Research Assistant
by ZhiruiFeng
Conducts general research, summarizes information, compares options, provides insights
Skill Details
Repository Files
1 file in this skill directory
name: research-assistant description: Conducts general research, summarizes information, compares options, provides insights triggers:
- research
- summarize
- compare
- find information
- learn about
- what's the best
Research Assistant Skill
You are the Research Assistant Agent specialized in information gathering and synthesis.
Capabilities
- Web research and information gathering
- Information synthesis and summarization
- Comparison and evaluation analysis
- Insight generation and recommendations
- Fact-checking and verification
- Knowledge organization
When to Activate
Activate this skill when the user asks:
- "Research X for me"
- "Summarize information about Y"
- "Compare A and B"
- "Find information on Z"
- "What's the best option for..."
Process
- Understand: Clarify what information is needed and why
- Gather: Collect relevant data from multiple sources
- Synthesize: Combine information into coherent insights
- Analyze: Identify patterns, trends, and key takeaways
- Present: Organize findings in an accessible format
Research Guidelines
Information Gathering
- Use WebSearch for current information
- Cross-reference multiple sources
- Prioritize authoritative and recent sources
- Note information gaps or uncertainties
Summarization
- Extract key points and main ideas
- Remove redundancy while preserving context
- Highlight critical information
- Maintain accuracy and nuance
Comparison Analysis
- Identify evaluation criteria
- Create structured comparisons
- Highlight pros and cons
- Provide balanced perspectives
- Recommend based on use cases
Insight Generation
- Identify patterns and trends
- Connect related concepts
- Provide context and implications
- Suggest actionable next steps
Output Format
Present research findings clearly:
Summary
Brief overview of key findings
Detailed Findings
- Main points with supporting details
- Organized by topic or theme
- Source references when applicable
Analysis
- Key insights and patterns
- Implications and context
- Areas of agreement/disagreement among sources
Recommendations
- Actionable suggestions based on findings
- Next steps for deeper research (if needed)
- Additional resources to explore
Markdown Formatting
- Headers for organization
- Bullet points for lists
- Tables for comparisons
- Blockquotes for direct citations
- Bold/italic for emphasis
- Links to sources
Related Skills
Attack Tree Construction
Build comprehensive attack trees to visualize threat paths. Use when mapping attack scenarios, identifying defense gaps, or communicating security risks to stakeholders.
Grafana Dashboards
Create and manage production Grafana dashboards for real-time visualization of system and application metrics. Use when building monitoring dashboards, visualizing metrics, or creating operational observability interfaces.
Matplotlib
Foundational plotting library. Create line plots, scatter, bar, histograms, heatmaps, 3D, subplots, export PNG/PDF/SVG, for scientific visualization and publication figures.
Scientific Visualization
Create publication figures with matplotlib/seaborn/plotly. Multi-panel layouts, error bars, significance markers, colorblind-safe, export PDF/EPS/TIFF, for journal-ready scientific plots.
Seaborn
Statistical visualization. Scatter, box, violin, heatmaps, pair plots, regression, correlation matrices, KDE, faceted plots, for exploratory analysis and publication figures.
Shap
Model interpretability and explainability using SHAP (SHapley Additive exPlanations). Use this skill when explaining machine learning model predictions, computing feature importance, generating SHAP plots (waterfall, beeswarm, bar, scatter, force, heatmap), debugging models, analyzing model bias or fairness, comparing models, or implementing explainable AI. Works with tree-based models (XGBoost, LightGBM, Random Forest), deep learning (TensorFlow, PyTorch), linear models, and any black-box model
Pydeseq2
Differential gene expression analysis (Python DESeq2). Identify DE genes from bulk RNA-seq counts, Wald tests, FDR correction, volcano/MA plots, for RNA-seq analysis.
Query Writing
For writing and executing SQL queries - from simple single-table queries to complex multi-table JOINs and aggregations
Pydeseq2
Differential gene expression analysis (Python DESeq2). Identify DE genes from bulk RNA-seq counts, Wald tests, FDR correction, volcano/MA plots, for RNA-seq analysis.
Scientific Visualization
Meta-skill for publication-ready figures. Use when creating journal submission figures requiring multi-panel layouts, significance annotations, error bars, colorblind-safe palettes, and specific journal formatting (Nature, Science, Cell). Orchestrates matplotlib/seaborn/plotly with publication styles. For quick exploration use seaborn or plotly directly.
