academic-deep-research

Conduct transparent academic research with documented multi-cycle methodology and APA citations.

1|Updated Feb 14, 2026
One-click install
npx skills add https://github.com/AmitabhainArunachala/clawd --skill academic-deep-research-amitabhainarunachala
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: academic-deep-research
Source: https://github.com/AmitabhainArunachala/clawd/tree/main/skills/academic-deep-research
Command: npx skills add https://github.com/AmitabhainArunachala/clawd --skill academic-deep-research-amitabhainarunachala

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill provides a transparent, rigorous, and self-contained research methodology, avoiding the "black-box" nature of API wrappers. It ensures every step is documented and reproducible, offering user control and academic standards.

Core Features & Use Cases

  • Full Methodology Visibility: Every step of the research process is documented.
  • No External Dependencies: Runs entirely on native OpenClaw tools.
  • User Control: Features three explicit checkpoints for user approval.
  • Academic Rigor: Adheres to APA citations, evidence hierarchy, and confidence levels.
  • Mandated Research Cycles: Conducts a minimum of two full research cycles per theme for thoroughness.
  • Use Case: Ideal for literature reviews requiring academic rigor, competitive intelligence with source verification, or complex topics needing multi-source synthesis.

Quick Start

Use /research to start a comprehensive analysis of your topic.

Frequently Asked Questions about academic-deep-research

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I conduct reproducible academic research without using opaque AI wrappers?▼

Reproducible academic research requires a multi-cycle methodology that documents every step and provides user checkpoints. This approach ensures full visibility into the process, adhering to APA citations and evidence hierarchy.

What is the best way to structure a literature review with strict evidence hierarchy and source verification?▼

A rigorous literature review uses transparent methodologies with minimum research cycles to synthesize complex topics. It enforces source verification and confidence levels, ensuring your academic analysis remains fully documented.

Can I perform competitive intelligence research with full visibility into the source verification process?▼

Competitive intelligence research can be conducted transparently using native tools without external dependencies. The process includes explicit user checkpoints, allowing you to verify sources and methodology throughout the analysis.

How to start a deep dive synthesis for a complex topic using a transparent research methodology?▼

Start a deep dive synthesis by triggering a comprehensive analysis command. The methodology mandates multiple research cycles per theme, requiring your approval at three distinct checkpoints to maintain academic rigor.

Does transparent academic research require external API dependencies to synthesize multiple sources?▼

Transparent academic research does not require external API dependencies. It operates entirely on native tools, avoiding black-box processes while maintaining strict adherence to academic standards like APA citations.

When should I not use an automated multi-cycle methodology for academic research?▼

Avoid multi-cycle research methodologies when your project lacks time for multiple synthesis cycles and user checkpoints. This rigorous approach mandates thoroughness and explicit approval phases, which may delay rapid preliminary investigations.