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OpenPaperGraph
作者
JiahaoWuGit
· GitHub ↗
· v1.0.0
· MIT-0
144
总下载
0
收藏
0
当前安装
1
版本数
在 OpenClaw 中安装
/install openpapergraph
功能描述
Academic literature discovery and citation network analysis. Multi-source search across arXiv, DBLP, Semantic Scholar, and Google Scholar. Build citation net...
安全使用建议
OpenPaperGraph appears internally consistent with its stated purpose, but before installing:
- Inspect install.sh and prefer running dependency installation inside a virtualenv (pip install into a venv) to avoid changing system Python packages.
- The installer may create a symlink under ~/.claude/commands/opg/SKILL.md for global availability; if you don't want global changes, use the project install mode or skip the installer and call the CLI directly.
- Optional API keys (S2_API_KEY, OPENAI_API_KEY, etc.) are documented and not required; only provide keys you trust and understand their scope.
- Expect network activity (queries to arXiv, Semantic Scholar, Google Scholar via scholarly, Unpaywall, CrossRef, OpenAlex) and local file writes (graph JSON, exported HTML/BibTeX). Don't feed private PDFs or secrets you don't want stored in graph JSON files.
- The project uses the scholarly package to access Google Scholar (scraping-like access) which can be rate-limited or fragile; monitor usage accordingly.
If you want greater assurance, run the installer in --check mode, review the CLI source (openpapergraph_cli.py) and services/*.py modules, and run the CLI locally in a controlled environment before enabling global skill registration.
功能分析
Type: OpenClaw Skill
Name: openpapergraph
Version: 1.0.0
OpenPaperGraph is a comprehensive academic research tool designed for literature discovery, citation network analysis, and AI-powered summarization. It integrates with multiple legitimate academic data sources (arXiv, Semantic Scholar, CrossRef, etc.) and provides a local HTTP server for interactive graph management. All high-risk behaviors, such as network requests, PDF downloads to a local cache, and LLM integration, are transparently documented and directly support the tool's stated functionality. No evidence of malicious intent, credential theft, or unauthorized data exfiltration was found across the codebase or the SKILL.md instructions.
能力评估
Purpose & Capability
The name/description (search, PDF parsing, citation graphs, LLM summaries) match the provided CLI and service modules (arXiv, DBLP, Semantic Scholar, Google Scholar access via scholarly, PDF parsing, graph building, Zotero import). Optional env vars documented in SKILL.md (S2_API_KEY, various LLM keys) correspond to documented features and are optional.
Instruction Scope
SKILL.md instructs the agent to run the included CLI from SKILL_DIR, install a small set of Python packages, and read/write graph JSON and uploaded PDFs. The instructions do not ask the agent to read arbitrary system files or exfiltrate secrets; parsing PDFs, writing JSON, and starting a local server are within the stated scope.
Install Mechanism
There is no platform-level install spec, but an install.sh (one-line installer) is included. install.sh symlinks SKILL.md into ~/.claude (global) or project .claude folder and runs pip install httpx pymupdf scholarly. This is coherent with enabling the skill but will modify the user's Python environment (global pip) and create symlinks in the home directory—recommend running in a virtualenv or inspecting the script first.
Credentials
Registry metadata lists no required env vars; SKILL.md documents optional env vars (S2_API_KEY and many LLM keys) that are reasonable for optional features (avoid rate limits, enable LLM summaries). The code and installer check these variables but do not require them. No unrelated credentials are requested.
Persistence & Privilege
The skill writes and updates graph JSON files and the serve mode persists edits to disk. The installer creates symlinks under ~/.claude when installing globally. always:false and normal autonomous invocation are used. These behaviors are expected for a CLI/skill but involve persistent local storage and minor changes to the user's Claude/OpenClaw configuration.
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 openpapergraph - 安装完成后，直接呼叫该 Skill 的名称或使用
/openpapergraph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
v1.0.0
Initial release with right name
元数据
常见问题
OpenPaperGraph 是什么？
Academic literature discovery and citation network analysis. Multi-source search across arXiv, DBLP, Semantic Scholar, and Google Scholar. Build citation net... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 144 次。
如何安装 OpenPaperGraph？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install openpapergraph」即可一键安装，无需额外配置。
OpenPaperGraph 是免费的吗？
是的，OpenPaperGraph 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。
OpenPaperGraph 支持哪些平台？
OpenPaperGraph 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 OpenPaperGraph？
由 JiahaoWuGit（@jiahaowugit）开发并维护，当前版本 v1.0.0。
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