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scientific-graphical-abstract-skill科学图形抽象能力

Agent Skill

scientific-graphical-abstract-skill 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

16,064

周安装

683

GitHub Stars

1

下载量

5,628
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:scientific-graphical-abstract-skill(科学图形抽象能力)
来源仓库:https://github.com/jackkuo666/scientific-graphical-abstract-skill
安装命令:
openclaw skills install scientific-graphical-abstract-skill
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install scientific-graphical-abstract-skill

简介

使用具有可定制图表、图表和数据驱动可视化的 AI 模型,为科学论文生成可编辑、出版质量的 SVG 图形摘要。

SKILL.md

Scientific Graphical Abstract Generator

AI-Powered Scientific Visualization Tool - Generate editable graphical abstracts for research papers

Description

Generate professional graphical abstracts for scientific papers using multiple AI models. This skill transforms research descriptions and data into publication-quality, editable SVG visualizations.

Features

  • Multiple AI Models: Support for Claude, GPT-4o, DeepSeek, and other multimodal models
  • Editable SVG Output: Generate vector graphics that can be edited in Inkscape, Illustrator, or any SVG editor
  • Multiple Chart Types: Bar charts, line charts, pie charts, scatter plots, flowcharts, diagrams
  • Data-Driven Visuals: Automatically create charts from CSV/JSON data
  • Customizable Styles: Adjust colors, fonts, layouts to match journal requirements
  • Publication Ready: High-quality output suitable for scientific journals

Usage

/graphical-abstract Generate a graphical abstract showing the research workflow for a CRISPR gene editing study
/graphical-abstract Create a bar chart comparing the performance of three different machine learning models from this data: [data]
/graphical-abstract Design a flowchart illustrating the mechanism of action of the proposed drug
/graphical-abstract Generate a line chart showing temperature changes over time from the following CSV data

Examples

Generate Research Workflow Diagram

/graphical-abstract Create a graphical abstract showing the workflow: Sample preparation → RNA extraction → Sequencing → Data analysis → Results visualization. Use a clean, professional style with blue color scheme.

Create Data Visualization

/graphical-abstract Generate a bar chart with the following data:
Model A: 85% accuracy
Model B: 92% accuracy
Model C: 78% accuracy

Title: Model Performance Comparison
Y-axis: Accuracy (%)
Color scheme: Professional blue gradient

Generate Mechanism Diagram

/graphical-abstract Design a schematic diagram showing how the proposed inhibitor binds to the active site of the enzyme, blocking substrate access. Include labels for key components.

Command Reference

generate

Generate a graphical abstract.

OptionDescription
--promptDescription of what to visualize
--dataData file (CSV/JSON) for charts
--typeChart type: bar, line, pie, scatter, flowchart, diagram
--modelAI model: claude, gpt4o, deepseek (default: claude)
--styleStyle: minimal, professional, colorful, journal
--outputOutput SVG file path
--widthCanvas width (default: 800)
--heightCanvas height (default: 600)

template

Use predefined templates for common visualizations.

OptionDescription
--typeTemplate type: workflow, mechanism, comparison, timeline
--promptSpecific requirements

Supported Models

Claude (Recommended)

  • Best for: Complex diagrams, scientific illustrations
  • Vision capabilities: Excellent
  • API: Anthropic Claude API

GPT-4o

  • Best for: Charts, data visualization
  • Vision capabilities: Very good
  • API: OpenAI API

DeepSeek

  • Best for: Technical diagrams, cost-effective
  • Vision capabilities: Good
  • API: DeepSeek API

Output Format

All outputs are in SVG format which offers:

  • Editable: Open in Inkscape, Adobe Illustrator, or any text editor
  • Scalable: Infinite resolution without quality loss
  • Web-ready: Can be embedded directly in websites
  • Publication quality: Meets most journal requirements

Example SVG structure:

<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 800 600">
  <!-- Editable elements with clear structure -->
  <g id="chart-area">...</g>
  <g id="labels">...</g>
  <g id="legend">...</g>
</svg>

Notes

  • For complex visualizations, provide detailed descriptions
  • Data files should be in CSV or JSON format
  • SVG files can be edited after generation
  • Different models may produce different styles
  • Journal-specific requirements can be specified in the prompt

Related Skills

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

75.01%
按下载量换算4,222

安全审计

VirusTotal

通过

ClawScan

可疑

Static analysis

未展示

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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