discover-research
About
The discover-research skill is a gateway that automatically loads other specialized research skills based on the context of your task. It activates for various research activities, including study design, data analysis, literature reviews, and academic writing. This provides developers with a streamlined way to access a full suite of research methodology tools without manually selecting individual skills.
Quick Install
Claude Code
Recommended/plugin add https://github.com/rand/cc-polymathgit clone https://github.com/rand/cc-polymath.git ~/.claude/skills/discover-researchCopy and paste this command in Claude Code to install this skill
Documentation
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 Repository
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