Data Science & ML Agent Skills

Prompt Analyzer & Insights

Analyzes generated prompts to provide deep insights into element usage, quality comparisons, and style-based recommendations.

Synapse Plugin Execution

Facilitates the programmatic execution and discovery of Synapse plugins across local and distributed environments.

Vercel AI SDK Assistant

Simplifies the development of AI-powered features and autonomous agents using the Vercel AI SDK.

Python Data Grouping Patterns

Optimizes Python data structures using defaultdict for efficient grouping, adjacency lists, and nested dictionary management.

Agent Creator

Architects specialized, production-ready AI agents using a rigorous 4-phase methodology and evidence-based prompting techniques.

Counter Frequency Patterns

Implements efficient counting and frequency analysis patterns using Python's collections.Counter for data processing and distribution analysis.

Constraint Satisfaction Solver

Solves complex logic puzzles and scheduling problems using Peter Norvig's propagate-then-search algorithmic pattern.

AI Prompt Optimizer

Refines and compresses LLM prompts to minimize token usage and maximize response quality.

State-Driven Class Patterns

Encapsulates complex state management into robust class structures to handle transitions, backtracking, and algorithmic branching.

Frontier-Based Graph Exploration

Implements flexible graph and tree traversal patterns with configurable DFS, BFS, and randomized exploration strategies.

Stable Matching & Gale-Shapley

Implements the Gale-Shapley algorithm to solve stable matching problems for two-sided markets like residency and admissions.

Graceful Failure Coding Pattern

Implements the Norvig pattern of returning sentinel values instead of exceptions for natural algorithmic failures.

Side-by-Side Comparison Patterns

Visualizes code changes, algorithm results, and data states by displaying multiple outputs in parallel columns.

Local LLM Management

Manages local Ollama LLM models for development, testing, and VRAM optimization within Claude Code workflows.

Local Search Optimizer

Solves NP-hard optimization problems using greedy construction and iterative local improvement patterns.

Lattice Spatial-Collective

Implements a decentralized context-sharing protocol for multi-agent systems using cryptographic sharding and Byzantine fault tolerance.

Norvig Sparse Set Pattern

Implements memory-efficient sparse data structures using Python sets for infinite grids and large coordinate spaces.

Propagate-Then-Search Logic Pattern

Optimizes constraint satisfaction problem-solving by eliminating impossibilities through inference before initiating recursive search operations.

Priority Queue Implementation Patterns

Implements high-performance priority queues for pathfinding, scheduling, and stream processing using efficient heap-based structures.

Python NamedTuple Records

Implements immutable, memory-efficient data structures using Python's namedtuple for cleaner and more readable code.

Python Operator Overloading DSL

Enables the creation of expressive domain-specific languages in Python by overloading arithmetic and logical operators.

Statistical Data Reporting

Generates human-readable, aligned tables and statistical summaries for reporting results and data comparisons.

Python Memoization Patterns

Optimizes Python functions by implementing memoization and dynamic programming patterns to eliminate redundant recursive computations.

Convex Hull & Geometric Patterns

Implements efficient computational geometry algorithms for calculating convex hulls, point enclosures, and polygon operations.

Symbolic Expression Tree Builder

Implements symbolic computation patterns and Abstract Syntax Trees for mathematical modeling and code transformation.

Text Data Extraction Patterns

Extracts structured data, numbers, and identifiers from unstructured text using optimized regex patterns and Norvig-inspired utilities.

Python Lazy Generator Patterns

Implements memory-efficient data processing using Python generators and lazy evaluation patterns.

Iterate with Itertools

Implements memory-efficient combinatorial iteration patterns in Python using the itertools library.

Probability & Counting Patterns

Implements exact probability calculations and combinatorial counting patterns using a functional, Norvig-inspired approach.

Professional Excel & Financial Modeling

Creates, edits, and analyzes professional spreadsheets with industry-standard formatting, dynamic formulas, and automated recalculation.