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setup

Set up Diverga through an interactive researcher profile wizard. It records your discipline, experience, statistical tools, database access, and collaboration preferences, then saves configuration that guides explanations, code suggestions, and database recommendations.

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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, 설정, install

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查看安装方法

适用场景

  • Setting up a Diverga researcher profile
  • Updating statistical software preferences
  • Recording available academic databases
  • Choosing multi-agent collaboration and debate modes

包含的文件(1)

  • SKILL.md11.8 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

/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

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