Skill
pipeline
Classical end-to-end empirical analysis workflow in the traditional Python econometric stack — pandas + numpy + scipy + statsmodels + linearmodels + pyfixest +…
Automation
Skill
/help
Diverga help guide - displays all 24 agents across 9 categories, commands, and usage examples. Triggers: help, guide, how to use, 도움말
Install
$ npx -y skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill help --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/help
Context preview
The summary Claude sees to decide when to auto-load this skill.
Diverga help guide - displays all 24 agents across 9 categories, commands, and usage examples. Triggers: help, guide, how to use, 도움말
SKILL.md
help.SKILL.mdname: help
description: |
Diverga help guide - displays all 24 agents across 9 categories, commands, and usage examples.
Triggers: help, guide, how to use, 도움말
version: "12.0.1"
/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 Pa
Read more
name: help description: | Diverga help guide - displays all 24 agents across 9 categories, commands, and usage examples. Triggers: help, guide, how to use, 도움말 version: "12.0.1"
/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 Pa
Ships withauto-empirical-research-skills
📌 文档结构（2026-07-22 起）： 本文件是中文默认入口 —— banner + badges + 信任面 + 9 阶段流水线速览 + 76 行合集总表。 每个合集的完整描述、按用途分组、精确数字、验证方法在 docs/CONTENT_ZH.md（扩展正文，总表行内的 → 直接跳转到对应锚点）。 English version: README-en.md · 中文扩展正文：docs/CONTENT_ZH.md · README-zh-CN.md 已弃用（重定向占位） 🌐 语言: English |
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