Skill UI

Exa MCP provides advanced neural search capabilities across the web, specialized code repositories (like GitHub), and corporate/personnel databases. Use it for deep background research, finding the latest news, debugging complex code patterns, or conducting thorough market and competitor analysis.

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.

Matplotlib is the foundational Python library for creating static, animated, and high-quality visualizations. This comprehensive skill guide covers everything from basic line plots and scatter graphs to advanced concepts like multi-subplot layouts, heatmaps, and 3D visualization. It details both the convenient pyplot interface and the powerful object-oriented API, ensuring you can generate publication-ready charts with professional customization.

NetworkX is a powerful Python package designed for creating, manipulating, and analyzing complex networks and graphs. It supports various graph types (Directed, Undirected, MultiGraphs) and provides extensive functionality for graph algorithms, including shortest path calculation, centrality measures (like PageRank), community detection, and connectivity checks. Users can generate synthetic networks, read/write data from multiple formats (GraphML, CSV, Pandas), and visualize results using Matplotlib. Ideal for social network analysis, biological research, and system modeling.

Scanpy is a powerful, scalable Python toolkit built on AnnData for comprehensive single-cell RNA-seq data analysis. It supports the complete biological workflow, including quality control, normalization, dimensionality reduction (PCA, UMAP, t-SNE), clustering, marker gene identification, and sophisticated cell type annotation, enabling the generation of publication-quality figures.

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.

This core skill is designed for academic publishing, combining deep AI research with structured, professional writing. It guides the creation of manuscripts using IMRAD structure and handles complex citation styles (APA, AMA, etc.). Crucially, it mandates the generation of graphical abstracts and rich technical schematics to ensure the highest level of visual rigor for research papers.

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 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.