Help
Skill brycewang-stanford/Auto-Empirical-Research-Skills/skills/25-HosungYou-Diverga/skills/help
Diverga help guide - displays all 24 agents across 9 categories, commands, and usage examples. Triggers: help, guide, how to use, 도움말From its SKILL.md
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SKILL.md
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/diverga:help
Version: 2.0.0
Trigger: /diverga:help
Description
Displays comprehensive guide for Diverga, including all 24 agents across 9 categories, commands, and usage examples.
Output
When user invokes /diverga:help, display:
╔══════════════════════════════════════════════════════════════════╗
║ Diverga v11.0 Help ║
║ AI Research Assistant - 24 Agents, 9 Categories ║
╚══════════════════════════════════════════════════════════════════╝
┌─────────────────────────────────────────────────────────────────┐
│ QUICK START │
├─────────────────────────────────────────────────────────────────┤
│ Just describe your research: │
│ "I want to conduct a meta-analysis on AI in education" │
│ "Help me design a qualitative study" │
│ "메타분석 연구를 시작하고 싶어" │
│ │
│ Diverga auto-detects context and activates relevant agents. │
└─────────────────────────────────────────────────────────────────┘
┌─────────────────────────────────────────────────────────────────┐
│ COMMANDS │
├─────────────────────────────────────────────────────────────────┤
│ /diverga:setup Initial configuration wizard │
│ /diverga:doctor System diagnostics & health check │
│ /diverga:help This help guide │
│ /diverga:meta-analysis Meta-analysis workflow (C5) │
│ /diverga:humanize Humanization pipeline (G5+G6+F5) │
└─────────────────────────────────────────────────────────────────┘
┌─────────────────────────────────────────────────────────────────┐
│ CATEGORY A: FOUNDATION (3 agents) │
├─────────────────────────────────────────────────────────────────┤
│ diverga:a1 ResearchQuestionRefiner Refine research Qs │
│ diverga:a2 TheoreticalFrameworkArchitect Frameworks + Critique │
│ + Visualization (absorbed A3, A6) │
│ diverga:a5 ParadigmWorldviewAdvisor Ontology + Ethics │
└─────────────────────────────────────────────────────────────────┘
┌─────────────────────────────────────────────────────────────────┐
│ CATEGORY B: EVIDENCE (2 agents) │
├─────────────────────────────────────────────────────────────────┤
│ diverga:b1 LiteratureReviewStrategist Literature search │
│ diverga:b2 EvidenceQualityAppraiser RoB, GRADE appraisal │
└─────────────────────────────────────────────────────────────────┘
┌─────────────────────────────────────────────────────────────────┐
│ CATEGORY C: DESIGN & META-ANALYSIS (4 agents) │
├─────────────────────────────────────────────────────────────────┤
│ diverga:c1 QuantitativeDesignConsultant Quant design │
│ + Materials + Sampling (absorbed C4, D1) │
│ diverga:c2 QualitativeDesignConsultant Qual design │
│ + Ethnography + Action Research (absorbed H1, H2) │
│ diverga:c3 MixedMethodsDesignConsultant Mixed methods │
│ diverga:c5 MetaAnalysisMaster ⭐ Meta-analysis lead │
│ + Data/Effect/Error/Sensitivity (absorbed C6,C7,B3,E5)│
└─────────────────────────────────────────────────────────────────┘
┌─────────────────────────────────────────────────────────────────┐
│ CATEGORY D: DATA COLLECTION (2 agents) │
├─────────────────────────────────────────────────────────────────┤
│ diverga:d2 DataCollectionSpecialist Interview + Observation │
│ (absorbed D3, renamed) │
│ diverga:d4 MeasurementInstrumentDeveloper Instrument dev │
└─────────────────────────────────────────────────────────────────┘
┌─────────────────────────────────────────────────────────────────┐
│ CATEGORY E: ANALYSIS (3 agents) │
├─────────────────────────────────────────────────────────────────┤
│ diverga:e1 QuantitativeAnalysisGuide Statistical guidance │
