Skill UI

A comprehensive guide for building responsive UIs in Flutter. It promotes using fundamental layout widgets like Column, Row, Expanded, and Flexible for flexible composition, advising developers to build layouts from the constraint system outward. Learn best practices for space distribution, content flow management, and avoiding rigid, hardcoded coordinates for robust, adaptive designs.

This skill generates high-quality images, textures, icons, and visual assets from text prompts using advanced AI models. It supports multiple providers, including OpenAI (DALL-E) and Google Gemini, offering flexibility in quality and speed. Ideal for rapid prototyping, game asset creation, artwork, and visual mockups across various projects. Requires configuration with an API key.

gget is a versatile CLI and Python package designed for rapid, reproducible bioinformatics searches across major genomic reference databases (e.g., Ensembl, UniProt). It allows users to quickly query gene metadata, perform initial BLAST/BLAT style alignments, and explore associated pathways, cancer, or disease modules. It is ideal for initial data exploration and generating reproducible evidence logs before building complex, full-scale local pipelines.

Provides a comprehensive, step-by-step workflow for conducting rigorous literature reviews across academic, biomedical, and technical domains. It guides users through defining research questions (PICO), developing systematic search protocols, evidence logging, source screening, structured data extraction, and synthesizing findings to build high-quality, reproducible review reports.

Polars is a lightning-fast DataFrame library designed for efficient, memory-efficient data processing in Python and Rust. Built upon Apache Arrow, it supports lazy evaluation and parallel execution, making it ideal for ETL pipelines, large-scale data transformations, and scenarios where standard Pandas performance is insufficient. It excels at handling datasets up to 100GB that fit within available RAM.

This skill provides a comprehensive, reproducible rubric for evaluating scholarly and scientific work. It covers nine critical dimensions—including problem statement, methodology, data evidence, analysis rigor, and citation quality—making it ideal for reviewing research papers, grant proposals, literature reviews, and academic theses. Use it to provide structured, actionable, and professional feedback to enhance scholarly output.

Statsmodels is Python's premier library for rigorous statistical modeling. It provides comprehensive tools for estimation, inference, and diagnostics across a wide range of statistical methods. Use this skill for advanced analysis, including linear regression (OLS, WLS), generalized linear models (Logistic, Poisson), and complex time series forecasting (ARIMA). Ideal for econometric studies and producing publication-ready results.

SymPy is a powerful Python library designed for symbolic mathematics. Unlike numerical solvers, it performs exact calculations using mathematical symbols, allowing users to model and solve complex problems across various domains. Core capabilities include symbolic calculus (derivatives, integrals, limits), advanced algebra, solving systems of equations, linear algebra (determinants, eigenvalues), and specialized modules for physics and number theory. It can also generate executable code in languages like C and Fortran, making it invaluable for academic research and scientific computing.

This skill helps developers and QA engineers transform vague, intermittent, or poorly documented bug reports into a minimal, reproducible, and evidence-backed brief. It guides the user to isolate the exact failure conditions, separate expected outcomes from actual errors, and reduce the issue to the smallest safe failing fixture, ensuring diagnosis occurs before premature repair.

This skill helps diagnose the health and gather comprehensive status reports for the Ruflo system, including the MCP server and active agents. It provides a read-only workflow to check system status or, when explicitly requested, performs a non-destructive repair and reports the changes.

This skill reports the overall integration and configuration status of the AGNTCY ecosystem, covering several critical areas. It verifies package availability (TS/Rust), determines the active communication transport (local or SLIM), checks the CASA enforcement state, and reports on IOC coordination and identity observability features. Use when troubleshooting or confirming system setup.

This utility packages multiple independent FHIR R4 resources into a single, valid Transaction Bundle. It automatically handles deterministic URN UUID generation and resolves internal cross-references, making the bundle immediately ready for POSTing to a FHIR server. This is crucial for maintaining data integrity and interoperability when submitting multiple related clinical resources.