3. Data, Science & AI

Provides CLI utilities for creating, altering, and validating Snowflake semantic views with DDL validation and setup guidance.

Provides tools for designing and managing relational (SQL) and non-relational (NoSQL) databases with efficient data handling patterns.

Provides SQL patterns for efficient database querying and schema design.

Transforms vague user queries into structured Japanese YAML prompts for AI interactions, using clarifying questions and examples.

Manages research paper knowledge graphs, enabling SPARQL queries, metadata addition, and claim relationship recording (e.g., extends, refutes).

Converts academic trading research into executable NautilusTrader strategy specifications, reducing token count by 70%.

A system employing three AI models for parallel analysis and consensus judgment in debate scenarios.

Analyzes command, skill, and agent usage frequency to generate reports and identify unused items for optimization.

Guides users in creating, configuring, and utilizing Antigravity subagents and the Task tool for specialized agent workflows within an AI framework.

Tool for creating, altering, and validating Snowflake semantic views using Snowflake CLI, including DDL validation and setup guidance.

Enables efficient data manipulation, lazy evaluation, and performance optimization for data pipelines using Polars DataFrame operations.

Generates data visualizations including plots, charts, and heatmaps using Python libraries for statistical graphics and publication-ready figures.

Executes and evaluates Julia code for scientific computing, data analysis, and package development with optimized REPL session practices.

Enables advanced data visualization in R using ggplot2 4.0+ features, including theme customization, scale improvements, and plot styling.

Standardizes data preprocessing and model construction for R modeling packages, supporting formula, data frame, matrix, and recipe interfaces.

Guides correct column reference handling in tidyverse functions (dplyr, ggplot2) using tidy evaluation patterns to avoid common pitfalls.

Analyzes images, videos, and web content using Gemini AI, providing multimodal capabilities and web search beyond Claude's native text-based functions.

Analyzes personal financial transaction CSV data to calculate account totals, generate detailed breakdowns, and support multiple account types including banking and crypto.

Retrieves past session context including user preferences, discussions, and workflows to inform current responses.

Guides statistical experiment design, execution, and interpretation to ensure validity and prevent false positives using industry frameworks.

Contextual overview of R tidymodels ecosystem for machine learning, covering workflows, recipes, tuning, and model comparison.

Retrieves YouTube video transcripts, captions, or subtitles from a specified video URL upon user request.

Manages agent memory for Serena projects, enabling context retention across sessions and distinguishing documentation from agent-specific memories.

Manages Neon PostgreSQL databases with capabilities for project listing, schema inspection, and query execution.