discover-research
について
discover-researchスキルは、タスクの内容に応じて自動的に専門的な研究スキルを読み込むゲートウェイ機能です。研究デザイン、データ分析、文献レビュー、学術論文執筆など、様々な研究活動において作動します。これにより、開発者は個々のスキルを手動で選択することなく、研究方法論ツール一式にシームレスにアクセスできるようになります。
クイックインストール
Claude Code
推奨/plugin add https://github.com/rand/cc-polymathgit clone https://github.com/rand/cc-polymath.git ~/.claude/skills/discover-researchこのコマンドをClaude Codeにコピー&ペーストしてスキルをインストールします
ドキュメント
Research Skills Discovery
Auto-Activation
This skill is automatically activated when your task involves:
- Research synthesis, literature reviews, meta-analysis
- Quantitative research, statistical analysis, surveys, experiments
- Qualitative research, interviews, ethnography, case studies
- Study design, hypothesis testing, sampling strategies
- Data collection, survey design, interview protocols
- Data analysis, coding, statistical tests, visualization
- Research writing, academic papers, citations, reporting
Available Research Skills
Core Methodology Skills
1. research-synthesis - Synthesizing information and conducting meta-analysis
- Narrative synthesis approaches
- Meta-analysis with Python implementation
- Thematic synthesis of qualitative findings
- Evidence mapping and gap analysis
- GRADE framework for quality assessment
- Use when: Integrating findings across studies
2. quantitative-methods - Quantitative research and statistical analysis
- Experimental design with power analysis
- Survey methods and analysis
- Hypothesis testing framework
- Regression analysis with diagnostics
- Effect sizes and reporting
- Use when: Testing hypotheses with numerical data
3. qualitative-methods - Qualitative research approaches
- In-depth interview protocols
- Thematic analysis (6 phases)
- Grounded theory coding
- Case study research design
- Quality criteria and rigor
- Use when: Exploring experiences and meanings
4. research-design - Planning and designing research studies
- Research question formulation (FINER criteria)
- Validity threat analysis
- Sampling strategies with Python tools
- Experimental control frameworks
- Design quality assessment
- Use when: Planning a new study from scratch
Implementation Skills
5. data-collection - Methods for gathering research data
- Survey instrument design and validation
- Interview protocol development
- Observation methods and field notes
- Data quality control frameworks
- Response rate optimization
- Use when: Implementing data collection
6. data-analysis - Analyzing quantitative and qualitative data
- Comprehensive descriptive statistics
- Inferential testing with full reporting
- Systematic qualitative coding
- Thematic development process
- Publication-ready visualizations
- Use when: Making sense of collected data
7. research-writing - Writing research papers and reports
- IMRAD structure with guidelines
- APA statistical reporting
- Citation management
- Argument construction
- Peer review response strategies
- Use when: Communicating research findings
Loading Skills
Load Individual Skills
# From skills directory
cat skills/research/research-synthesis.md
cat skills/research/quantitative-methods.md
cat skills/research/qualitative-methods.md
cat skills/research/research-design.md
cat skills/research/data-collection.md
cat skills/research/data-analysis.md
cat skills/research/research-writing.md
Common Workflow Combinations
Quantitative Research Study:
# Planning phase
cat skills/research/research-design.md
# Data collection
cat skills/research/data-collection.md
cat skills/research/quantitative-methods.md
# Analysis and reporting
cat skills/research/data-analysis.md
cat skills/research/research-writing.md
Qualitative Research Study:
# Planning phase
cat skills/research/research-design.md
# Data collection
cat skills/research/data-collection.md
cat skills/research/qualitative-methods.md
# Analysis and reporting
cat skills/research/data-analysis.md
cat skills/research/research-writing.md
Literature Review / Meta-Analysis:
# Synthesis phase
cat skills/research/research-synthesis.md
# If including quantitative synthesis
cat skills/research/quantitative-methods.md
# Writing phase
cat skills/research/research-writing.md
Mixed Methods Study:
# All methods
cat skills/research/research-design.md
cat skills/research/quantitative-methods.md
cat skills/research/qualitative-methods.md
cat skills/research/data-collection.md
cat skills/research/data-analysis.md
cat skills/research/research-writing.md
Progressive Loading
Load skills progressively based on research phase:
Phase 1: Planning (Load 1-2 skills)
- research-design (always)
- quantitative-methods OR qualitative-methods (based on approach)
Phase 2: Collection (Add 1-2 skills)
- data-collection (always)
- Keep loaded: specific method skill
Phase 3: Analysis (Add 1 skill)
- data-analysis (always)
- Keep loaded: method and collection skills for reference
Phase 4: Writing (Add 1 skill, can unload others)
- research-writing (always)
- research-synthesis (if synthesizing literature)
- Keep one method skill for reporting details
Phase 5: Synthesis (If conducting review)
- research-synthesis (load early)
- quantitative-methods (if meta-analysis)
- qualitative-methods (if thematic synthesis)
Decision Tree
Research Task
↓
Conducting new study?
