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Deep Article Analysis

作者 OpenLark · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ 安全检测通过
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在 OpenClaw 中安装
/install deep-article-analysis
功能描述
Conduct in-depth analysis and interpretation of articles, extracting core viewpoints, key data, and deep insights.
使用说明 (SKILL.md)

Deep Article Analysis

Overview

Provides systematic article analysis methods and thinking tools to help extract core viewpoints, key data, and deep insights from complex articles. Comprehensively applies 10+ thinking models: SCQA Framework, 5W2H Analysis, First Principles, Six Thinking Hats, Critical Thinking, Systems Thinking, Reverse Thinking, Mental Models, Comparison Matrix, Inversion Thinking, and more. Suitable for deeply understanding complex articles, analyzing argumentative logic, and extracting actionable insights from reading materials.

Use Cases

Article analysis, report interpretation, argument evaluation, deep reading, insight extraction.

Thinking Model Overview

The skill is accompanied by reference documents for 10+ thinking models:

Model Purpose When to Use
SCQA Framework Grasp the logical thread of the article When needing to clarify article structure
5W2H Analysis Comprehensive information scanning When systematically gathering information
First Principles Trace back to the source When needing to understand the essence
Six Thinking Hats All-around evaluation When examining from multiple perspectives
Critical Thinking Argument assessment When evaluating reliability
Systems Thinking Complex system analysis When analyzing interrelated factors
Reverse Thinking Identify weaknesses When questioning or refining arguments
Mental Models Framework examination When cognitive framework analysis is needed
Comparison Matrix Option comparison When comparative analysis is needed
Inversion Thinking Risk prevention When preventing failure

Full index: references/index.md

Core Workflow

1. Quick Scan (5W2H)

First, comprehensively scan the basic information of the article using 5W2H:

  • What: Core topic / event of the article
  • Why: Causes and background
  • Who: Individuals and audience involved
  • When: Timeline
  • Where: Location / platform / scenario
  • How: Methods / mechanisms / processes
  • How much: Data / degree / scale

2. Structure Extraction (SCQA)

Grasp the logic of the article using the SCQA framework:

  • Situation: Background context
  • Complication: Core conflict / problem
  • Question: Key question
  • Answer: Author's viewpoint / solution

3. In-Depth Analysis (Select appropriate models)

Argument Evaluation → Critical Thinking

  • Is the evidence sufficient?
  • Is the logic valid?
  • Are there any logical fallacies?

Essential Inquiry → First Principles

  • What is the root cause?
  • Are the underlying assumptions reliable?
  • Is there a simpler explanation?

Comprehensive Examination → Six Thinking Hats

  • What are the facts? (White Hat)
  • What are the intuitive feelings? (Red Hat)
  • Where are the risks? (Black Hat)
  • What are the value opportunities? (Yellow Hat)
  • What are the innovative possibilities? (Green Hat)

Systemic Interconnection → Systems Thinking

  • Elements and relationships?
  • Feedback loops?
  • Time delays?

Risk Prevention → Inversion Thinking

  • How can we ensure failure?
  • What is the greatest risk?
  • How can we avoid it?

4. Insight Extraction

Extract from the analysis:

  • Core Viewpoint: Summarize the author's claim in one sentence
  • Key Data: Important figures and facts
  • Deep Insights: Valuable insights and inspirations
  • Actionable Takeaways: Advice that can guide action
  • Key Questions: Issues worth further consideration

Output Format

The analysis report is recommended to include:

## Core Viewpoint
[One-sentence summary]

## Key Data
- [Data point 1]
- [Data point 2]

## Deep Insights
### Insight 1
[Specific analysis]

### Insight 2
[Specific analysis]

## Thinking Models Applied
- [List of models used]
- [Key findings from each model]

## Questions for Further Exploration
[Issues worth further discussion]

Resources

references/

Directory of thinking model reference documents, containing detailed guides for 10 thinking models:

  • scqa.md - SCQA Framework
  • 5w2h.md - 5W2H Analysis
  • first-principles.md - First Principles
  • six-thinking-hats.md - Six Thinking Hats
  • critical-thinking.md - Critical Thinking
  • systems-thinking.md - Systems Thinking
  • reverse-thinking.md - Reverse Thinking
  • mental-models.md - Mental Models
  • comparison-matrix.md - Comparison Matrix
  • inversion-thinking.md - Inversion Thinking
  • index.md - Navigation Index

Selectively load the corresponding reference documents based on analysis needs.

安全使用建议
This skill appears coherent and low-risk: it only contains analysis instructions and local reference documents. Before installing, note that (1) the quality of outputs depends on the model and provided article text, (2) do not feed highly sensitive PII or secrets into the skill for analysis, and (3) you should still review any generated analysis for factual accuracy and bias. If you need the skill to access external sources or connectors later, expect additional review because that would increase risk.
功能分析
Type: OpenClaw Skill Name: deep-article-analysis Version: 1.0.0 The 'deep-article-analysis' skill bundle is a purely instructional set of Markdown files designed to guide an AI agent through structured article analysis using various cognitive frameworks (e.g., SCQA, 5W2H, First Principles). It contains no executable code, no network requests, no data exfiltration logic, and no malicious prompt injection attempts. The files (SKILL.md and the references/ directory) serve as a knowledge base for the agent to improve its analytical output.
能力标签
cryptocan-make-purchases
能力评估
Purpose & Capability
Name/description describe deep article analysis and the skill provides local reference documents and a clear workflow for exactly that purpose. No unrelated binaries, env vars, or external services are requested.
Instruction Scope
SKILL.md contains only analysis workflows and guidance to use the included reference docs. It does not instruct reading arbitrary host files, accessing environment variables, or contacting external endpoints.
Install Mechanism
There is no install spec and no code files — this is instruction-only, so nothing is downloaded or written to disk during install.
Credentials
No environment variables, credentials, or config paths are requested. The declared surface area is minimal and appropriate for an analysis/knowledge skill.
Persistence & Privilege
Skill does not request always-on status and uses normal model invocation defaults. It does not modify other skills or system settings and requires no elevated persistence.
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 deep-article-analysis
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /deep-article-analysis 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
v1.0.0
Initial release of deep-article-analysis. - Provides structured methods for in-depth article analysis and insight extraction. - Integrates 10+ thinking models, including SCQA, 5W2H, First Principles, Six Thinking Hats, and more. - Offers a step-by-step workflow: quick scan, structure extraction, in-depth analysis, and insight extraction. - Includes recommended output formats for consistent analysis reports. - Reference documents for each thinking model are organized for easy access.
元数据
Slug deep-article-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 Article Analysis 是什么?

Conduct in-depth analysis and interpretation of articles, extracting core viewpoints, key data, and deep insights. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 30 次。

如何安装 Deep Article Analysis?

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

Deep Article Analysis 是免费的吗?

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

Deep Article Analysis 支持哪些平台?

Deep Article Analysis 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 Article Analysis?

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

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