Skill UI

This guide provides an in-depth breakdown of the academic research paper review cycle, using top-tier database conferences (like SIGMOD) as a case study. It covers the double-anonymous review process, the author feedback phase, interpreting the Accept/Reject/Revise verdicts, and navigating the post-decision revision window and embargo rules. Essential knowledge for authors preparing submissions to top-tier conference proceedings.

This expert, interactive assistant provides comprehensive troubleshooting for complex issues encountered with Claude Code. It systematically scans the user's environment, checks global and project configurations, and cross-references symptoms against a deep knowledge base to pinpoint root causes and provide actionable, step-by-step solutions. Ideal for resolving integration errors, permission issues, or unexpected behavior.

This tool tests your deep understanding of code you have recently written or reviewed. It generates structured, multi-level questions (Recall, Understanding, Application, Analysis, Synthesis) based on the provided code. Users can focus the quiz on specific areas like error handling, performance, or security, making it an excellent mechanism for continuous learning and solidifying technical knowledge.

A skill that models AI educator Baoyu's approach to creating accessible AI content, systematic prompt engineering teaching (Level 1-10), tool reviews, open-source sharing, and daily knowledge updates. Ideal for writing tutorials, translating tech articles, and building AI knowledge bases without hype or anxiety.

Converts books, documentation folders, and source collections (PDF, EPUB, DOCX, HTML, Markdown, RST, etc.) into structured agent skills. Extracts named frameworks, principles, techniques, and anti-patterns into a master SKILL.md plus chapter files, glossary, patterns, and a decision cheatsheet. Ideal for turning internal docs or standards into reusable knowledge bases or packaging compiled skills as plugins.

Evidence-first deep reading skill. Extracts claims, evidence, assumptions, and counterarguments from books, articles, PDFs, and document sets; builds argument trees, evidence ledgers, and knowledge maps; supports Feynman-based learning and recall. Ideal for in-depth comprehension and durable learning.

A comprehensive guide for creating and maintaining an atomic, index-driven knowledge base (KB) using Markdown. This method enables AI agents to bypass traditional vector search limitations by reading a central index file (INDEX.md) and opening only the most relevant, highly signaled notes, drastically improving context efficiency.

This agent is an expert legal assistant focused exclusively on Chilean law, covering labor, civil, penal, and commercial codes. It provides precise, technical answers to legal inquiries based on the model's knowledge, strictly citing relevant laws, articles, and linking to official sources (BCN). Crucially, it operates without a live database connection and always issues a professional disclaimer, advising users to verify all information with official legal counsel.

A comprehensive knowledge base covering the theoretical fundamentals and advanced algorithms of Deep Reinforcement Learning (Deep RL). It details core concepts like Bellman equations, policy gradients, and the trade-offs between policy optimization and Q-learning. The guide analyzes leading algorithms such as PPO, SAC, TRPO, and DDPG, and provides rigorous best practices for debugging and running scientifically sound RL experiments.