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cccskills
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help

Diverga help guide - displays all 24 agents across 9 categories, commands, and usage examples. Triggers: help, guide, how to use, 도움말

インストール方法を見る

含まれるファイル(1)

  • SKILL.md15.1 KB

SKILL.md(原文)

インストールする前に、エージェントに与えられる指示の中身を確認できます。

/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

レビュー

まだレビューはありません。使ってみた感想をお寄せください。

同じリポジトリのスキル

概要と使いどころ

a1

無料

VS-Enhanced Research Question Refiner - Prevents Mode Collapse and derives differentiated research questions Enhanced VS 3-Phase process: Modal question avoidance, alternatives presentation, differentiated RQ recommendation Use when: refining research ideas, formulating research questions, clarifying scope Triggers: research question, 연구 질문, PICO, SPIDER, research idea

日本語の概要は準備中です。原文の説明を表示しています。

brycewang-stanford/Auto-Empirical-Research-Skills4,5992026年10月12日 更新

a2

無料

VS-Enhanced Theoretical Framework Architect with Critique & Visualization Full VS 5-Phase process: Modal theory avoidance, Long-tail exploration, differentiated framework presentation Absorbed A3 (Devil's Advocate) critique and A6 (Conceptual Framework Visualizer) capabilities Use when: building theoretical foundations, designing conceptual models, deriving hypotheses, critiquing frameworks, visualizing models Triggers: theoretical framework, 이론적 프레임워크, conceptual model, 개념적 모형, hypothesis derivation, critique, devil's advocate, 반론, visualization, diagram

日本語の概要は準備中です。原文の説明を表示しています。

brycewang-stanford/Auto-Empirical-Research-Skills4,5992026年10月12日 更新

a5

無料

Agent A5 - Paradigm & Worldview Advisor - Philosophical foundations for research design. Covers ontology, epistemology, axiology, and methodology alignment. Use when: establishing philosophical foundations, justifying methodological choices, writing positionality statements Triggers: paradigm, 패러다임, ontology, epistemology, worldview, 세계관, philosophical foundations, 철학적 기초

日本語の概要は準備中です。原文の説明を表示しています。

brycewang-stanford/Auto-Empirical-Research-Skills4,5992026年10月12日 更新

Academic paper writing skill with 12-agent pipeline. v2.5: Style Calibration (learn author's writing voice from past papers) + Writing Quality Check (writing quality checklist for natural prose). Supports IMRaD, literature review, theoretical, case study, policy brief, and conference paper structures. APA 7.0 (default), Chicago, MLA, IEEE, Vancouver citation formats. Bilingual abstracts (zh-TW + EN). Multi-format output (LaTeX, DOCX, PDF, Markdown). Triggers on: write paper, academic paper, paper outline, write abstract, revise paper, check citations, convert to LaTeX, guide my paper, parse reviews, revision roadmap, 寫論文, 學術論文, 論文大綱, 寫摘要, 修改論文, 檢查引用, 引導我寫論文, 帶我規劃論文, 逐章規劃, 論文架構, 審查意見, 修訂路線圖.

日本語の概要は準備中です。原文の説明を表示しています。

brycewang-stanford/Auto-Empirical-Research-Skills4,5992026年10月12日 更新

Systematic writing framework for philosophy and interdisciplinary academic papers from optimized outline to submission-ready manuscript. Use when users want to: (1) write a paper from a detailed outline, (2) ensure quality control during writing, (3) maintain consistency across chapters, (4) prepare a submission-ready manuscript, or (5) systematically execute a planned paper. Triggered by phrases like 'write the paper from this outline,' 'compose the full manuscript,' 'execute the outline,' or when users have completed strategic planning (academic-paper-strategist skill) and are ready to write. Takes optimized outline as input; outputs complete manuscript with iterative quality checks.

日本語の概要は準備中です。原文の説明を表示しています。

brycewang-stanford/Auto-Empirical-Research-Skills4,5992026年10月12日 更新

Multi-perspective academic paper review with dynamic reviewer personas. Simulates 5 independent reviewers (EIC + 3 peer reviewers + Devil's Advocate) with field-specific expertise. Supports full review, re-review (verification), quick assessment, methodology focus, and Socratic guided modes. Triggers on: review paper, peer review, manuscript review, referee report, review my paper, critique paper, simulate review, editorial review.

日本語の概要は準備中です。原文の説明を表示しています。

brycewang-stanford/Auto-Empirical-Research-Skills4,5992026年10月12日 更新

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