kesslerio/academic-deep-research-clawhub-skill
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Moltbot skill for exhaustive research with academic rigor
개요
Most "deep research" tools are wrappers around external APIs. You send a query, get a report, and have no idea what happened in between. - ✅ — Every step documented, reproducible - ✅ — Runs entirely on OpenClaw native tools - ✅ — 3 explicit checkpoints for approval - ✅ — APA citations, evidence hierarchy, confidence levels - ✅ — No API keys, no cloud services Every theme gets : 1. Broad landscape search → Analysis → Gap identification 2. Targeted deep dive → Challenge assumptions → Synthesis - - — not hidden - [HIGH], [MEDIUM], [LOW], [SPECULATIVE] - Meta-analyses > RCTs > Observational > Expert opinion - 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 Three mandatory stop points: 1. — Clarify scope before research 2. — Approve themes and approach 3.
README
원문 README의 일부입니다. 원문 보기.
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.
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설치
npx skillfish add kesslerio/academic-deep-research-clawhub-skill