Skill UI

This guide helps researchers structure rigorous, mechanism-driven theoretical arguments for top-tier academic journals. It teaches users how to move beyond mere correlation by establishing a clear causal logic, identifying the underlying mechanism, and integrating established strategic lenses (e.g., RBV, Dynamic Capabilities) to build testable hypotheses.

A comprehensive guide designed for the late-stage polishing of academic manuscripts, specifically targeting submissions to top-tier journals. It focuses on enhancing clarity, improving argument flow, adhering to strict academic house conventions (such as dual abstracts and APA style), and refining prose. This skill ensures the research contribution is clearly articulated and immediately visible to the reader, optimizing the structure and polish of the final paper.

A comprehensive guide for structuring the 'Related Work' section for top-tier HCI conferences (e.g., UIST). This document emphasizes that the section must function as a novelty proof, not a literature survey. It teaches authors to organize content by capability delta, utilize detailed comparison tables, and trace three critical lineages: technique, toolkit, and commercial practice, ensuring the work's unique contribution is clearly established.

A comprehensive workflow guide for managing the entire academic research cycle of a major conference, such as the Web Conference. It details key milestones, backward planning strategies from abstract deadlines, fallback options (Short Papers, Web4Good), and capacity planning tips to ensure timely and successful submission and publication.

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.

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 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 adapter provides professional AI audio generation capabilities, supporting voiceovers, music, and sound effects through OpenRouter. Designed for OpenSquilla compatibility, it handles complex API contracts, including streaming data and outputting browser-playable WAV files, making it ideal for web content enrichment.

This skill acts as a comprehensive map for developing clinical and biomedical NLP pipelines using OpenMed. OpenMed is a local-first Python library that performs named-entity recognition (NER), protected health information (PHI) de-identification, and FHIR export, all running fully on-device without cloud calls. Use this guide when starting a new clinical text project, needing to select the appropriate capability (e.g., zero-shot NER, auditing, or FHIR conversion), or requiring an entry point for the core OpenMed features.

A specialized deep-dive skill for analyzing container-to-host escape vulnerabilities. This tool is used after a sandbox orchestrator establishes initial assumptions, focusing on mapping isolation boundaries (namespaces, cgroups, seccomp, capabilities). It helps prove boundary crossings, identify minimal exploit primitives, and determine if an exploit can break out of the container context to the host kernel.

This specialized skill is designed for deep forensic analysis of compromised Linux environments, specifically tracing the sequence of credential usage (tokens, keys, service accounts) that leads to lateral movement or privilege escalation. It helps map the decisive path from a recovered artifact to an accepted replay mechanism, identifying the exact trust edge or capability abuse responsible for the host-to-host pivot.