data science & ml向けのClaudeスキルを発見してください。61個のスキルを閲覧し、AIワークフローに最適な機能を見つけましょう。
Implements the Symmetry Theory of Valence (STV) to analyze, map, and optimize phenomenal states through topological mathematical models.
Orchestrates a polyglot environment for social network analysis and multimedia processing using Clojure, Julia, and DuckDB.
Analyzes conversation threads and concept networks using advanced relational thinking and ACSet modeling.
Extracts and verifies information deltas between Claude.ai conversation exports using categorical morphisms and bisimulation.
Validates triadic color systems by comparing predicted efference copies against observed color streams to minimize system error.
Analyzes dynamical systems using partial derivative matrices to linearize complex flows and evaluate local stability.
Transforms formal proofs into interactive game-theoretic strategies using Gödel’s Dialectica interpretation.
Automates the creation of high-quality training datasets from Claude conversation history and local skill files to fine-tune LLMs using MLX on Apple Silicon.
Navigates complex conceptual possibility spaces using type-theoretic bridge transitions and ordered locale structures.
Analyzes and implements convergence patterns in coupled dynamical systems for complex mathematical modeling.
Analyzes and models Hopf bifurcations to identify transitions from equilibrium to limit cycles in complex dynamical systems.
Automates professional spreadsheet creation, data analysis, and financial modeling with a focus on formula-driven logic.
Analyzes and deconstructs linguistic puns into multiple semantic and phonetic parses using algebraic and topological structures.
Implements Fixed-Parameter Tractable (FPT) algorithms using sheaves on tree decompositions for compositional data structures.
Models and analyzes interacting dynamical systems using topological and algebraic frameworks for complex system simulation.
Integrates deterministic color generation with bisimulation game semantics for verifiable GF(3) conservation logic.
Unifies mathematical topos-theoretic resources, category theory tools, and cognitive modeling frameworks across the filesystem.
Analyzes and models the paths of solutions through phase space within dynamical systems.
Facilitates structured generation and composition of complex multi-input operations using colored operads and category theory principles.
Transfers and synthesizes knowledge across domains using propagator-based networks to exploit structural isomorphisms.
Implements point-free topology and triadic GF(3) logic to manage causal structures and deterministic parallel execution for MCP servers.
Detects and analyzes qualitative state transitions in dynamical systems using Hopf bifurcation detection and GF(3) phase portraits.
Facilitates Galois adjunctions between local agent operations and global cognitive category theory using Mazzola’s mathematical music structures.
Bridges representation space and execution time to optimize AI model performance through mathematical spectral analysis.
Implements and analyzes agreement protocols within multi-agent dynamical systems using algebraic dynamics and topological principles.
Analyzes and identifies sets within dynamical systems that are preserved by the flow of differential equations and manifolds.
Analyzes invariant sets and long-term trajectory behaviors within dynamical systems to model stable states and system evolution.
Analyzes symmetric bifurcations and symmetry-breaking patterns in complex dynamical systems and differential equations.
Verifies that neural network training trajectories have reached theoretical Gibbs equilibrium using Fokker-Planck equations.
Provides unified access to topos-theoretic resources, mathematical music theory, and categorical database structures for advanced AI reasoning.
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