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setup

Diverga v12.0 setup wizard. 4-step researcher profile setup. Captures discipline, experience, tools, database access, and Agent Teams + VS Arena preference. Triggers: setup, configure, 설정, install

Published by brycewang-stanford ↗brycewang-stanford/Auto-Empirical-Research-Skills

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setup

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Use setup to set up my Diverga researcher profile by collecting my discipline, experience, statistical tools, database access, and collaboration preference; generate the resulting configuration, and if my choice would change shared settings, stop for my final confirmation before making that change.

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    SKILL.md

    name: setupdescription: |  Diverga v12.0 setup wizard. 4-step researcher profile setup.  Captures discipline, experience, tools, database access, and Agent Teams + VS Arena preference.  Triggers: setup, configure, 설정, installversion: "12.0.1"

    /diverga:setup

    Version: 12.0.0 Trigger: /diverga:setup

    Description

    Diverga setup wizard. 4 steps: Researcher Profile, Tools & Access, Agent Teams + VS Arena, Config Generation. Captures information that genuinely changes agent behavior.

    Design Principles

    1. Only ask what agents actually use — no dead config fields
    2. Lazy config for rare features — OpenAlex email, citation format, qual software are asked when the relevant agent runs for the first time
    3. Researcher profile is stable — discipline and tools don't change per project; checkpoints handle project-specific decisions

    Workflow

    When user invokes /diverga:setup, execute this interactive wizard:

    Step 0: Project Detection

    Check for existing config:

    • If ~/.claude/plugins/diverga/config/diverga-config.json exists with researcher field → "Existing profile detected. Update?"
    • Otherwise → "New profile setup"

    Step 1: Welcome + Researcher Profile

    Display welcome message, then ask TWO questions using a single AskUserQuestion call:

    ╔══════════════════════════════════════════════════════════════════╗
    ║                    Welcome to Diverga v12.0                     ║
    ║   AI Research Assistant - 29 Agents (24 core + 5 VS Arena)      ║
    ╠══════════════════════════════════════════════════════════════════╣
    ║                                                                  ║
    ║  Diverga adapts to your background.                             ║
    ║  A doctoral student gets more scaffolding.                      ║
    ║  An experienced faculty gets concise recommendations.           ║
    ║  Your preferred tools determine code and database suggestions.  ║
    ║                                                                  ║
    ╚══════════════════════════════════════════════════════════════════╝
    
    questions:
      - question: "What is your primary research discipline?"
        header: "Discipline"
        multiSelect: false
        options:
          - label: "Education"
            description: "Educational Technology, Curriculum, Higher Ed, STEM Ed, etc."
          - label: "Psychology"
            description: "Clinical, Developmental, Social, Cognitive, I/O, etc."
          - label: "Health Sciences"
            description: "Public Health, Nursing, Medicine, Rehabilitation, etc."
          - label: "Social Sciences"
            description: "Sociology, Political Science, Communication, Business, etc."
        # User can also type a custom discipline via "Other"
    
      - question: "What is your research experience level?"
        header: "Experience"
        multiSelect: false
        options:
          - label: "Doctoral Student"
            description: "Currently pursuing PhD/EdD. More guidance on methodology and analysis."
          - label: "Postdoc / Early Career"
            description: "Completed doctorate. Familiar with research process."
          - label: "Faculty / Senior Researcher"
            description: "Experienced researcher. Concise recommendations preferred."
    

    How this affects agents:

    • Doctoral Student → A1 explains PICO/SPIDER, C1 scaffolds power analysis, E1 adds interpretation guidance
    • Faculty → Agents skip explanations, go straight to options and trade-offs
    • Discipline → G1 prioritizes field-specific journals, I1 leads with field-appropriate databases

    Step 2: Tools & Institutional Access

    Ask TWO questions using a single AskUserQuestion call:

    questions:
      - question: "Which statistical software do you use?"
        header: "Stats Tools"
        multiSelect: true
        options:
          - label: "R"
            description: "tidyverse, lavaan, lme4, etc."
          - label: "Python"
            description: "pandas, statsmodels, scikit-learn, etc."
          - label: "SPSS"
            description: "IBM SPSS Statistics"
          - label: "Stata"
            description: "Stata/SE or Stata/MP"
    
      - question: "Which academic databases can you access?"
        header: "DB Access"
        multiSelect: true
        options:
          - label: "Scopus"
            description: "Elsevier Scopus (institutional subscription)"
          - label: "Web of Science"
            description: "Clarivate WoS (institutional subscription)"
          - label: "PsycINFO"
            description: "APA PsycINFO (institutional subscription)"
          - label: "ERIC + Semantic Scholar (free)"
            description: "Always available, no subscription needed"
    

    How this affects agents:

    • Stats tools → E1 generates code ONLY in selected languages (no more 4-language output)
    • DB access → I1/I0 recommends only accessible databases at SCH_DATABASE_SELECTION checkpoint

    Step 3: Agent Teams and VS Arena

    question: "Configure multi-agent collaboration mode"
    header: "Agent Teams"
    options:
      - label: "Agent Teams + VS Arena (Recommended)"
        description: "Full parallel execution with inter-agent communication. VS Arena debates use real cross-critique between personas. Requires Claude Code v2.1.32+. Higher token usage."
      - label: "Subagents + Classic VS (Default)"
        description: "Agents run as subagents. VS Arena generates options from single agent (no cross-critique). Lower cost."
      - label: "Disabled"
        description: "No multi-agent features. Single agent execution only."
    

