Discover Research | Skills Pool
Discover Research 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.
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
クイックインストール
Discover Research npx skillvault add rand/rand-cc-polymath-skills-discover-research-skill-md
スター 93
更新日 2026/02/28
職業
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
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
statistics : Advanced statistical techniquesdata-science : Machine learning and big data approachesvisualization : Advanced data visualizationacademic-writing : General academic writing skillsscientific-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
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
Start with design : Load research-design first when planning new studiesMethod-specific loading : Load only the method skill you need (quant OR qual)Progressive addition : Add skills as you progress through research phasesUnload when done : Unload skills from completed phases to manage contextKeep 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 analysispython-visualization : For publication graphicsacademic-latex : For paper formattinggit-workflow : For research project managementreproducibility : For reproducible research practices 02
Auto-Activation