Skill UI

This skill provides an automated solution for transforming diverse, unstructured technical data sources—including documentation websites, GitHub repositories, and PDFs—into structured, actionable 'Claude AI skills.' It significantly streamlines the process of knowledge base creation, data structuring, and preparing large volumes of technical information for advanced AI applications.

Vexor is a powerful command-line interface designed for advanced semantic search across local files. By utilizing vector embeddings and integrating with large language models (like Claude/Codex), it allows users to search files based on meaning and context, rather than just exact keywords. This is ideal for large codebases or document repositories where traditional keyword search methods are insufficient.

This skill provides a comprehensive, end-to-end pipeline for the entire academic research lifecycle. It guides users from initial idea discovery and experimental validation through rigorous cross-model review, culminating in a polished research paper draft. It supports advanced configurations, such as defining reviewer difficulty or integrating specific base code repositories, and allows for resumable runs.

This skill allows agents to ingest external resources (local files, URLs, repositories) using `ov add-resource`, and to create long-lasting searchable memories from conversations using `ov add-memory`. It is essential for building a comprehensive, persistent knowledge base for the OpenViking context database, ensuring that learned insights and external data remain available across sessions and interactions. Use when external knowledge injection or context persistence is required.

This powerful compiler ingests heterogeneous research inputs, including PDF papers, code repositories, experiment logs, and raw notes. It transforms this diverse data into a comprehensive, structured Agent-Native Research Artifact (ARA). The system extracts core knowledge atoms, builds cognitive maps (claims, concepts, heuristics), and generates a verifiable, executable knowledge package for advanced AI consumption and research iteration.

This skill helps discover new Japanese Natural Language Processing (NLP) resources, including GitHub repositories and Hugging Face models/datasets, that are not yet documented in the awesome-japanese-nlp-resources list. It analyzes a given topic, suggests candidates using web search, and outputs contribution-ready markdown for easy integration.