    If "Agent Teams + VS Arena" selected, add to config:

    {
      "agent_teams": { "enabled": true },
      "vs_arena": { "enabled": true, "team_size": 3, "cross_critique": true }
    }
    

    Also set CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS=1 in user's settings.json env:

    1. Write to ~/.claude/settings.json:
      { "env": { "CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS": "1" } }
      
      (merge with existing settings, don't overwrite)

    If "Subagents + Classic VS" selected, add to config:

    {
      "agent_teams": { "enabled": false },
      "vs_arena": { "enabled": true, "team_size": 3, "cross_critique": false }
    }
    

    If "Disabled" selected, add to config:

    {
      "agent_teams": { "enabled": false },
      "vs_arena": { "enabled": false }
    }
    

    Step 4: Generate Configuration & Complete

    After collecting all preferences, generate config/diverga-config.json at ~/.claude/plugins/diverga/config/:

    {
      "version": "12.0.0",
      "researcher": {
        "discipline": "Education",
        "experience": "doctoral_student",
        "stats_software": ["R", "SPSS"],
        "db_access": ["Scopus", "ERIC", "Semantic Scholar"]
      },
      "agent_teams": { "enabled": true },
      "vs_arena": { "enabled": true, "team_size": 3, "cross_critique": true }
    }
    

    Experience level mapping:

    • "Doctoral Student" → "doctoral_student"
    • "Postdoc / Early Career" → "early_career"
    • "Faculty / Senior Researcher" → "faculty"

    Display completion:

    ╔══════════════════════════════════════════════════════════════════╗
    ║                  Diverga v12.0 Setup Complete!                  ║
    ╠══════════════════════════════════════════════════════════════════╣
    ║                                                                  ║
    ║  Profile saved:                                                  ║
    ║    Discipline: Education                                        ║
    ║    Experience: Doctoral Student                                  ║
    ║    Stats: R, SPSS                                               ║
    ║    Databases: Scopus, ERIC, Semantic Scholar                    ║
    ║    Agent Teams: Enabled                                          ║
    ║    VS Arena: Cross-critique enabled                              ║
    ║                                                                  ║
    ║  29 agents (24 core + 5 VS Arena)                               ║
    ║  Agent Teams orchestrator — unified parallel and debate workflows║
    ║                                                                  ║
    ║  Quick Start:                                                    ║
    ║  - Just describe your research in natural language               ║
    ║  - "I want to conduct a systematic review on AI in education"    ║
    ║  - Diverga adapts to your profile automatically                  ║
    ║                                                                  ║
    ║  Commands:                                                       ║
    ║  - /diverga:help     - View all 29 agents                       ║
    ║  - /diverga:memory   - Memory system commands                    ║
    ║  - /diverga:setup    - Update your profile anytime               ║
    ║                                                                  ║
    ╚══════════════════════════════════════════════════════════════════╝
    

    Lazy Config (Agent-Level)

    These settings are NOT asked during setup. Each agent asks when first needed:

    SettingAgentWhen AskedStorage
    OpenAlex emailG1 (Journal Matcher)First journal_search_by_field call.omc/config.json
    Citation formatG2 (Publication)First manuscript generationresearcher.citation_format in config
    Qualitative softwareE2 (Coding)First qualitative coding taskresearcher.qual_software in config

    Lazy config prompt template (for agents to use):

    When an agent needs a lazy config value that isn't set yet:

    1. Explain WHY the information is needed (1 sentence, tied to the current task)
    2. Ask via AskUserQuestion with relevant options
    3. Save to config/diverga-config.json under the researcher object
    4. Continue with the task — do NOT restart or re-prompt

    Example (G1 first call):

    "Journal search uses OpenAlex API. Registering your email enables
    faster responses (polite pool). This is optional."
    → AskUserQuestion: [Enter email] [Skip]
    → If email: save to .omc/config.json
    

    First-Run Detection

    When a Diverga plugin session starts:

    1. Check if ~/.claude/plugins/diverga/config/diverga-config.json exists with researcher field
    2. If missing → display:
      Welcome to Diverga! Run /diverga:setup to set up your researcher profile (1 minute).
      
    3. Do NOT auto-run — only display the suggestion once.

    Config Schema Reference

    {
      "version": "12.0.0",
      "researcher": {
        "discipline": "string",
        "experience": "doctoral_student | early_career | faculty",
        "stats_software": ["R", "Python", "SPSS", "Stata", "Mplus"],
        "db_access": ["Scopus", "Web of Science", "PsycINFO", "ERIC", "Semantic Scholar"],
        "qual_software": "NVivo | ATLAS.ti | MAXQDA | Dedoose | manual",
        "citation_format": "APA | Chicago | Vancouver | Harvard"
      },
      "agent_teams": {
        "enabled": "boolean"
      },
      "vs_arena": {
        "enabled": "boolean",
        "team_size": "number (default 3)",
        "cross_critique": "boolean"
      }
    }
    

    Fields are added incrementally:

    • researcher.discipline, experience, stats_software, db_access — set during /diverga:setup
    • researcher.qual_software, citation_format — added by lazy config when relevant agent runs
    • agent_teams, vs_arena — set during /diverga:setup Step 3

    Error Handling

    If config directory doesn't exist, create it:

    mkdir -p ~/.claude/plugins/diverga/config