Discover Agent Skills for data science & ml. Browse 61 skills for Claude, ChatGPT & Codex.
Automates the creation, editing, and analysis of professional Excel spreadsheets with advanced formula support and financial modeling standards.
Transforms research papers and code repositories into high-quality, reusable AI skills through a multi-agent peer-review process.
Builds robust, production-grade backtesting systems for trading strategies while eliminating common statistical biases.
Calculates comprehensive portfolio risk metrics like VaR, CVaR, and Sharpe ratios to monitor and manage financial exposure.
Master advanced prompt engineering techniques to maximize LLM performance, reliability, and controllability in production.
Implements optimized hybrid search patterns combining vector similarity and keyword matching to enhance RAG system recall.
Implements efficient semantic search and vector database patterns for production-grade retrieval systems.
Builds production-grade Python document-processing systems featuring Docling integration, OCR fallbacks, and editable DOCX generation.
Streamlines academic literature review and research paper discovery with automated prioritization and screening workflows.
Processes and prepares data files for AI agent testing and deployment workflows.
Performs systematic testing of input variables to identify key drivers and assess model risk across finance, engineering, and strategy.
Corrects probability judgments by integrating statistical base rates with case-specific information to avoid common cognitive biases.
Leverages the data flywheel mental model to build compounding competitive advantages through automated machine learning and user-generated signals.
Implements comprehensive evaluation frameworks for LLM applications using automated metrics, human feedback, and benchmarking.
Implements continuous model updates and incremental learning patterns to handle evolving data streams without full retraining.
Predicts market price and quantity changes by analyzing the interaction between producer supply and consumer demand at equilibrium.
Implements sophisticated Retrieval-Augmented Generation architectures to ground AI responses in real-time external knowledge and eliminate hallucinations.
Identifies and mitigates the gambler's fallacy to improve decision-making in probabilistic and high-risk scenarios.
Evaluates research rigor by assessing methodology, statistical validity, and evidence quality using industry-standard frameworks like GRADE and Cochrane.
Implements advanced data resampling and validation strategies using the R tidymodels framework for robust model evaluation.
Implements comprehensive evaluation frameworks for LLM applications using automated metrics, human feedback, and statistical benchmarking.
Systematically evaluates scholarly research, academic papers, and technical proposals using the peer-reviewed ScholarEval framework.
Provides expert guidance and best practices for conducting Matching-Adjusted Indirect Comparisons (MAIC) in biostatistical research.
Facilitates the creation, review, and optimization of Bayesian models using PyMC 5 and ArviZ diagnostics.
Guides the implementation and review of Simulated Treatment Comparisons (STC) using NICE DSU TSD 18 compliant methodologies.
Simplifies the creation and review of Bayesian models using BUGS and JAGS declarative syntax and precision parameterization.
Provides comprehensive Bayesian meta-analysis templates using Stan and JAGS for advanced biostatistical evidence synthesis.
Orchestrates complex social science research and systematic reviews using 24 specialized agents and integrated academic database tools.
Automates the creation, editing, and analysis of professional Excel spreadsheets with advanced formula support and industry-standard financial modeling.
Queries and interprets genetic variant clinical significance data from the NCBI ClinVar database.
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