Skill UI

This comprehensive guide details the ten most common mistakes and anti-patterns encountered when integrating with the Figma REST and Plugin APIs. It covers critical topics such as preventing oversized data fetches, managing rate limits, securing tokens, handling color format conversions, and optimizing data sync using webhooks instead of polling. Essential for code reviews and onboarding. Use when reviewing Figma code, onboarding new developers, or auditing an existing Figma integration.

A specialized mentor designed to guide students through major global standardized examinations (e.g., SAT, ACT, 高考, IB, A-Level, 中考). This coach moves beyond mere content review, focusing intensely on meta-skills such as time management, error analysis, strategic test-taking, and managing pre-exam anxiety. It utilizes proven methodologies like deliberate practice and spaced repetition to help students optimize performance while maintaining mental well-being.

Dedicated skill for quickly understanding a single academic paper using the AlphaXiv platform. It employs a tiered source fallback system: starting with an LLM-optimized overview, progressing to full markdown text, and finally accessing the raw LaTeX source for deep inspection. Ideal when you have a specific arXiv ID or URL, and do not require broad literature reviews.

A comprehensive, step-by-step guide for safely upgrading ClickHouse server versions and the associated Node.js client SDK. This guide covers pre-upgrade checks, reviewing major breaking changes, updating client code (e.g., 'host' to 'url'), performing server backups and updates, and implementing full validation and rollback procedures.

This skill provides a comprehensive framework for conducting high-quality code reviews. It guides developers through checking code across four critical dimensions: Correctness (functional accuracy and edge cases), Maintainability (readability and documentation), Performance (efficiency and resource usage), and Security (input validation and vulnerability management). It also emphasizes providing actionable, constructive, and empathetic feedback.

This guide provides a comprehensive framework for investigating production issues on the Nexu platform using the Datadog Logs API. It details how to query crash events, analyze OpenClaw stderr output, check gateway startup status, and review API request logs (including 5xx errors). It includes best practices for authentication, filtering by pod/time, and parsing raw JSON logs using Python for actionable insights.

A multi-phase workflow designed to guide users through complex problem analysis and solution design. Instead of providing immediate answers, it systematically enforces deep thinking by reviewing the problem's validity, assessing information gaps, performing root cause analysis, and iterating through solution vetting (self-check and final review). Ideal for complex technical troubleshooting, decision-making, or theoretical discussions requiring rigorous methodology.

A comprehensive skill that brings the entire GitHub pull request workflow directly into your terminal. It allows users to view PR status, monitor real-time CI/CD progress, summarize bot comments, and execute merge operations (squash, merge, rebase) without switching to a browser. It consolidates all critical PR information—including file changes and review blockers—into one cohesive view, streamlining the developer workflow and DevOps process.

This guide details the recommended reference architecture and project structure for integrating with the Hex platform. It covers best practices for designing robust data pipelines, including components like orchestration layers (Airflow, Dagster), API clients, and standardized project layouts. Use this when starting new Hex integrations or reviewing complex data workflows.

This skill performs a rigorous, adversarial review of implemented code. It verifies that the task implementation is complete, structurally sound, respects defined boundaries, and aligns perfectly with approved requirements and design specifications. Use it after an implementer finishes work, or before final acceptance, to ensure code quality and architectural integrity.

Conduct comprehensive, systematic literature reviews across biomedical, scientific, and technical domains. This skill facilitates meta-analyses, scoping reviews, and research syntheses by searching multiple academic databases (e.g., PubMed, arXiv). It generates professionally formatted reports (Markdown/PDF) with verified citations and mandates the inclusion of AI-generated scientific schematics (e.g., PRISMA flow diagrams). Ideal for academic research and thesis writing.

A comprehensive, step-by-step guide for safely upgrading the Palantir Foundry SDK. This skill covers version dependency checks, reviewing breaking changes via API changelogs, running integrated unit and integration tests, and implementing robust rollback procedures, ensuring smooth platform migration.