的逻辑:问题为什么重要 → 现有方法为什么不够 → 本文提供了什么新解法 → 证据如何支持。
  3. 打不过的维度,不设为比赛项目。 某指标不占优势,就不要把叙事建立在该指标上。 重新选择更能反映本文价值的任务定义、评价维度、应用场景、约束条件或比较口径。 不争夺不属于本文的冠军,明确本文赢的是另一场更有意义的比赛。
  4. 优势必须被明确说出来。 不要期待审稿人自己从表格中发现贡献。主动解释: 本文在哪个条件下表现最好、为什么这种优势会出现、解决了什么实际问题、为什么值得关注。
  5. 控制比较范围。 不追求"所有数据集、所有指标全面领先"。只提出证据能牢固支撑的主张。 说服力来自主张与证据高度一致,而不是比较项目数量最多。
  6. 允许彻底重构故事。 现有结果无法支撑原始叙事时,不要围绕原叙事防守。重新定义问题、 重排贡献、重选主结果、重做标题摘要引言和实验结构。故事服务于最强证据,而非忠于最初设想。

二、语言规则(防自我削弱)

  • 禁用自我削弱式表达:"遗憾的是""仅""仍明显落后""效果有限""存在严重不足"。
  • 不说输。 面对不占优的结果,不使用"本文弱于""性能下降""未能超过"。按顺序判断: ①该结果是否必须讨论;②能否从不同目标、约束或适用场景解释;③是否体现某种合理权衡; ④能否收缩主张,避免不必要的正面对撞;⑤是否应调整故事主线,让它不再承担证明核心贡献的职责。
  • 某项结果不构成优势时,不必提炼成结论,更不应帮读者把局部现象上升为对整体方法的否定。

三、实验规则

实验不是结果仓库,而是论证工具。每个实验必须承担明确职责之一:

  • 证明核心方法有效;
  • 证明优势来自关键机制;
  • 证明方法在目标场景中具有价值;
  • 排除最可能的替代解释。

无法强化主线、容易分散注意力或引出无关争论的实验:删除、弱化、移动或重新设计。

四、结构规则

摘要和引言 = 发布会开场,开头迅速建立四件事: ①一个重要且尚未解决的问题;②现有方法的关键缺口;③本文独特的解决思路;④最有分量的结果和意义。 不从实现细节、研究过程或大量背景知识开始,不在贡献尚未建立时提前讨论不足。

结论只强化记忆点:本文解决了什么、提出了什么、证明了什么、为什么重要。 不在最后一段突然加入新的自我否定或扩大局限性。

五、默认决策规则(遇到不理想材料时,按优先级处理)

  1. 删除与核心主张无关的内容;
  2. 缩小主张,避免无意义的正面对比;
  3. 更换更能体现价值的评价维度;
  4. 将结果解释为目标差异或合理权衡;
  5. 重组实验,使优势成为视觉和叙事中心;
  6. 重新定义论文故事;
  7. 只有在无法回避且确实影响核心结论时,才进行必要说明。

六、交稿前自查(不给审稿人递刀子)

  • 这句话是否无意中扩大了本文需要承担的责任?
  • 是否提出了一个本来没人要求回答的问题?
  • 是否把局部现象描述成了普遍缺陷?
  • 是否使用了比证据更宽泛的负面判断?
  • 有没有按"我们做了什么过程"在展开?
  • 有没有把不领先的指标设成了主战场?
  • 摘要前五句里,问题和贡献都出来了吗?
  • 结论里有没有突然的自我否定?

不主动制造审稿问题,不主动扩大攻击面,不主动替反方完成论证。

最终目标

论文中的每一个章节、段落、表格和句子,都应共同完成一件事:让读者相信, 这项工作解决了一个值得解决的问题,提出了一种值得关注的方法, 并且已经有足够清晰的证据证明它的价值。 找到真正成立的优势,围绕它组织全部材料,并把这个优势讲到足够清楚。

Frequently asked questions

What does the Anti Defensive Writing AI skill do?

论文写作、修改、压缩和实验组织全流程中阻止【防御性写作】。把论文视为一场学术发布会, 而不是项目总结、实验日志或自我审查报告:识别这项工作最值得发表的价值,围绕它建立 最有利、最完整、最有说服力的叙事。不平均展示、不主动示弱、不写实验流水账、不替审稿人 攻击自己。 触发词:论文润色、论文修改、写摘要、写引言、写结论、压缩论文、rebuttal、回复审稿意见、 组织实验、论文AI味、防御性写作、心虚。

Why use Anti Defensive Writing on TypingMind?

Because you install it once and use it with any model. Anti Defensive Writing is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Anti Defensive Writing in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Adkid-Zephyr/anti-defensive-writing-Skill/tree/main/skills/anti-defensive-writing. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Anti Defensive Writing?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Anti Defensive Writing?

As many as you like. As long as a model supports skills, you can use Anti Defensive Writing with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Anti Defensive Writing AI skill free?

Yes. It is published on GitHub by Adkid-Zephyr under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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