Design of Experiments skill for systematic optimization of nanomaterial synthesis and processing
Author custom amq-squad roles that are not in the built-in persona catalog, then wire them into a team.
In-depth Kaggle competition data analysis workflow. Use for exploratory data analysis (EDA), data preprocessing, feature engineering, statistical analysis, and comprehensive…
Expert-level data science, analytics, visualization, and statistical modeling
Use when planning or reporting the analysis for an American Educational Research Journal (AERJ) manuscript — multilevel/HLM and growth models, IRT/measurement, quasi-experimental…
Expert data analyst specializing in business intelligence, data visualization, and statistical analysis.
Expert data scientist specializing in statistical analysis, machine learning, and business insights. Masters exploratory data analysis, predictive modeling, and data storytelling…
Architect and ship a complete multi-agent backend system on AgentField from a one-line user request. Use when the user asks to build, scaffold, design, or ship an agent system,…
AI Agent-driven Kaggle competition workflow. Learn from real competition experience: score stabilization patterns, submission troubleshooting, kernel workflows, GPU task…
Use when evaluating the model and analyzing results for an Agricultural Systems (AgSy) manuscript so it survives expert systems review — independent model evaluation (observed vs.
Perform comprehensive data analysis, statistical modeling, and data visualization by writing and executing self-contained Python scripts.
Perform comprehensive data analysis, statistical modeling, and data visualization by writing and executing self-contained Python scripts.
End-to-end data science and ML engineering workflows: problem framing, data/EDA, feature engineering (feature stores), modelling, evaluation/reporting, plus SQL transformations…
Get personalized academic paper recommendations. Activate whenever the user asks for paper recommendations — explicit command (/aminer-dp) or natural language (e.g.
Use when running and reporting the statistical analysis for an Academy of Management Journal (AMJ) manuscript — measurement validity, common-method bias, the right estimator (HLM,…
Use when the research design and method are the bottleneck for an Academy of Management Journal (AMJ) manuscript — matching design (archival, survey, experiment, multi-method,…
Use when executing and reporting the analysis for an American Political Science Review (APSR) manuscript so it survives expert, double-anonymous review — honest uncertainty,…
Expert knowledge for Azure Data Science Virtual Machines development including troubleshooting, decision making, architecture & design patterns, security, configuration,…
Use when running and reporting the analysis for a Contemporary Accounting Research (CAR) manuscript — the right estimator for archival/capital-markets, experimental, or…
Use when the research design and identification are the bottleneck for a Contemporary Accounting Research (CAR) manuscript — choosing and defending an archival, experimental,…
Use when building the exhibits of a Contemporary Accounting Research (CAR) manuscript — descriptive/correlation/results tables for archival work, experimental cell-means and ANOVA…
Build apps with the Claude API or Anthropic SDK. TRIGGER when: code imports `anthropic`/`@anthropic-ai/sdk`/`claude_agent_sdk`, or user asks to use Claude API, Anthropic SDKs, or…
Use when starting technical work requiring structured approach - writing tests before code (TDD), planning data exploration (EDA), designing statistical analysis, clarifying…
Use when executing and reporting the analysis for a Conservation Biology manuscript so it survives expert, double-blind review — appropriate ecological/statistical models, honest…
Use when when deploying a multi-component research application (e.g., MAGMa's four subproject services) as containerized microservices that need to communicate…
Search the web using Brave Search API. Use for research, current events, finding information online, fact-checking, or when you need to look something up.
Analyze datasets to extract insights, identify patterns, and generate reports. Use when exploring data, creating visualizations, or performing statistical analysis.
Turn raw data into decisions with statistical rigor, proper methodology, and awareness of analyti。Use when 需要数据分析、报表生成、统计洞察、数据可视化时使用。不适用于实时流数据处理。适用于独立开发者、企业团队和自动化工作流场景。
Data collection, analysis, and interpretation for scientific inquiry. Covers measurement and units, data recording and organization, descriptive and inferential statistics,…
SQL for data analysis with exploratory analysis, advanced aggregations, statistical functions, outlier detection, and business insights. 50+ real-world analytics queries.