│ + Code Gen + Sensitivity (absorbed E4, E5) │
│ diverga:e2 QualitativeCodingSpecialist Qualitative coding │
│ diverga:e3 MixedMethodsIntegration Integration methods │
└─────────────────────────────────────────────────────────────────┘
┌─────────────────────────────────────────────────────────────────┐
│ CATEGORY F: QUALITY (1 agent) │
├─────────────────────────────────────────────────────────────────┤
│ diverga:f5 HumanizationVerifier Verify humanization │
└─────────────────────────────────────────────────────────────────┘
┌─────────────────────────────────────────────────────────────────┐
│ CATEGORY G: COMMUNICATION (4 agents) │
├─────────────────────────────────────────────────────────────────┤
│ diverga:g1 JournalMatcher Match journals │
│ diverga:g2 PublicationSpecialist Writing + Review + PreReg│
│ + Quality (absorbed G3, G4, F1, F2, F3) │
│ diverga:g5 AcademicStyleAuditor AI pattern detection │
│ diverga:g6 AcademicStyleHumanizer Humanize AI text │
└─────────────────────────────────────────────────────────────────┘
┌─────────────────────────────────────────────────────────────────┐
│ CATEGORY I: SYSTEMATIC REVIEW (4 agents) │
├─────────────────────────────────────────────────────────────────┤
│ diverga:i0 ReviewPipelineOrchestrator Pipeline coordination │
│ diverga:i1 PaperRetrievalAgent Multi-database fetch │
│ diverga:i2 ScreeningAssistant AI-PRISMA screening │
│ diverga:i3 RAGBuilder Vector DB + Parallel │
│ (absorbed B5) │
└─────────────────────────────────────────────────────────────────┘
┌─────────────────────────────────────────────────────────────────┐
│ CATEGORY X: CROSS-CUTTING (1 agent) │
├─────────────────────────────────────────────────────────────────┤
│ diverga:x1 ResearchGuardian Ethics + Bias detection │
│ (absorbed A4, F4) │
└─────────────────────────────────────────────────────────────────┘
┌─────────────────────────────────────────────────────────────────┐
│ HUMAN CHECKPOINTS │
├─────────────────────────────────────────────────────────────────┤
│ 🔴 REQUIRED (System STOPS): │
│ CP_PARADIGM Research paradigm selection │
│ CP_METHODOLOGY Methodology approval │
│ │
│ 🟠 RECOMMENDED (System PAUSES): │
│ CP_THEORY Theory framework selection │
│ CP_DATA_VALIDATION Data extraction validation │
└─────────────────────────────────────────────────────────────────┘
┌─────────────────────────────────────────────────────────────────┐
│ MODEL ROUTING │
├─────────────────────────────────────────────────────────────────┤
│ HIGH (Opus): A1,A2,A5,C1,C2,C3,C5,D4,E1,E2,E3,G6,I0 │
│ MEDIUM (Sonnet): B1,B2,D2,G1,G2,G5,X1,I1,I2 │
│ LOW (Haiku): F5,I3 │
└─────────────────────────────────────────────────────────────────┘
┌─────────────────────────────────────────────────────────────────┐
│ AUTO-TRIGGER KEYWORDS │
├─────────────────────────────────────────────────────────────────┤
│ "research question", "RQ", "연구 질문" → diverga:a1 │
│ "theoretical framework", "이론적 프레임워크" → diverga:a2 │
│ "critique", "devil's advocate", "반론" → diverga:a2 │
│ "IRB", "ethics", "연구 윤리" → diverga:x1 │
│ "meta-analysis", "메타분석", "효과크기" → diverga:c5 │
│ "systematic review", "PRISMA" → diverga:b1 │
│ "qualitative", "interview", "질적 연구" → diverga:c2 │
│ "ethnography", "action research" → diverga:c2 │
└─────────────────────────────────────────────────────────────────┘
For more info: https://github.com/HosungYou/Diverga
Direct Agent Invocation
Users can invoke specific agents:
diverga:c5 # Invoke Meta-Analysis Master directly
diverga:a1 # Invoke Research Question Refiner
Implementation Notes
- Help content adapts to user's language preference
- Agent recommendations based on detected research context
- Links to GitHub for full documentation
What ships with it
Read from the repository
Just SKILL.md. No reference files, no scripts.