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Deep Article Analysis

by OpenLark · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ Security Clean
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Install in OpenClaw
/install deep-article-analysis
Description
Conduct in-depth analysis and interpretation of articles, extracting core viewpoints, key data, and deep insights.
README (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.

Usage Guidance
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.
Capability Analysis
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.
Capability Tags
cryptocan-make-purchases
Capability Assessment
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.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install deep-article-analysis
  3. After installation, invoke the skill by name or use /deep-article-analysis
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
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.
Metadata
Slug deep-article-analysis
Version 1.0.0
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is Deep Article Analysis?

Conduct in-depth analysis and interpretation of articles, extracting core viewpoints, key data, and deep insights. It is an AI Agent Skill for Claude Code / OpenClaw, with 30 downloads so far.

How do I install Deep Article Analysis?

Run "/install deep-article-analysis" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Deep Article Analysis free?

Yes, Deep Article Analysis is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Deep Article Analysis support?

Deep Article Analysis is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Deep Article Analysis?

It is built and maintained by OpenLark (@openlark); the current version is v1.0.0.

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