Discover Agent Skills for data science & ml. Browse 61 skills for Claude, ChatGPT & Codex.
Analyzes and implements Hopf bifurcations to create limit cycles from equilibrium points in complex dynamical systems.
Implements topological transport and harmonic centrality gadgets with GF(3) conservation for advanced mathematical and linguistic data modeling.
Analyzes conversation threads and concept networks using relational ACSet patterns and HyJAX structures.
Integrates deterministic color generation with bisimulation game semantics and GF(3) conservation verification.
Integrates local LLM inference via Ollama to reduce API costs and enhance data privacy during development and CI/CD pipelines.
Coordinates multiple specialized AI agents using a central supervisor pattern within LangGraph workflows.
Guides R developers in choosing and implementing the optimal OOP system, including S7, S3, S4, and vctrs.
Integrates Claude with the OMERO platform to manage, analyze, and automate bioimaging data workflows using the Python API.
Implements and explores presheaf toposes as contravariant set-valued functors for categorical logic and structural data modeling.
Provides programmatic access to over 40 bioinformatics web services for biological data retrieval, identifier mapping, and pathway analysis.
Implements compositional string diagrams and operadic structures for categorical computing and active inference.
Validates the integrity and quality of AI evaluation datasets through schema enforcement, duplicate detection, and coverage analysis.
Extracts and verifies information deltas between Claude.ai conversation exports using ACSets morphisms and bisimulation verification.
Models and analyzes interacting dynamical systems using algebraic structures and GF(3) conservation principles.
Implements and analyzes agreement protocols for multi-agent systems using dynamical systems theory and triadic composition.
Verifies that machine learning models correctly respect intended symmetries through systematic numerical tests and debugging guidance.
Provides structured frameworks and systematic workflows for Test-Driven Development (TDD), data exploration, and statistical modeling.
Establishes objective statistical baselines for predictions and projects by anchoring them in historical reality and the 'Outside View.'
Implements reinforcement learning workflows using Stable Baselines3 for training agents, creating environments, and optimizing deep RL models.
Detects and mitigates cognitive biases to improve decision-making, forecasting accuracy, and intellectual honesty.
Models and analyzes concurrent systems through Petri net logic, token flow dynamics, and categorical foundations.
Generates visual bifurcation diagrams to analyze parameter-dependent transitions in dynamical systems.
Optimizes LLM performance by implementing token-efficient context management strategies for AI agents and tools.
Analyzes complex dynamical systems and strange attractors with sensitive dependence on initial conditions.
Calculates time averages of observables along trajectories to analyze qualitative behavior and stability in dynamical systems.
Implements a 3×3×3 matrix execution framework using the TiDAR pattern with GF(3) conservation invariants.
Facilitates the research, modeling, and implementation of complex artificial life systems, from cellular automata to evolutionary dynamics.
Systematically evaluates research papers and scholarly work using the peer-reviewed ScholarEval framework for soundness and contribution.
Accesses the NIH Metabolomics Workbench to query metabolite structures, study metadata, and standardized chemical nomenclature for biomarker discovery.
Facilitates collaborative research ideation through hypothesis generation, interdisciplinary exploration, and systematic challenge of scientific assumptions.
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