Paper Assistant for Openclaw

A comprehensive academic writing assistant designed to transform raw research ideas into structured, professional thesis content and formal papers.

52yuanchangxing
v1.0.0
Mar 11, 2026
1
1.2k
0

Install & Download

1. ClawHub CLI

The fastest way to install a skill directly from the registry.

npx clawhub@latest install paper-assistant

2. Manual Installation

Copy the skill folder to one of these locations

Global
~/.openclaw/skills/
Workspace
<project>/skills/

Priority: Workspace > Local > Bundled

3. Prompt Installation

Copy this prompt to OpenClaw to install it automatically.

Help me install paper-assistant using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).

Prefer to download?

Get the raw skill files in a ZIP archive.

What is Paper Assistant?

Paper Assistant is a specialized AI agent skill within the Openclaw Skills ecosystem, meticulously crafted for academic excellence. It serves as a dedicated partner for undergraduate, graduate, and doctoral researchers, as well as scholars preparing journal submissions. The skill focuses on converting vague research concepts into clear, structured, and formally articulated academic documents.

Built with a focus on structural integrity and logical progression, Paper Assistant ensures that every piece of writing adheres to rigorous academic standards. It prioritizes actionability, providing users with ready-to-use text rather than abstract advice, making it an essential component for anyone using Openclaw Skills for high-stakes academic projects.

Paper Assistant Use Cases

  • Writing and optimizing undergraduate, master's, and doctoral dissertations.
  • Developing comprehensive research proposals and opening reports.
  • Generating systematic literature reviews categorized by theme, methodology, or timeline.
  • Converting colloquial drafts into formal academic prose through professional polishing.
  • Preparing high-impact abstracts and highlight summaries for journal submissions.
  • Designing research methodologies including qualitative, quantitative, and case study frameworks.

How Paper Assistant Works

  1. The user initiates a request by providing a research theme, a specific chapter requirement, or a rough draft.
  2. The skill analyzes the input to identify the academic level and the missing core elements such as research objects, problems, and methods.
  3. It prioritizes the creation of a logical structure or multi-level outline (H1, H2, H3) before expanding into full text.
  4. The agent generates continuous academic prose, ensuring consistent use of formal terminology and objective tone.
  5. If information is insufficient, the skill provides professional templates and prompts the user for specific data to maintain factual accuracy.

Paper Assistant Setup

To deploy this skill within your environment using Openclaw Skills, use the following configuration:

# Install the core CLI if not already present
npm install -g @openclaw/cli

# Add the paper-assistant skill to your local agent
openclaw skill install paper-assistant

# Configure your academic preferences
openclaw configure paper-assistant --level doctoral

Paper Assistant Data Schema & Taxonomy

Paper Assistant organizes research data and generated content using a standardized taxonomy to ensure logical flow and easy integration into document editors.

Component Description Format
Research Metadata Defines research object, methodology type, and academic level Key-Value Pair
Structural Outline Hierarchical breakdown of chapters and sections Markdown (H1-H3)
Content Blocks Continuous, ready-to-use academic paragraphs Markdown
Review Framework Categorization of literature by debate points or research gaps Nested Lists
Defense Materials Summary of innovations, limitations, and presentation outlines Bulleted Lists

Paper Assistant Advanced Features

  • Multi-perspective topic optimization to help narrow down broad research areas into executable titles.
  • Context-aware academic polishing that preserves original research intent while upgrading linguistic precision.
  • Four-element abstract generation (Background, Method, Results, Conclusion) for high-impact summaries.
  • Automated extraction of research innovations and limitations for defense and submission preparation.
  • Version-controlled output offering "Academic," "Concise," or "Submission-ready" variations of the same content.

SKILL.md


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