Skill UI

A comprehensive guide for training or fine-tuning advanced sentence-transformer models. This skill assists in selecting the correct architecture—including Bi-encoders (SentenceTransformer), CrossEncoders (for reranking), and SparseEncoders—for various Natural Language Processing (NLP) tasks. Use cases include semantic retrieval, similarity matching, document clustering, and pair-wise classification.

A technical specialization focused on Generative Engine Optimization (GEO). This skill ensures that specific web pages are structured, documented, and optimized for modern AI answer engines (Google AI Overviews, ChatGPT, Bing Copilot). It focuses on technical elements like structured data (JSON-LD), semantic HTML, and robust metadata to maximize discoverability, trustworthiness, and quotability for AI consumption, rather than traditional SEO ranking.

A comprehensive tool for querying, storing, and managing complex knowledge across multiple agent sessions. AgentDB utilizes advanced techniques including semantic routing, hierarchical recall, causal graph construction, and context synthesis. Use this skill when your application requires robust, multi-faceted knowledge retrieval and reasoning based on structured and unstructured data. It provides a structured workflow for checking system health, starting sessions, storing knowledge in tiers (working, episodic, semantic), and searching learned patterns.

A state-of-the-art memory search engine providing multi-faceted retrieval strategies. It supports default dense semantic matching, advanced hybrid search (sparse + dense with RRF), deep multi-hop Graph RAG for complex reasoning, and 'Smart' search utilizing query expansion, recency boosting, and MMR diversity reranking. Ideal for retrieving nuanced, diverse, and time-sensitive information from large, complex knowledge bases across multiple namespaces.

A utility designed to generate high-dimensional vector embeddings (384-dim) from various sources including text, code, or documents. This process converts raw data into numerical representations optimized for semantic search, similarity comparison, and clustering, utilizing ONNX and HNSW indexing for efficient retrieval.

Ruflo is a powerful, cross-agent orchestration layer designed to manage complex, multi-step AI coding workflows. It supports coordinating large swarms of AI agents, managing persistent memory through semantic search, and executing sophisticated pipelines using 30+ specialized plugins. Ideal for large-scale development tasks, system benchmarking, and deep research requiring coordinated agent effort.

A comprehensive guide for authors submitting papers to the ACL conference. It assists in positioning the manuscript, verifying topic fit (NLP, language models, semantics), and ensuring the evidence meets the high standards required for top-tier computational linguistics venues. Covers structure, best practices, and submission checklists.

This skill is a strategic guide for authors submitting to top-tier AI conferences, specifically the International Conference on Principles of Knowledge Representation and Reasoning (KR). It helps users assess manuscript fit, framing, and evidence requirements. It provides deep guidance on the required scope, such as formal semantics, nonmonotonic reasoning, and ontologies, ensuring the paper is positioned correctly within the specialized KR community. Ideal for pre-submission strategy and manuscript re-framing.

This skill provides a comprehensive guide for authors targeting the International Semantic Web Conference (ISWC). It details the best practices for framing semantic web, knowledge graph, and ontology papers. It helps authors ensure their manuscript meets the venue's high standards regarding semantic interoperability, real-world data application, and specific contribution types, optimizing the submission strategy.

This operator skill provides comprehensive control over the OpenViking context engine, enabling agents to manage long-term memory, session archives, and external resources within OpenClaw. It facilitates semantic recall, context querying, resource import, and recall trace debugging by communicating with a remote OpenViking server. Use this plugin when your agent requires advanced, persistent context management.

This skill provides a comprehensive guide for manuscript authors targeting the StarSem Conference on Computational Semantics (*SEM). It helps authors determine the conference fit, refine framing, establish the necessary evidence bar, and strategize submissions for topics related to meaning representation, semantic parsing, and inference. It is a specialized venue-selection and re-framing tool for advanced NLP/CS papers.

Use for live Windows or macOS GUI tasks that structured tools cannot complete. Discover approved apps and windows, observe current state, act via semantic elements or shortcuts, and verify every requested outcome. Includes an operating loop for reliable desktop automation and visual verification.