Skill UI

Provides guidance on organizing and writing focused XUnit unit tests, covering project setup, fact/theory patterns, assertions, mocking, and data-driven testing for reliable .NET test suites.

Provides paragraph-level structural blueprints and venue-specific checklists for 10–12 page systems conference submissions (OSDI/SOSP/ASPLOS/NSDI/EuroSys), covering writing patterns, reviewer guidance, LaTeX templates, and deadline tracking.

Provides comprehensive guidance for upgrading and migrating between different versions of the Grammarly API. This skill covers version detection, critical schema changes (e.g., score breakdown), migration checklists, and implementing robust rollback strategies for writing analysis, AI detection, and plagiarism checking.

This guide provides comprehensive documentation and best practices for interacting with the Veeva Vault platform. It covers REST API usage, writing effective VQL (Vault Query Language) queries, and utilizing the VAPIL Java SDK. It also details common error handling procedures and addresses rate limit guidance for developers working in life sciences and CRM environments.

Provides expert guidance for building professional, scalable, and brand-aligned design systems. It covers foundational tokens (color, typography, spacing), component anatomy, accessibility standards (WCAG 2.2 AA), and structured content writing rules, ensuring design consistency and high quality for large-scale enterprise products.

A powerful PreToolUse hook designed to act as a safety net during code writing sessions. It automatically scans both file paths and content for 12 common security anti-patterns, including SQL injection, XSS, command injection (Node.js/Python), and unsafe deserialization. It blocks the writing operation and provides immediate warnings, ensuring adherence to secure coding practices when handling sensitive code like authentication or payment logic.

Skills and references for writing, debugging, and optimizing DAX in semantic models. Provides a tiered framework, engine internals, patterns, and model optimization strategies, along with trace capture and performance profiling guidance for local and remote models.

Provides comprehensive style guidance for writing and refining scientific manuscripts for Acta Automatica Sinica (AAS). This guide covers the structure of the reporting abstract (Purpose/Method/Result/Conclusion), handling bilingual requirements, formatting rules for equations, figures, and adherence to national standards for units and citations (GB/T 7714). Ideal for papers in control theory, robotics, and intelligent systems.

This skill provides architectural guidance for writing high-level academic history articles, specifically tailored for the American Historical Review (AHR). It helps writers ensure that the narrative development and the core historical argument are seamlessly interwoven, adhering to strict length and scholarly standards. Use it when outlining complex drafts or restructuring material that feels disjointed.

This skill provides comprehensive guidance for authors writing critical, authoritative reviews targeting Coordination Chemistry Reviews (CCR). It details the required scope, mandatory synthesis level, and specific house style expectations concerning advanced topics such as MOFs, coordination catalysis, and bioinorganic chemistry. Use it to assess topic fit, structure a manuscript, and re-frame work for submission to this specialized journal.

This skill provides detailed guidance for authors proposing or writing a high-level, conceptual review for Nature Reviews Materials. It outlines the journal's unique standards, focusing on conceptual synthesis, establishing unifying design principles, and providing an expert map for cross-disciplinary audiences in materials science and engineering. It covers scope, evidence bar, house style, and the crucial pre-submission collaboration process.

This guide outlines the rigorous standards for writing top-tier distributed systems conference papers. It details the mandatory narrative arc—moving from an operational pain point to a named design principle—and emphasizes that every claim must be supported by precise, measured evidence (e.g., percentiles and specific workloads) rather than relying on superlatives or vague adjectives. It also provides guidance on structuring the argument, budgeting page space, and designing figures as core evidence.