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Setup

Skill brycewang-stanford/Auto-Empirical-Research-Skills/skills/25-HosungYou-Diverga/skills/setup

๐Ÿ”ฌ A curated collection of 23,000+ agent skills for empirical research across 8 social science disciplines. | ็ฒพ้€‰ 23,000+ AI Agent ๆŠ€่ƒฝๅบ“๏ผŒ่ฆ†็›–8ๅคง็คพไผš็ง‘ๅญฆๅญฆ็ง‘็š„ๅฎž่ฏ็ ”็ฉถใ€‚CoPaper.AI 20ๅˆ†้’ŸๅฎŒๆˆไธ€็ฏ‡ๅฏๅค็Žฐ็š„่ง„่Œƒๅฎž่ฏ่ฎบๆ–‡๏ผŒๅนถๆ”ฏๆŒ็”จๆˆทไธŠไผ  Skillsใ€‚-- Maintained by CoPaper.AI from Stanford REAP.

Install
npx -y skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill setup

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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, ์„ค์ •, install

SKILL.md

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/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 โ€” no dead config fields
  2. Lazy config for rare features โ€” OpenAlex email, citation format, qual software are asked when the relevant agent runs for the first time
  3. Researcher profile is stable โ€” 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 โ†’ "Existing profile detected. Update?"
  • Otherwise โ†’ "New profile setup"

Step 1: Welcome + Researcher Profile

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

โ•”โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•—
โ•‘                    Welcome to Diverga v12.0                     โ•‘
โ•‘   AI Research Assistant - 29 Agents (24 core + 5 VS Arena)      โ•‘
โ• โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•ฃ
โ•‘                                                                  โ•‘
โ•‘  Diverga adapts to your background.                             โ•‘
โ•‘  A doctoral student gets more scaffolding.                      โ•‘
โ•‘  An experienced faculty gets concise recommendations.           โ•‘
โ•‘  Your preferred tools determine code and database suggestions.  โ•‘
โ•‘                                                                  โ•‘
โ•šโ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•
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 โ†’ A1 explains PICO/SPIDER, C1 scaffolds power analysis, E1 adds interpretation guidance
  • Faculty โ†’ Agents skip explanations, go straight to options and trade-offs
  • Discipline โ†’ 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 โ†’ E1 generates code ONLY in selected languages (no more 4-language output)
  • DB access โ†’ 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" โ†’ "doctoral_student"
  • "Postdoc / Early Career" โ†’ "early_career"
  • "Faculty / Senior Researcher" โ†’ "faculty"

Display completion:

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

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 โ€” 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."
โ†’ AskUserQuestion: [Enter email] [Skip]
โ†’ 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 โ†’ display:
    Welcome to Diverga! Run /diverga:setup to set up your researcher profile (1 minute).
    
  3. Do NOT auto-run โ€” 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 โ€” set during /diverga:setup
  • researcher.qual_software, citation_format โ€” added by lazy config when relevant agent runs
  • agent_teams, vs_arena โ€” set during /diverga:setup Step 3

Error Handling

If config directory doesn't exist, create it:

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

Keep looking

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