Discover Agent Skills for data science & ml. Browse 61 skills for Claude, ChatGPT & Codex.
Calculates statistical power and determines optimal sample sizes to ensure experimental designs meet rigorous scientific and funding standards.
Linearizes complex nonlinear dynamics using Koopman operator theory to enable predictive modeling through observable space.
Linearizes nonlinear dynamical systems using Koopman operator theory to generate predictive models from observable data.
Analyzes and models complex dynamical systems using ergodicity principles where time averages equate to space averages.
Analyzes and traces the flow of ideas, topics, and behaviors across complex social and interperspectival networks.
Analyzes social network dynamics to trace idea adoption, influence flow, and interperspectival relationships.
Coordinates multi-agent systems and state transitions using GF(3) Galois Field conservation principles.
Facilitates complex system modeling through a triadic balance of categorical structure, cybernetic agency, and phenomenological observation.
Implements a triadic framework balancing category theory, cybernetic agency, and phenomenological observation for complex system modeling.
Configures AI model selection, cost estimates, and batch processing strategies for qualitative research workflows.
Performs advanced geodesic calculations and Riemannian manifold operations for geospatial navigation and spherical geometry.
Performs vector similarity search and hierarchical clustering for agent skills using P-adic ultrametrics and MLX-powered embeddings.
Navigates complex research contradictions and integrates conflicting data patterns using contemplative reasoning frameworks.
Initializes qualitative research environments with structured epistemic foundations and standardized folder hierarchies.
Integrates advanced topological graph theory and bicomodule structures into Claude for complex scientific computing and algebraic modeling.
Optimizes interaction sequences using information theory to maximize learning efficiency and pattern recognition.
Provides high-performance LLVM-level automatic differentiation for Julia code on CPU and GPU architectures.
Facilitates structured, step-by-step thinking for complex analytical decisions and theoretical framework construction using the Sequential Thinking MCP.
Optimizes interaction sequences using information theory and active inference to maximize learning efficiency and information gain.
Performs high-performance geospatial analysis, H3 hexagonal indexing, and PostGIS-compatible spatial SQL queries using DuckDB.
Orchestrates systematic document coding, progress tracking, and audit trail generation for qualitative research projects.
Converts complex PDFs, academic papers, and tables into structured formats using intelligent tool selection and VLM-based parsing.
Bridges Scholze-Clausen condensed mathematics and analytic stacks to sheaf neural networks via 6-functor formalisms.
Converts audio recordings, PDFs, and diverse document formats into structured markdown for qualitative research and AI-assisted analysis.
Enforces GF(3) color conservation and deterministic traversal across complex data navigator compositions.
Facilitates deep analytical reasoning and navigates theoretical paradoxes in qualitative research using systematic thinking and dialectical wisdom.
Constructs high-fidelity psychological models from interaction patterns to predict intellectual trajectories and maintain authentic voice consistency.
Builds and validates high-fidelity psychological models to predict behaviors and generate authentic cognitive responses matching a subject's unique patterns.
Facilitates reflexive qualitative data analysis through dialogical questioning and multi-stage visible reasoning.
Builds, trains, and validates high-fidelity psychological models to predict and generate authentic cognitive responses.
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