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。
Validates World Extractable Value (WEV) and topological system states using GF(3) logic and cybernetic reafference loops.
Models and analyzes invariant sets that repel nearby trajectories within complex dynamical systems and topological manifolds.
Automates the creation and management of robust data pipelines using Hamilton DAGs and the FlowerPower framework.
Analyzes the asymptotic behavior of trajectories in dynamical systems to determine long-term qualitative patterns.
Enhances AI reasoning by implementing a two-stage deliberate attention mechanism to filter noise and ensure factual grounding.
Models and verifies state-dependent Markov games using Attributed C-sets and GF(3) conservation laws.
Models and analyzes one-parameter groups of diffeomorphisms generated by vector fields within dynamical systems.
Implements high-performance adaptive learning and memory distillation for AI agents using the AgentDB vector engine.
Analyzes the stability and qualitative behavior of dynamical systems using scalar function trajectories.
Manages the reparameterization of time in flows for complex dynamical systems and topological modeling.
Integrate 9 reinforcement learning algorithms to build self-improving AI agents that learn from experience and optimize behavior autonomously.
Models and analyzes the categorical structure of dynamical systems to evaluate stability and qualitative behavior.
Orchestrates multi-agent AI swarms for parallel task execution and dynamic coordination using the agentic-flow framework.
Facilitates real-time, multi-modal continuous coaching and guidance through LiveKit using dynamic modality selection and symbolic expression processing.
Implements bottom-up fixpoint iteration for recursive Datalog queries using saturation-based evaluation.
Transforms quantum qubit states into expressive musical textures through Bloch sphere sonification and MIDI control.
Implements bidirectional constraint propagation and fixpoint derivation for complex autonomous information networks.
Recovers local structural seeds from global color distributions using Möbius inversion and topological duality.
Analyzes time-series data using scaling theory to identify turbulence regimes, persistence, and long-range dependencies.
Routes complex tasks to specialized subagent triads using GF(3) triadic logic to ensure balanced execution and validation.
Transforms structured data and acsets using category-theoretic graph rewriting techniques like DPO, SPO, and SqPO.
Verifies that neural network training trajectories have reached theoretical Gibbs equilibrium using Fokker-Planck equations.
Analyzes symmetric bifurcations and symmetry-breaking patterns in complex dynamical systems and differential equations.
Analyzes invariant sets and long-term trajectory behaviors within dynamical systems to model stable states and system evolution.
Analyzes and identifies sets within dynamical systems that are preserved by the flow of differential equations and manifolds.
Implements and analyzes agreement protocols within multi-agent dynamical systems using algebraic dynamics and topological principles.
Bridges representation space and execution time to optimize AI model performance through mathematical spectral analysis.
Analyzes and simulates critical opalescence signatures and phase transition dynamics in physical and biological systems.
Facilitates Galois adjunctions between local agent operations and global cognitive category theory using Mazzola’s mathematical music structures.
Detects and analyzes qualitative state transitions in dynamical systems using Hopf bifurcation detection and GF(3) phase portraits.
Scroll for more results...