academic-deep-research
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.
Academic Deep Research 🔬
Transparent, rigorous, self-contained research — not a black-box API wrapper.
Why This Skill Exists
Most "deep research" tools are wrappers around external APIs. You send a query, get a report, and have no idea what happened in between.
This skill is different:
- ✅ Full methodology visible — Every step documented, reproducible
- ✅ No external dependencies — Runs entirely on OpenClaw native tools
- ✅ User control — 3 explicit checkpoints for approval
- ✅ Academic rigor — APA citations, evidence hierarchy, confidence levels
- ✅ Works offline — No API keys, no cloud services
Comparison with Cloud-Based Research Tools
| Feature | This Skill | Cloud API Wrappers |
|---|---|---|
| Methodology | Fully documented | Black box |
| Dependencies | None | External API + key |
| Offline | ✅ Yes | ❌ No |
| User Checkpoints | 3 approval points | Usually none |
| Citation Format | APA 7th edition | Varies/unspecified |
| Evidence Hierarchy | Explicit (meta-analyses → opinion) | Unspecified |
| Output Control | Strict prose, no bullet points | Varies |
| Reproducibility | ✅ Same inputs = same process | ❓ Unknown |
Core Features
Mandated Research Cycles
Every theme gets minimum 2 full research cycles:
- Broad landscape search → Analysis → Gap identification
- Targeted deep dive → Challenge assumptions → Synthesis
No shortcuts. No single-pass summaries.
Evidence Standards
- Every conclusion cites multiple sources
- Contradictions must be addressed — not hidden
- Confidence annotations: [HIGH], [MEDIUM], [LOW], [SPECULATIVE]
- Evidence hierarchy: Meta-analyses > RCTs > Observational > Expert opinion
Academic Output
- Flowing narrative prose (no bullet point dumps)
- APA 7th edition citations (1-2 per paragraph)
- Proper paragraph structure: claim → evidence → analysis → transition
- Executive summary, methodology, findings, limitations, references
User Control
Three mandatory stop points:
- Initial Engagement — Clarify scope before research
- Research Planning — Approve themes and approach
- Final Report — Review completed analysis
Quick Start
/research "Comprehensive analysis of [your topic]"
Or just ask for "deep research on..." or "exhaustive analysis of..."
Research Protocol
Phase 1: Clarification
Agent asks 2-3 essential questions, confirms understanding, waits for you.
Phase 2: Planning
Agent presents:
- Major themes identified (3-5)
- Research execution plan (table format)
- Expected deliverables
You approve before execution begins.
Phase 3: Execution (Auto)
For each theme, two full cycles:
web_search(count=20) for landscape- Analysis and gap identification
web_fetchon primary sources- Synthesis and assumption challenging
- Repeat for depth
Required: Explicit analysis between every tool call showing evolution of understanding.
Phase 4: Report
Academic narrative with:
- Executive Summary
- Knowledge Development
- Comprehensive Analysis
- Practical Implications
- APA References
File Structure
deep-research/
├── SKILL.md # Full methodology (500+ lines)
├── README.md # This file
├── quickref.md # One-page cheat sheet
├── example.md # Complete workflow example
└── LICENSE # Apache 2.0
When to Use This
- Literature reviews requiring academic rigor
- Competitive intelligence with source verification
- Complex topics needing multi-source synthesis
- Any research where you need to show your work
- When you don't trust black-box AI summaries
License
Apache 2.0 — See LICENSE
Built for researchers who care about methodology, not just outputs.