YES → Load research-design
↓
Quantitative approach?
YES → Load quantitative-methods + data-collection
Qualitative approach?
YES → Load qualitative-methods + data-collection
Mixed methods?
YES → Load both methods + data-collection
↓
Ready to analyze?
YES → Load data-analysis
↓
Ready to write?
YES → Load research-writing
NO → Synthesizing existing research?
YES → Load research-synthesis
↓
Quantitative synthesis (meta-analysis)?
YES → Also load quantitative-methods
Qualitative synthesis?
YES → Also load qualitative-methods
↓
Ready to write?
YES → Load research-writing
Context-Aware Loading
Based on keywords in your task, these skills auto-load:
Keywords → Skills Mapping:
- "literature review", "meta-analysis", "systematic review" → research-synthesis
- "survey", "experiment", "hypothesis", "statistical" → quantitative-methods
- "interview", "ethnography", "case study", "lived experience" → qualitative-methods
- "study design", "sampling", "validity", "research plan" → research-design
- "questionnaire", "data collection", "measurement" → data-collection
- "analyze data", "coding", "statistical test", "thematic" → data-analysis
- "write paper", "manuscript", "citation", "peer review" → research-writing
Related Skill Categories
- statistics: Advanced statistical techniques
- data-science: Machine learning and big data approaches
- visualization: Advanced data visualization
- academic-writing: General academic writing skills
- scientific-computing: Python/R for research computing
Quick Start Examples
"I need to design a survey study"
cat skills/research/research-design.md
cat skills/research/data-collection.md
cat skills/research/quantitative-methods.md
"I need to analyze interview transcripts"
cat skills/research/qualitative-methods.md
cat skills/research/data-analysis.md
"I need to conduct a meta-analysis"
cat skills/research/research-synthesis.md
cat skills/research/quantitative-methods.md
"I need to write up my results"
cat skills/research/research-writing.md
cat skills/research/data-analysis.md
Best Practices
- Start with design: Load research-design first when planning new studies
- Method-specific loading: Load only the method skill you need (quant OR qual)
- Progressive addition: Add skills as you progress through research phases
- Unload when done: Unload skills from completed phases to manage context
- Keep writing loaded: research-writing useful throughout for documentation
Skill Maintenance
All research skills follow these standards:
- Practical code examples (Python primary, R when appropriate)
- Real-world templates and protocols
- Best practices and anti-patterns
- Cross-references to related skills
- 250-400 lines optimized for context efficiency
Integration with Other Skills
Research skills integrate well with:
- python-data-science: For advanced analysis
- python-visualization: For publication graphics
- academic-latex: For paper formatting
- git-workflow: For research project management
- reproducibility: For reproducible research practices
GitHub リポジトリ
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