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Literature Report

作者 ZJUZhiyuCai · GitHub ↗ · v1.0.4
cross-platform ⚠ suspicious
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在 OpenClaw 中安装
/install literature-report
功能描述
自动科研文献汇报系统。每天自动检索顶级期刊最新论文，AI辅助筛选，生成双语摘要，推送到飞书。使用方法：1. 用户说"设置文献汇报"或"每天推送论文"时激活；2. 用户要求自定义研究主题时激活；3. 用户要求文献检索和推送时激活。
使用说明 (SKILL.md)

自动科研文献汇报系统

自动化的科研文献检索与汇报系统，让科研人员轻松追踪最新研究动态。

🔑 所需凭据

必须凭据

LLM API Key（必需）

可选凭据

飞书用户ID（可选，用于推送）

  • 获取方式： 在飞书中打开个人资料，查看"用户ID"或"open_id"
  • 用途： 推送每日文献报告
  • 安全提示： 用户ID不会产生费用，但请勿泄露

🚀 快速开始

1. 环境要求

  • Python 3.8+
  • LLM API Key（OpenAI / Claude / 硅基流动等）
  • 飞书账号（可选，用于推送）

2. 安装

# 安装
bash install.sh

# 验证安装
python3 scripts/verify_install.py

3. 配置

  1. 复制配置文件模板：
cp config.yaml.example config.yaml
  1. 编辑 config.yaml，填入你的配置：
# LLM API配置（必须）
api:
  api_key: "YOUR_API_KEY"        # 你的LLM API Key
  base_url: "https://api.siliconflow.cn/v1"  # API基础URL
  model: "deepseek-ai/DeepSeek-V3.2"  # 模型名称

# 推送配置（可选）
feishu:
  enabled: true
  target: "YOUR_USER_ID"          # 你的飞书用户ID

# 研究主题
research:
  topic: "你的研究领域"
  max_papers: 5                    # 每天推送数量

4. 测试

# 验证配置
python3 scripts/validate_config.py

# 测试运行
python3 scripts/fetch_papers.py
python3 scripts/generate_summary.py

5. 运行

# 手动执行
python3 scripts/fetch_papers.py      # 抓取论文
python3 scripts/generate_summary.py  # 生成摘要
python3 scripts/send_to_feishu.py    # 推送

# 设置定时任务（每天早上9点）
openclaw cron add literature-report --time '0 9 * * *'

🔧 安装验证

运行验证脚本检查环境：

python3 scripts/verify_install.py

检查项目：

  • ✅ Python版本
  • ✅ 依赖库安装
  • ✅ 配置文件存在
  • ✅ API Key格式
  • ✅ 网络连接

❓ 故障排除

问题1: API Key无效

错误信息： API Key无效或账户余额不足

解决方案：

  1. 检查API Key是否正确复制
  2. 确认账户有余额
  3. 确认API Key有权限访问指定模型
  4. 确认base_url指向正确的API端点

问题2: 找不到论文

错误信息： 未找到符合条件的论文

解决方案：

  1. 放宽关键词设置
  2. 添加更多期刊
  3. 调整研究主题描述
  4. 检查网络连接

问题3: 推送失败

错误信息： 飞书推送失败

解决方案：

  1. 确认飞书用户ID正确
  2. 确认网络连接正常
  3. 检查飞书服务状态
  4. 注意：当前飞书推送为占位符实现，仅打印消息

📚 期刊覆盖

RSS期刊（10个）

Nature, Nature Biotechnology, Nature Materials, Nature Communications, Nature Nanotechnology, Nature Sustainability, Nature Reviews Drug Discovery, Nature Reviews Materials, Advanced Materials, Advanced Science

PubMed API期刊（16个）

Nature Biomedical Engineering, Nature Electronics, Nature Machine Intelligence, Nature Sensors, Nature Reviews Bioengineering, Science, Science Translational Medicine, Science Advances, Biomaterials, Journal of Controlled Release, ACS Nano, Biosensors and Bioelectronics, Nano Letters, Advanced Healthcare Materials

⚙️ 自定义配置

修改研究主题

research:
  topic: "你的研究领域"
  description: |
    研究方向包括：
    - 方向1
    - 方向2

添加自定义期刊

journals:
  custom_journals:
    - name: "Your Journal"
      type: "pubmed"
      query: '"Journal Name"[Journal]'

🔒 安全提示

  1. 不要将config.yaml提交到公开仓库
  2. API Key请妥善保管
  3. 用户ID不要泄露
  4. 建议使用环境变量存储敏感信息
  5. 确保base_url指向可信的API提供商
  6. 论文标题和摘要将发送到配置的LLM服务

