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academic-writing-refiner

Refine academic writing for computer science research papers targeting top-tier venues (NeurIPS, ICLR, ICML, AAAI, IJCAI, ACL, EMNLP, NAACL, CVPR, WWW, KDD, SIGIR, CIKM, and similar). Use this skill whenever a user asks to improve, polish, refine, edit, or proofread academic or research writing — including paper drafts, abstracts, introductions, related work sections, methodology descriptions, experiment write-ups, or conclusion sections. Also trigger when users paste LaTeX content and ask for writing help, mention "camera-ready", "rebuttal", "paper revision", or reference any academic venue or conference. This skill handles both full paper refinement and section-by-section editing.

Why use this skill?

Refine and polish your computer science research papers for top-tier conferences like NeurIPS, ACL, and CVPR with this AI-powered writing assistant.

skill-install — Terminal

Install via CLI (Recommended)

clawhub install openclaw/skills/skills/zihan-zhu/academic-writing-refiner
Or

What This Skill Does

The academic-writing-refiner is a specialized OpenClaw agent skill designed to elevate technical drafts to the standards required by top-tier computer science conferences such as NeurIPS, ICLR, ICML, ACL, and CVPR. It acts as an expert peer reviewer and technical editor, focusing on clarity, conciseness, and structural integrity. The skill moves beyond simple grammar correction by ensuring that technical claims are precise, the narrative flow is logical, and the terminology adheres to the rigorous conventions of machine learning, NLP, and systems research. It excels at transforming dense, jargon-heavy, or poorly structured prose into authoritative, publication-ready text that communicates research contributions efficiently.

Installation

To install this skill, run the following command in your terminal: clawhub install openclaw/skills/skills/zihan-zhu/academic-writing-refiner

Use Cases

This skill is perfect for researchers, PhD students, and data scientists looking to improve their paper drafts. It is specifically useful for:

  • Polishing an abstract to ensure it hits the 'problem-approach-result-impact' structure within strict word counts.
  • Restructuring 'Related Work' sections to avoid 'laundry list' descriptions and instead synthesize thematic comparisons.
  • Refining Introduction sections to create a more compelling narrative 'hook' that clearly identifies the research gap.
  • Editing LaTeX manuscripts for final submission or camera-ready versions.
  • Providing feedback on technical clarity in methodology sections to ensure that reviewers can easily follow the logic.

Example Prompts

  • 'I am preparing a camera-ready version for NeurIPS. Could you polish the Abstract and Introduction of this paper? Here is the current text: [Paste text]'
  • 'My Related Work section feels like a list of papers. Can you help me rewrite it to group these by theme and clearly distinguish my work from existing literature?'
  • 'Please review this LaTeX snippet from my methodology section. The logic feels weak; can you tighten the phrasing to make it more precise and authoritative?'

Tips & Limitations

  • Context is King: Always provide the target conference venue if known, as stylistic preferences differ between communities (e.g., ML vs. NLP).
  • Structural Focus: For best results, share your outline or core contribution points alongside the text.
  • Limitations: The skill is an editor, not a substitute for research. It cannot verify the correctness of your experiments or proofs, so ensure your technical values are accurate before pasting. It works best on sections rather than entire 30-page PDFs at once; submit piece-by-piece for maximum depth.

Metadata

Author@zihan-zhu
Stars879
Views1
Updated2026-02-11
View Author Profile
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Add to Configuration

Paste this into your clawhub.json to enable this plugin.

{
  "plugins": {
    "official-zihan-zhu-academic-writing-refiner": {
      "enabled": true,
      "auto_update": true
    }
  }
}

Tags(AI)

#academic-writing#latex#research#paper-editing#technical-writing
Safety Score: 5/5