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Scientific Graphical Abstract Skill
作者
JackKuo666
· GitHub ↗
· v0.1.2
538
总下载
1
收藏
1
当前安装
3
版本数
在 OpenClaw 中安装
/install scientific-graphical-abstract-skill
功能描述
Generate editable, publication-quality SVG graphical abstracts for scientific papers using AI models with customizable charts, diagrams, and data-driven visu...
安全使用建议
Key points to consider before installing:
- Verify the source repository and author (README points to a personal GitHub). Only install from a repo/account you trust.
- The README suggests running a remote installer (curl https://astral.sh/uv/install.sh | sh). Avoid piping unknown scripts to sh; review the script first or use an alternative installation method.
- The code will read ANTHROPIC_API_KEY / OPENAI_API_KEY / DEEPSEEK_API_KEY from your environment if present. The skill metadata did not declare required env vars — do not supply API keys unless you trust the code and repository. If you must provide keys, create least-privilege credentials and monitor usage.
- The included Python script appears to depend on listed requirements; consider running it in an isolated virtual environment or sandbox before granting any credentials.
- There is a minor code quality issue (math is used in several methods but not imported in the visible snippet) — this suggests limited review/testing; review the full code for other bugs or hidden network calls.
- If you want to proceed, review the full repository contents locally (search for network calls, external endpoints, and code that reads arbitrary files outside the skill folder), or ask the publisher to add clear requires.env metadata and an official install spec.
功能分析
Type: OpenClaw Skill
Name: scientific-graphical-abstract-skill
Version: 0.1.2
The skill bundle is a legitimate tool for generating scientific graphical abstracts in SVG format. The core logic in `graphical_abstract_generator.py` uses standard Python libraries to construct SVG elements based on user prompts or data files. Although the script contains code to load API keys from environment variables, it does not utilize them or make any external network calls, and no evidence of malicious intent, data exfiltration, or prompt injection was found.
能力评估
Purpose & Capability
The name/description (generate editable SVG graphical abstracts) aligns with the included code and examples. However, the README and SKILL.md advertise integrations with Anthropic/ OpenAI/DeepSeek APIs while the skill metadata declares no required environment variables — that's a mild mismatch (API use is optional in code, but metadata doesn't document these optional creds).
Instruction Scope
SKILL.md and README instruct the agent/user to load local CSV/JSON files and optionally use AI model APIs. That scope is appropriate for the feature set, but the runtime instructions assume availability of API keys and local files while metadata omits those env declarations. The README also suggests running external install steps and placing files under ~/.claude/skills, which will write to user disk; the instructions grant broad discretion to call external APIs if keys are provided.
Install Mechanism
The registry lists no install spec, but README suggests installation from a personal GitHub repo and provides a remote install pipeline: an npx clone URL and a curl | sh command to install 'uv' (https://astral.sh/uv/install.sh). Remote install scripts and cloning unverified repos increase risk; the skill lacks an official, vetted install spec in the registry.
Credentials
The code (Config._load_api_keys) reads ANTHROPIC_API_KEY, OPENAI_API_KEY, and DEEPSEEK_API_KEY from the environment and README documents these optional vars, but the skill metadata declares no required env vars. Requesting API keys for multiple providers is understandable for multimodel support, but the metadata omission is an inconsistency and increases the chance users provide credentials without clear justification. Provide keys only if you trust the code and owner.
Persistence & Privilege
The skill does not request always:true, does not declare system-wide config paths, and README describes installing into the user's skills directory (~/.claude/skills). Nothing in the package requests elevated or persistent privileges beyond normal installation.
如何使用
- 确保已安装 OpenClaw（本地或 Docker 部署）
- 在对话框中输入安装命令：
/install scientific-graphical-abstract-skill - 安装完成后，直接呼叫该 Skill 的名称或使用
/scientific-graphical-abstract-skill触发 - 根据 Skill 的参数说明提供必要输入，即可获得结构化输出
版本历史
v0.1.2
Version 0.1.2 of Scientific Graphical Abstract Generator
- No changes detected in this release; documentation remains unchanged.
- All features, usage examples, and supported models are consistent with the previous version.
v0.1.1
Version 0.1.1
- No file changes detected in this release.
- Documentation, features, usage, and examples remain unchanged.
- No new features, bug fixes, or enhancements introduced.
v0.1.0
Scientific Graphical Abstract Generator v0.1.0 — Initial Release
- Generate professional, editable SVG graphical abstracts for scientific papers using multiple AI models (Claude, GPT-4o, DeepSeek).
- Support for various visualization types: bar charts, line charts, pie charts, scatter plots, flowcharts, and schematic diagrams.
- Data-driven visuals: create charts directly from CSV or JSON data.
- Customizable output: adjust colors, fonts, layouts, and styles to meet publication standards.
- Command and template system for flexible visualization generation.
- All outputs are high-quality, publication-ready SVG files, fully editable in vector graphics editors.
元数据
常见问题
Scientific Graphical Abstract Skill 是什么？
Generate editable, publication-quality SVG graphical abstracts for scientific papers using AI models with customizable charts, diagrams, and data-driven visu... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 538 次。
如何安装 Scientific Graphical Abstract Skill？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install scientific-graphical-abstract-skill」即可一键安装，无需额外配置。
Scientific Graphical Abstract Skill 是免费的吗？
是的，Scientific Graphical Abstract Skill 完全免费（开源免费），可自由下载、安装和使用。
Scientific Graphical Abstract Skill 支持哪些平台？
Scientific Graphical Abstract Skill 跨平台运行，可在任意部署了 OpenClaw / Claude Code 的环境中使用（cross-platform）。
谁开发了 Scientific Graphical Abstract Skill？
由 JackKuo666（@jackkuo666）开发并维护，当前版本 v0.1.2。
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