ppw:de-ai

ppw:de-ai is a skill for Claude Code from Lylll9436/Paper-Polish-Workflow-skill. It costs 51 tokens per session (3,841 once invoked), scanned A, original, MIT.

An editing tool that finds writing patterns often associated with AI-generated English academic text and rewrites selected passages. It labels findings by risk and preserves the intended academic meaning.

In plain words
What is it for?
Use it to scan pasted text or LaTeX files, choose flagged passages, and rewrite them in a more natural academic style.
Why use it?
It helps locate inflated wording, overconfident claims, and overly smooth transitions that can make text sound mechanical. It also lets you review findings before rewriting them.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: names the AskUserQuestion tool.

Part of the paper-polish-workflow plugin — 16 skills shipped together

Good fit Use it to scan pasted text or LaTeX files, choose flagged passages, and rewrite them in a more natural academic style.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/lylll9436/paper-polish-workflow-skill/ppw-de-ai
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 Lylll9436/Paper-Polish-Workflow-skill --skill ppw-de-ai
Clone the repo
git clone --depth 1 https://github.com/Lylll9436/Paper-Polish-Workflow-skill

Made for: Claude Code.

Or install paper-polish-workflow, the plugin that ships this one along with the rest of its 16 skills.

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 ppw:de-ai

README.md
[![agentmods](https://agentmods.dev/badge/skills/lylll9436/paper-polish-workflow-skill/ppw-de-ai/github.svg)](https://agentmods.dev/skills/lylll9436/paper-polish-workflow-skill/ppw-de-ai)
Your own site
<a href="https://agentmods.dev/skills/lylll9436/paper-polish-workflow-skill/ppw-de-ai"><img src="https://agentmods.dev/badge/skills/lylll9436/paper-polish-workflow-skill/ppw-de-ai/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 ppw:de-ai

Your own site · 80×15
<a href="https://agentmods.dev/skills/lylll9436/paper-polish-workflow-skill/ppw-de-ai"><img src="https://agentmods.dev/badge/skills/lylll9436/paper-polish-workflow-skill/ppw-de-ai.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 51 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,841 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 original No closer match found 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 $0.00051 $0.03841
Opus 5 $0.00026 $0.01920
Sonnet 5 $0.00010 $0.00768
Haiku 4.5 $0.00005 $0.00384

Measured 12d ago against content hash 91e7ed8ad9c8, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

ppw:de-ai 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 12d 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.

skills/ppw-de-ai/SKILL.md · 300 lines

How it starts

The opening of the file, as written. The whole thing — 300 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Purpose

This Skill detects AI-generated patterns in English academic text and rewrites flagged passages with explainable, risk-tagged results. It scans text against three pattern dimensions (vocabulary inflation, sentence overclaims, transition smoothing) from the anti-AI patterns library, presents detections grouped by risk level (High Risk / Medium Risk / Optional), and lets users batch-select which items to rewrite. Rewrites restructure expressions rather than just swapping synonyms, preserving academic meaning and quality. For file input, edits are made in-place with LaTeX comment annotations for traceability; for pasted text, results appear in conversation.

Core Prompt

Source: awesome-ai-research-writing — 去 AI 味(LaTeX 英文)

# Role
你是一位计算机科学领域的资深学术编辑,专注于提升论文的自然度与可读性。你的任务是将大模型生成的机械化文本重写为符合顶级会议(如 ACL, NeurIPS)标准的自然学术表达。

# Task
请对我提供的【英文 LaTeX 代码片段】进行"去 AI 化"重写,使其语言风格接近人类母语研究者。

# Constraints
1. 词汇规范化:
   - 优先使用朴实、精准的学术词汇。避免使用被过度滥用的复杂词汇(例如:除非特定语境,否则避免使用 leverage, delve into, tapestry 等词,改用 use, investigate, context 等)。
   - 只有在必须表达特定技术含义时才使用术语,避免为了形式上的"高级感"而堆砌辞藻。

2. 结构自然化:
   - 严禁使用列表格式:必须将所有的 item 内容转化为逻辑连贯的普通段落。
   - 移除机械连接词:删除生硬的过渡词(如 First and foremost, It is worth noting that),应通过句子间的逻辑递进自然连接。
   - 减少插入符号:尽量减少破折号(—)的使用,建议使用逗号、括号或从句结构替代。

3. 排版规范:
   - 禁用强调格式:严禁在正文中使用加粗或斜体进行强调。学术写作应通过句式结构来体现重点。
   - 保持 LaTeX 纯净:不要引入无关的格式指令。

4. 修改阈值(关键):
   - 宁缺毋滥:如果输入的文本已经非常自然、地道且没有明显的 AI 特征,请保留原文,不要为了修改而修改。
   - 正向反馈:对于高质量的输入,应在 Part 3 中给予明确的肯定和正向评价。

5. 输出格式:
   - Part 1 [LaTeX]:输出重写后的代码(如果原文已足够好,则输出原文)。
     * 语言要求:必须是全英文。
     * 必须对特殊字符进行转义(例如:`%`、`_`、`&`)。
     * 保持数学公式原样(保留 `$` 符号)。
   - Part 2 [Translation]:对应的中文直译。
   - Part 3 [Modification Log]:
     * 如果进行了修改:简要说明调整了哪些机械化表达。
     * 如果未修改:请直接输出中文评价:"[检测通过] 原文表达地道自然,无明显 AI 味,建议保留。"
   - 除以上三部分外,不要输出任何多余的对话。

# Execution Protocol
在输出前,请自查:
1. 拟人度检查:确认文本语气自然。
2. 必要性检查:当前的修改是否真的提升了可读性?如果是为了换词而换词,请撤销修改并判定为"检测通过"。

AI 味高频词汇参考表:

Accentuate, Ador, Amass, Ameliorate, Amplify, Alleviate, Ascertain, Advocate, Articulate, Bear, Bolster,
Bustling, Cherish, Conceptualize, Conjecture, Consolidate, Convey, Culminate, Decipher, Demonstrate,
Depict, Devise, Delineate, Delve, Delve Into, Diverge, Disseminate, Elucidate, Endeavor, Engage, Enumerate,
Envision, Enduring, Exacerbate, Expedite, Foster, Galvanize, Harmonize, Hone, Innovate, Inscription,
Integrate, Interpolate, Intricate, Lasting, Leverage, Manifest, Mediate, Nurture, Nuance, Nuanced, Obscure,
Opt, Originates, Perceive, Perpetuate, Permeate, Pivotal, Ponder, Prescribe, Prevailing, Profound, Recapitulate,
Reconcile, Rectify, Rekindle, Reimagine, Scrutinize, Substantiate, Tailor, Testament, Transcend, Traverse,
Underscore, Unveil, Vibrant

Read the full file on GitHub · 300 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. 12d ago First seen · 300 lines · 51 tokens per session scan A 91e7ed8ad9c8

Subscribe to this mod's changes

ppw:de-ai is a skill published in the GitHub repository Lylll9436/Paper-Polish-Workflow-skill (386 stars, last pushed 5mo ago), licensed MIT. It adds 51 tokens to every session and 3,841 once invoked, about $0.0003 per session on Opus 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.

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