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
- 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
- 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
- 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
- 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
- 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
- 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
- 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 ~/.claude/skills/research/research-synthesis.md cat ~/.claude/skills/research/quantitative-methods.md cat ~/.claude/skills/research/qualitative-methods.md cat ~/.claude/skills/research/research-design.md cat ~/.claude/skills/research/data-collection.md cat ~/.claude/skills/research/data-analysis.md cat ~/.claude/skills/research/research-writing.md
Common Workflow Combinations
Quantitative Research Study:
Planning phase
cat ~/.claude/skills/research/research-design.md
Data collection
cat ~/.claude/skills/research/data-collection.md cat ~/.claude/skills/research/quantitative-methods.md
Analysis and reporting
cat ~/.claude/skills/research/data-analysis.md cat ~/.claude/skills/research/research-writing.md
Qualitative Research Study:
Planning phase
cat ~/.claude/skills/research/research-design.md
Data collection
cat ~/.claude/skills/research/data-collection.md cat ~/.claude/skills/research/qualitative-methods.md
Analysis and reporting
cat ~/.claude/skills/research/data-analysis.md cat ~/.claude/skills/research/research-writing.md
Literature Review / Meta-Analysis:
Synthesis phase
cat ~/.claude/skills/research/research-synthesis.md
If including quantitative synthesis
cat ~/.claude/skills/research/quantitative-methods.md
Writing phase
cat ~/.claude/skills/research/research-writing.md
Mixed Methods Study:
All methods
cat ~/.claude/skills/research/research-design.md cat ~/.claude/skills/research/quantitative-methods.md cat ~/.claude/skills/research/qualitative-methods.md cat ~/.claude/skills/research/data-collection.md cat ~/.claude/skills/research/data-analysis.md cat ~/.claude/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 ~/.claude/skills/research/research-design.md cat ~/.claude/skills/research/data-collection.md cat ~/.claude/skills/research/quantitative-methods.md
"I need to analyze interview transcripts" cat ~/.claude/skills/research/qualitative-methods.md cat ~/.claude/skills/research/data-analysis.md
"I need to conduct a meta-analysis" cat ~/.claude/skills/research/research-synthesis.md cat ~/.claude/skills/research/quantitative-methods.md
"I need to write up my results" cat ~/.claude/skills/research/research-writing.md cat ~/.claude/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