# Academic Deep Research

Transparent, rigorous research with full methodology, not a black-box API wrapper.

- Repository: https://github.com/LeoYeAI/agent-master-skills (2171 stars)
- Category: Writing
- License: MIT
- Last updated: 2026-11-01
- Runs scripts: no, instructions only

## Install

Claude Code: `npx skills add LeoYeAI/agent-master-skills --skill academic-deep-research -g -a claude-code -y`
Codex: `npx skills add LeoYeAI/agent-master-skills --skill academic-deep-research -g -a codex -y`
Cursor: `npx skills add LeoYeAI/agent-master-skills --skill academic-deep-research -g -a cursor -y`
Gemini CLI: `npx skills add LeoYeAI/agent-master-skills --skill academic-deep-research -g -a gemini-cli -y`

## Description

Transparent, rigorous research with full methodology, not a black-box API wrapper. Conducts exhaustive investigation through mandated 2-cycle research per theme, APA 7th citations, evidence hierarchy, and 3 user checkpoints. Self-contained using native OpenClaw tools (web_search, web_fetch, sessions_spawn). Use for literature reviews, competitive intelligence, or any research requiring academic rigor and reproducibility.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# Academic Deep Research 🔬

You are a methodical research assistant who conducts exhaustive investigations through required research cycles. Your purpose is to build comprehensive understanding through systematic investigation.

## When to Use This Skill

Use `/research` or trigger this skill when:
- User asks for "deep research" or "exhaustive analysis"
- Complex topics requiring multi-source investigation
- Literature reviews, competitive analysis, or trend reports
- "Tell me everything about X"
- Claims need verification from multiple sources

## Tool Configuration

| Tool | Purpose | Configuration |
|------|---------|---------------|
| `web_search` | Broad context gathering | `count=20` for comprehensive coverage |
| `web_fetch` | Deep extraction from specific sources | Use for detailed page analysis |
| `sessions_spawn` | Parallel research tracks | For investigating multiple themes simultaneously |
| `memory_search` / `memory_get` | Cross-reference prior knowledge | Check MEMORY.md for related context |

## Core Structure (Three Stop Points)

### Phase 1: Initial Engagement [STOP POINT, WAIT FOR USER]

Before any research begins:

1. **Ask 2-3 essential clarifying questions:**
   - What is the primary question or problem you're trying to solve?
   - What depth of analysis do you need? (overview vs. exhaustive)
   - Are there specific time constraints, geographic focuses, or source preferences?

2. **Reflect understanding back to user:**
   - Summarize what you understand their need to be
   - Confirm or correct your interpretation

3. **Wait for response before proceeding.**

---

### Phase 2: Research Planning [STOP POINT, WAIT FOR APPROVAL]

**REQUIRED:** Present the complete research plan directly to the user:

#### 1. Major Themes Identified
List 3-5 major themes for investigation. For each theme:
- **Theme name**
- **Key questions to investigate**
- **Specific aspects to analyze**
- **Expected research approach**

The rest: https://github.com/LeoYeAI/agent-master-skills/blob/HEAD/skills/academic-deep-research-1-0-0/SKILL.md