summarize
Summarize extracted paper text into concise Markdown memory for later Stage 2 and Stage 4 background use, with fixed section…
Remove AI-generated writing patterns from rebuttal prose to make it sound natural, direct, and authentically human-authored. Use when a Stage 2 refined draft or Stage 4 follow-up response reads too formulaic, robotic, or "GPT-like". Supports academic English.
$ npx -y skills add runtsang/rebuttalstudio --skill writing-anti-ai --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/writing-anti-aiContext preview
The summary Claude sees to decide when to auto-load this skill.
Remove AI-generated writing patterns from rebuttal prose to make it sound natural, direct, and authentically human-authored. Use when a Stage 2 refined draft or Stage 4 follow-up response reads too formulaic, robotic, or "GPT-like". Supports academic English.
name: writing-anti-ai description: Remove AI-generated writing patterns from rebuttal prose to make it sound natural, direct, and authentically human-authored. Use when a Stage 2 refined draft or Stage 4 follow-up response reads too formulaic, robotic, or "GPT-like". Supports academic English. tags: [Writing, Rebuttal, Anti-AI, Humanizer, Polish] version: 1.0.0 source: Adapted from Claude Scholar (https://github.com/Galaxy-Dawn/claude-scholar), skills/writing-anti-ai/SKILL.md. Original authored by gaoruizhang; based on Wikipedia's "Signs of AI writing" guide (WikiProject AI Cleanup).
> **RebuttalStudio Utility — Stage 2 / Stage 4 / Polish** > Apply this skill after Stage 2 refinement or Stage 4 follow-up drafting when the output reads formulaic or over-polished. Use before the Stage 3 document compilation to ensure the final rebuttal sounds authored by a researcher, not generated by a model.
Remove predictable AI writing patterns from rebuttal text so it reads as natural, confident academic prose — not as machine-generated boilerplate.
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Reviewers are experienced academics who read hundreds of papers and rebuttals. A rebuttal that sounds AI-generated signals:
The goal is not to hide AI assistance — it's to ensure the **ideas and voice** of the actual authors come through clearly.
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LLMs predict statistically likely continuations. This produces text that applies to the widest variety of cases — which is exactly what makes it feel generic in a rebuttal. Rebuttal prose needs to be *specific* to this paper, this reviewer, and this concern.
**Core principle**: Every sentence in a rebuttal should only be true for *this* paper. If it could appear in any rebuttal, rewrite it.
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Remove throat-clearing openers and emphasis crutches that add length without adding meaning.
**Common AI openers to remove:**
**AI emphasis phrases to cut:**
AI tends toward predictable patterns. In rebuttals, these appear as:
| AI Pattern | Rebuttal Fix | |-----------|-------------| | "It's not just X, it's also Y" (negative parallelism) | Drop it; state Y directly | | "First… Second… Third…" for every single response | Only use numbered lists when the reviewer explicitly listed multiple concerns | | Em-dash reveals: "X — which shows Y" | "X, which shows Y" or split into two sentences | | "This represents a significant advancement…" | State what changed specifically |
Check sentence length distribution in each response block:
Reviewers are experts. Do not over-explain or over-justify.
**Bad (patronizing):** "To ensure complete clarity, and so that the reviewer can fully appreciate our contribution, we explain in detail…"
**Good:** "To clarify: [the specific point]."
**Bad (hand-holding):** "It could potentially be argued that the metric might perhaps be considered somewhat limited in scope."
**Good:** "The metric has a known limitation: [state it]. We address this in Appendix B."
If a sentence sounds like it was written to be quoted or highlighted, rewrite it.
**Bad:** "This represents a paradigm shift in how the community will approach [problem]."
**Good:** "The method reduces [specific metric] by X% over [specific baseline], enabling [specific application]."
Academic rebuttals use "we" — but AI-generated text often over-hedges or over-personalizes.
**Too hedged:** "The authors feel that it may be the case that…" → "We argue that…" **Over-personalized:** "We personally believe that…" → "We believe that…"
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These words are statistically overrepresented in AI-generated academic text:
| Overused | Replace With | |----------|-------------| | additionally | also / and / (restructure sentence) | | furthermore | (restructure sentence) | | notably | (delete or be specific) | | it is worth noting | (just state the point) | | comprehensive | thorough / complete (or be specific) | | leverage | use | | utilize | use | | facilitate | help / enable | | demonstrate | show | | novel | (be specific about what is new) |
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Rate each response block (0–10 points each):
| Dimension | 0 pts | 10 pts | |-----------|-------|--------| | **Directness** | Opens with filler, buries the answer | States the answer in the first sentence | | **Specificity** | Could appear in any rebuttal | References this specific paper, reviewer comment, or result | | **Rhythm** | All sentences same length | Mix of short and long sentences | | **Tone** | Defensive or overly formal | Collegial, confident, factual | | **Density** | Padded with acknowledgments | Information-dense; every sentence moves forward |
**40–50**: Ready to submit. **30–39**: Needs targeted edits. **< 30**: Rewrite from outline.
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This skill only removes AI patterns. Do **not**:
A rebuttal editor for researchers to craft high-quality academic rebuttals — so you can focus on what to say, not how to format it.
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