Comprehensive data analysis expertise covering statistical analysis, data visualization, exploratory data analysis, hypothesis testing, machine learning, data cleaning, and data…
Fact-checking and source verification workflow for research documents. Launches parallel fact-checkers, aggregates findings, applies corrections systematically.
Systematic data validation, error detection, cross-source reconciliation, and query correctness checking for analytical work.
Data science and analytics expertise for statistical analysis, machine learning pipelines, data governance, business intelligence, predictive modeling, and analytics strategy.
Bundle of 50+ granular skills for Python Data Stack, SQL, Amplitude, and data engineering patterns.
Statistical analysis, ML, NLP, time series forecasting, network analysis for political intelligence data
Documentation of available data science libraries (scipy, numpy, pandas, sklearn) and best practices for statistical analysis, regression modeling, and organizing analysis…
Expert data scientist for advanced analytics, machine learning, and statistical modeling. Handles complex data analysis, predictive modeling, and business intelligence.
Use this agent when you need to analyze data patterns, build predictive models, or extract statistical insights from datasets.
Data scientist senior. EDA, ML, deep learning, NLP, MLOps, experimentación, deployment.
Operate as a product data scientist who frames falsifiable hypotheses, analyzes experiments, and reports results without flattering the launch.
Expert in statistical analysis, predictive modeling, machine learning, and data storytelling to drive business insights.
Use only when the user explicitly requests strict code-cell-only output for a Jupyter or undergraduate data-science task, or when an ITX2007 assignment requires that format.
Use for explicit undergraduate data-science teaching, assignment guidance, concept clarification, method selection, or output interpretation.
Use when executing and reporting the analysis for an Environmental Science & Technology (ES&T) manuscript so it survives expert review — analytical QA/QC, honest uncertainty,…
Statistical analysis and reporting for experimental datasets; use when you need to interpret experimental results, test significance (t-tests/ANOVA), or generate reproducible…
Use when executing and reporting the statistical analysis for a Field Crops Research (FCR) manuscript — mixed models for multi-environment and blocked/split-plot designs,…
Use when executing and reporting the analysis for a Global Change Biology (GCB) manuscript — mixed/hierarchical models, time-series and spatial analysis, meta-analysis, and model…
Use when a Games and Economic Behavior (GEB) manuscript involves experimental data or numerical illustration — analyzing strategic-game experiments and building verified worked…
Designs a tailored multi-product agentic data science architecture on Google Cloud that incorporates opinionated best practices.
Universal self-review protocol for all Rune teammates. Adapts checklist per agent role (worker, fixer, reviewer, researcher, forger, aggregator).
Use when when you have tandem mass spectra data and need to predict a binary molecular property (e.g., presence of a functional group like a sulfo group) while maintaining full…
Use when executing and reporting the analysis for an Information Systems Research (ISR) manuscript — identification and validity for empirical work, proof discipline and…
Use when choosing and stress-testing the research design for an Information Systems Research (ISR) manuscript — matching the genre (behavioral empirical, analytical-economic…
Use when designing the exhibits for an Information Systems Research (ISR) manuscript — correlation/measurement tables, estimation results, model/equilibrium figures,…
Use when building or refining the mechanism for an Information Systems Research (ISR) manuscript — deriving behavioral hypotheses for empirical work or analytical…
Use when turning empirical results into an explicit contribution to accounting knowledge for a Journal of Accounting Research (JAR) manuscript — stating what we now know about how…
Use when running and reporting the empirical-archival analysis for a Journal of Accounting Research (JAR) manuscript — standard-error clustering, endogeneity execution, construct…
Use when the research design and identification strategy are the bottleneck for a Journal of Accounting Research (JAR) manuscript — choosing the setting, source of identi — from…
Use when building the economic mechanism and deriving signed, falsifiable predictions for a Journal of Accounting Research (JAR) manuscript — grounding hypotheses in information…