📞 支持

如有问题或建议，请提交Issue或Pull Request。

📜 许可证

MIT License

版本: 1.0.4
更新时间: 2026-03-02

安全使用建议
Before installing: (1) Be aware this will send paper titles and abstracts to whatever LLM endpoint you configure — only use a trusted provider and review their data-retention/privacy terms. (2) The skill expects an LLM API Key in config.yaml (api.api_key) even though the registry metadata omitted that — do not paste keys into public repos. (3) Review and, if needed, change base_url to a known/approved endpoint; malicious endpoints could capture your data. (4) Feishu push is implemented as a placeholder that prints the message — if you expect real push behavior, review and implement the Feishu API call and handle tokens securely. (5) Run the code in an isolated environment (or sandbox/VM) and inspect config.yaml and scripts yourself; consider creating a provider account with limited quota or using a provider that supports private/deletion guarantees. (6) If you need the registry to be accurate, ask the publisher to update the metadata to declare the required credential (LLM API Key).
功能分析
Type: OpenClaw Skill Name: literature-report Version: 1.0.4 The OpenClaw AgentSkill 'literature-report' is designed for automated research paper retrieval and summarization. The `install.sh` script performs standard Python dependency installation and directory creation. Python scripts interact with legitimate external APIs (LLM providers, RSS feeds, PubMed) using user-configured API keys, with explicit warnings in `SKILL.md` and `GUIDE.md` not to expose sensitive credentials. The `send_to_feishu.py` script is a placeholder and does not currently send data externally. There is no evidence of intentional data exfiltration, unauthorized remote execution, persistence mechanisms, or prompt injection attempts against the OpenClaw agent itself. The code and documentation align with the stated purpose and lack high-risk behaviors indicative of malice or significant vulnerabilities.
能力评估
ℹ Purpose & Capability
The name/description (daily literature retrieval, AI filtering, bilingual summaries, Feishu push) align with the included scripts: RSS + PubMed fetching, AI filtering, summary generation, and Feishu push. However the published registry metadata lists no required credentials/primary credential, while SKILL.md/package.json and the code clearly require an LLM API key (stored in config.yaml). This metadata mismatch is an incoherence that could mislead users or automation.
⚠ Instruction Scope
Runtime instructions and scripts perform network operations: pulling RSS feeds, querying NCBI PubMed APIs, and sending paper titles/abstracts to the configured LLM endpoint (base_url + /chat/completions). The SKILL.md warns about this, but the code will transmit paper content to whichever base_url is configured. send_to_feishu is a placeholder that only prints by default (no real Feishu API call), but the scripts read/write config.yaml and data files. There is no instruction or code that reads unrelated local secrets or system config beyond the project's config.yaml, but sending abstracts to an external LLM is a potential data-exfiltration/privacy risk if the endpoint is untrusted.
✓ Install Mechanism
There is no platform install spec; installation is via the included install.sh which runs pip installs for common PyPI packages (feedparser, requests, pyyaml, markdown, weasyprint). No downloads from obscure URLs or archive extraction are present. install.sh also copies config template and runs local verify_install.py. This is standard but will install packages from PyPI.
⚠ Credentials
The code and SKILL.md require an LLM API key (api.api_key in config.yaml) and optionally a Feishu user ID. The registry metadata, however, declares 'Required env vars: none' and 'Primary credential: none', which contradicts the declared MUST credential in SKILL.md/package.json and the code. Aside from the LLM API key and optional Feishu ID, no other credentials are requested. Requiring an LLM API key is proportionate to the described functionality, but the metadata mismatch is misleading and should be corrected before installation.
✓ Persistence & Privilege
The skill does not request 'always:true' and does not modify other skills or system-wide configs. It creates/uses local project files (config.yaml, data/, logs/) which is expected. It will persist data (fetched papers and generated summaries) locally in the repository's data directory.
如何使用
  1. 确保已安装 OpenClaw（本地或 Docker 部署）
  2. 在对话框中输入安装命令：/install literature-report
  3. 安装完成后，直接呼叫该 Skill 的名称或使用 /literature-report 触发
  4. 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
v1.0.4
literature-report 1.0.4 - 增加 base_url 及 model 配置说明，示例默认 DeepSeek/硅基流动 API。 - 安全提示和凭据说明中，强调 base_url 安全性与LLM数据会被发送到API供应商。 - 故障排除部分增加 base_url 检查和飞书推送为“占位符实现”说明。 - 精简描述，去除对钉钉/微信推送相关表述。
v1.0.3
- 更新依赖和脚本，优化安装流程（install.sh、package.json 有更新） - 改进 AI 文献筛选脚本（scripts/ai_filter.py 有更新） - 其他小幅优化和维护，提升稳定性
v1.0.2
Version 1.0.2 - 增加 scripts/validate_config.py 和 scripts/verify_install.py 安装与配置校验脚本 - 文档（SKILL.md）详细加入凭据说明和常见故障排除指导 - 提升快速安装、配置、验证流程指引 - 强化安全提示，建议使用环境变量保存敏感信息
v1.0.1
- Added detailed usage guide (GUIDE.md) and configuration template (config.yaml.example) - Introduced install.sh and organized all core scripts under scripts/ directory - Updated and streamlined documentation for installation and configuration - Improved file structure section and removed outdated paths - Clarified quick start and setup instructions for easier onboarding
v1.0.0
- 首次发布：自动科研文献汇报系统 1.0.0 - 支持每天自动检索26个顶级期刊最新论文，AI筛选生成中英文摘要 - 推送平台覆盖飞书、钉钉、微信 - 支持自定义研究主题、期刊及关键词 - 提供简单配置与一键定时执行 - 包含隐私与API Key安全提示
元数据
Slug literature-report
版本 1.0.4
许可证 —
累计安装 1
当前安装数 1
历史版本数 5
常见问题

Literature Report 是什么？

自动科研文献汇报系统。每天自动检索顶级期刊最新论文，AI辅助筛选，生成双语摘要，推送到飞书。使用方法：1. 用户说"设置文献汇报"或"每天推送论文"时激活；2. 用户要求自定义研究主题时激活；3. 用户要求文献检索和推送时激活。 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 512 次。

如何安装 Literature Report？

在 OpenClaw 或 Claude Code 对话框中运行命令「/install literature-report」即可一键安装，无需额外配置。

Literature Report 是免费的吗？

是的，Literature Report 完全免费（开源免费），可自由下载、安装和使用。

Literature Report 支持哪些平台？

Literature Report 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 Literature Report？

由 ZJUZhiyuCai（@zjuzhiyucai）开发并维护，当前版本 v1.0.4。

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