--- name: discover-research description: Automatically discover research methodology skills when working with research methodology, literature review, systematic review, evidence synthesis, academic research, or experimental design. Activates for research tasks. license: MIT metadata: author: rand version: "4.0" compatibility: Designed for Claude Code. Compatible with any agent supporting the Agent Skills format. --- # 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 Read ../research/research-synthesis.md Read ../research/quantitative-methods.md Read ../research/qualitative-methods.md Read ../research/research-design.md Read ../research/data-collection.md Read ../research/data-analysis.md Read ../research/research-writing.md ### Common Workflow Combinations **Quantitative Research Study**: # Planning phase Read ../research/research-design.md # Data collection Read ../research/data-collection.md Read ../research/quantitative-methods.md # Analysis and reporting Read ../research/data-analysis.md Read ../research/research-writing.md **Qualitative Research Study**: # Planning phase Read ../research/research-design.md # Data collection Read ../research/data-collection.md Read ../research/qualitative-methods.md # Analysis and reporting Read ../research/data-analysis.md Read ../research/research-writing.md **Literature Review / Meta-Analysis**: # Synthesis phase Read ../research/research-synthesis.md # If including quantitative synthesis Read ../research/quantitative-methods.md # Writing phase Read ../research/research-writing.md **Mixed Methods Study**: # All methods Read ../research/research-design.md Read ../research/quantitative-methods.md Read ../research/qualitative-methods.md Read ../research/data-collection.md Read ../research/data-analysis.md Read ../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" Read ../research/research-design.md Read ../research/data-collection.md Read ../research/quantitative-methods.md ### "I need to analyze interview transcripts" Read ../research/qualitative-methods.md Read ../research/data-analysis.md ### "I need to conduct a meta-analysis" Read ../research/research-synthesis.md Read ../research/quantitative-methods.md ### "I need to write up my results" Read ../research/research-writing.md Read ../research/data-analysis.md ## Best Practices 1. **Start with design**: Load research-design first when planning new studies 2. **Method-specific loading**: Load only the method skill you need (quant OR qual) 3. **Progressive addition**: Add skills as you progress through research phases 4. **Unload when done**: Unload skills from completed phases to manage context 5. **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