Skill UI

This skill transforms a course syllabus (PDF, DOCX, etc.) into a highly curated, supplementary academic reading list. It parses topics and learning outcomes, calibrates content difficulty based on the target audience (undergraduate, graduate, etc.), and searches academic databases (Consensus) for recent, peer-reviewed papers. The output is a professional .docx file containing summaries, links, and advanced discussion questions, making it invaluable for educators and students needing structured, up-to-date course resources.

Generates a comprehensive Chinese interview-prep cheat sheet for a specific ML/LLM topic, including formulas with derivations, from-scratch PyTorch code, comparison tables, and 25 high-frequency interview questions at L1/L2/L3 levels. Ideal for interview preparation and focused technical review.

A comprehensive coaching layer designed to elevate users into power users of AI models. Upon first activation, it provides a structured glossary of high-impact techniques tailored to user needs. In subsequent turns, it actively monitors prompts, surfacing single, actionable tips to optimize interactions and maximize the AI's capabilities, ensuring continuous, guided learning.

This skill automatically enriches research wiki pages that are left as bare scaffolds after initial ingestion. It reads multiple external sources (like arXiv/alphaxiv) and fills in 10 structured `_TODO._` sections (e.g., Problem/Gap, Key Results, Open Questions) with detailed prose summaries. Use this skill to transform incomplete research scaffolds into a comprehensive, structured knowledge base.

This skill utilizes the 2slides API to generate professional, multi-format presentations. It supports creating slides from raw text, summarizing uploaded documents, matching a specific style from a reference image, and adding AI voice narration. Outputs include interactive slide URLs and downloadable PDFs. Ideal for any 'make slides' or 'create a deck' workflow.

This skill converts a single still image (PNG/JPG) into a short, animated MP4 video using a slow Ken-Burns zoom effect and a silent audio track. It is designed specifically as an 'on_failure' fallback mechanism for AI video generation steps that might fail due to content moderation or other upstream issues, ensuring a complete deliverable can still be produced for downstream merging.

This skill enables the creation and registration of reusable cloned voices from local audio samples for subsequent Text-to-Speech (TTS) applications. It implements a strict 'Consent-first' workflow, requiring explicit user consent, detailed metadata (speaker, permitted use), and adherence to copyright laws before any voice cloning can occur. It ensures the resulting voice ID is safe, traceable, and legally compliant for professional content creation.

This skill provides a comprehensive guide for building scalable Retrieval-Augmented Generation (RAG) pipelines and persistent agent memory using Pinecone as the vector database. It covers index setup, embedding large corpuses, implementing dense and hybrid semantic search, and advanced metadata filtering for real-world production systems. Use this for building searchable knowledge bases and context-aware AI agents.

This skill guides the process of routing a complex goal through an AI's scored-memory loop using the `acc_act(runtime="solve")` function. It provides a structured workflow for deliberation, handling intermediate `brain_frame` results, and submitting continuous proposals. It emphasizes systematic reasoning and requires careful resolution of all generated frames to ensure a robust and verifiable solution.

Conducts a comprehensive, structured ethical review for any AI or ML model, feature, or product. It assesses risks related to fairness, bias, transparency, privacy, and societal impact, providing a risk tier score, necessary mitigations, and governance documentation suitable for pre-deployment compliance.

This skill assists users in defining, adapting, and designing bounded, structured feedback loops for AI agents. Whether you need to find a suitable existing workflow, fine-tune a published loop, or design a new process from scratch, this tool guides you through a safe, iterative methodology. It emphasizes setting clear stopping rules, guardrails, and verifiable, measurable steps to ensure the automation remains controllable and focused.

This skill provides a repeatable assessment for RAG systems, testing for critical vulnerabilities in vector stores and embedding models. It specifically addresses embedding inversion, cross-tenant data leakage, and knowledge-base poisoning, aligning with OWASP LLM08:2025. Use when performing authorized security audits of retrieval layers and multi-tenant isolation.