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Deep Read

Name: Deep Read
Author: zhubao315

作者 zhubao315 · GitHub ↗ · v1.0.0 · MIT-0

cross-platform ⚠ suspicious

131

总下载

当前安装

版本数

在 OpenClaw 中安装

/install deep-read-analysis

功能描述

基于研究方法深度分析书籍，提炼核心观点、金句，生成实际应用指导和关联常青笔记。

使用说明 (SKILL.md)

Deep Read\r

\r 显示名称: Deep Read \r 版本: 1.0.0 \r 描述: 基于研究驱动方法，对书籍进行深度分析，提炼核心观点、金句，并生成实际应用指导和关联常青笔记。 \r 作者: Zhu Bao\r \r

输入参数\r

book_title (string, 必填)：书名\r
book_file (file, 可选)：书籍文件（PDF/EPUB/TXT）\r
user_notes (list, 可选)：用户已录入的笔记，用于生成关联常青笔记\r \r

输出参数\r

author_info (string)：作者介绍（生平、教育、主要著作、影响等）\r
creation_context (string)：创作背景（时间、社会环境、动机、评论等）\r
book_outline (string)：章节结构、大纲及核心观点\r
main_content (string)：书籍主要内容解读与分析\r
core_insights (string)：书籍最重要思想和见解\r
key_quotes (list)：引人深思的金句及分析\r
application_examples (list)：生活、学习和工作中的应用指导\r
related_evergreen_notes (list)：基于用户笔记生成的常青笔记标题及链接\r \r

标签\r

#deep-reading #knowledge-management #research-driven #book-analysis #insights\r \r

使用示例\r

from deep_read_generator import deep_read_analysis\r
\r
result = deep_read_analysis(\r
    book_title="原则",\r
    user_notes=["已读章节摘要", "高亮笔记"]\r
)\r
\r
print(result['core_insights'])\r
print(result['application_examples'])\r
print(result['related_evergreen_notes'])\r

安全使用建议

This skill appears to do what it says (deep book analysis) and its code is a safe placeholder, but there are a few red flags to check before installing: - The project lists openai and obsidian-api in requirements but does not declare any environment variables (e.g., OPENAI_API_KEY) or explain how Obsidian integration is configured. Ask the author or documentation how API keys or Obsidian credentials are expected to be provided. - If you install dependencies, they will be fetched from PyPI; review those packages (especially obsidian-api) to ensure you trust them. - If you must provide an API key (OpenAI or similar) or Obsidian credentials, limit the key permissions and avoid sharing highly privileged credentials. - Prefer running this in a sandboxed environment and inspect/modify the code yourself to ensure it only calls the services you expect (or remove the unused dependencies if you won't use them). If the author can confirm how API keys and Obsidian integration should be provided (or remove those dependencies if unused), the inconsistencies would be resolved and the skill would be reasonable to use.

功能分析

Type: OpenClaw Skill Name: deep-read-analysis Version: 1.0.0 The skill bundle is a legitimate framework for book analysis and knowledge management. The Python implementation in `deep_read_generator.py` is currently a placeholder that returns static data, and the `requirements.txt` includes relevant libraries like `openai` and `obsidian-api` which align with the stated purpose of generating 'evergreen notes'. No malicious logic, data exfiltration, or prompt injection attempts were detected across the files.

能力评估

ℹ Purpose & Capability

Name/description match the code and SKILL.md: the skill analyzes books and emits insights/evergreen-note links. However, requirements.txt includes openai and obsidian-api even though the shipped code is a local placeholder and the skill does not declare or document required credentials or where Obsidian integration would connect. This is likely sloppy packaging rather than outright malicious, but it's an unexplained dependency.

✓ Instruction Scope

SKILL.md describes inputs (book_title, optional book_file, user_notes) and outputs and does not instruct reading unrelated files, environment variables, or external endpoints. The runtime instructions explicitly say OpenAI or other model calls are a placeholder and should be replaced in the hosting environment.

ℹ Install Mechanism

There is no install spec (instruction-only behavior) which is low-risk. But a requirements.txt lists third-party packages (openai, pandas, markdown, obsidian-api). Installing those packages would pull code from PyPI; obsidian-api and openai are notable because they may enable network calls. The repository does not provide an install script or pin trusted release sources.

⚠ Credentials

The code imports openai (and requirements list openai) but the skill does not declare any required environment variables (e.g., OPENAI_API_KEY). If the placeholder were replaced with actual API calls, an API key would be needed — this mismatch is unexplained. Similarly, obsidian-api suggests possible integration with a user's Obsidian vault or service, but no config variables or paths are declared. Requesting secrets or vault access without documenting why is a proportionality concern.

✓ Persistence & Privilege

Skill does not request always:true, requires no special config paths, and has no install script that modifies other skills or system-wide settings. It appears to be a normal, non-persistent skill.

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 deep-read-analysis
安装完成后，直接呼叫该 Skill 的名称或使用 /deep-read-analysis 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 of Deep Read. - Provides research-driven deep analysis of books, extracting core insights and key quotes. - Accepts book title, optional file, and user notes for personalized output. - Generates author info, creation context, book outline, content analysis, application guidance, and related evergreen notes. - Supports linking user notes to new evergreen notes for better knowledge management. - Tags: deep-reading, knowledge-management, research-driven, book-analysis, insights.

元数据

Slug deep-read-analysis

版本 1.0.0

许可证 MIT-0

累计安装 0

当前安装数 0

历史版本数 1

常见问题

Deep Read 是什么？

基于研究方法深度分析书籍，提炼核心观点、金句，生成实际应用指导和关联常青笔记。它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 131 次。

如何安装 Deep Read？

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

Deep Read 是免费的吗？

是的，Deep Read 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。

Deep Read 支持哪些平台？

Deep Read 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 Deep Read？

由 zhubao315（@zhubao315）开发并维护，当前版本 v1.0.0。