351 skills · sorted by relevance
Spectral vector search using graph Laplacian eigenstructure. Use when cosine/L2 similarity misses latent structure in your embeddings.
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Build production-ready LLM applications, advanced RAG systems, and intelligent agents. Implements vector search, multimodal AI, agent orchestration, and enterprise AI integrations.
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Build production-ready LLM applications, advanced RAG systems, and intelligent agents. Implements vector search, multimodal AI, agent orchestration, and enterprise AI integrations.
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Build Retrieval-Augmented Generation (RAG) systems for LLM applications with vector databases and semantic search. Use when implementing knowledge-grounded AI, building document Q&A systems, or integrating LLMs with external knowledge bases.
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Build production-ready LLM applications, advanced RAG systems, and intelligent agents. Implements vector search, multimodal AI, agent orchestration, and enterprise AI integrations.
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Fast vector similarity search at billion scale.
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Build production-ready LLM applications, advanced RAG systems, and intelligent agents. Implements vector search, multimodal AI, agent orchestration, and enterprise AI integrations.
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Manage files and folders on the Unique AI Platform using the unique-cli command-line tool. Use when the user asks to upload, download, delete, rename, list, find, restore versions, list versions, look for, or organize files and folders on Unique, or to read / view / quote the text contents of a known file (optionally by page or page range, e.g. "what's on page 5?", "read pages 10-12"), or when working with scope IDs (scope_*) or content IDs (cont_*). IMPORTANT: When a user says they are "looking for a file" or wants to "find a file", they typically mean locating it within the Unique AI Platform knowledge base — not on the local filesystem. Use this skill to browse and list folders/files on Unique to help them find it. This is also the preferred approach for locating Excel (.xlsx/.xls), CSV (.csv), and image files, as these file types are not full-text indexed and cannot be found via vector/full-text search.
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Build production-ready LLM applications, advanced RAG systems, and intelligent agents. Implements vector search, multimodal AI, agent orchestration, and enterprise AI integrations.
The English summary is being prepared. Showing the original description.
Build production-ready LLM applications, advanced RAG systems, and intelligent agents. Implements vector search, multimodal AI, agent orchestration, and enterprise AI integrations.
The English summary is being prepared. Showing the original description.
Build production-ready LLM applications, advanced RAG systems, and intelligent agents. Implements vector search, multimodal AI, agent orchestration, and enterprise AI integrations. Use PROACTIVELY for LLM features, chatbots, AI agents, or AI-powered applications.
The English summary is being prepared. Showing the original description.
Build production-ready LLM applications, advanced RAG systems, and intelligent agents. Implements vector search, multimodal AI, agent orchestration, and enterprise AI integrations.
The English summary is being prepared. Showing the original description.
Build production-ready LLM applications, advanced RAG systems, and intelligent agents. Implements vector search, multimodal AI, agent orchestration, and enterprise AI integrations. Use PROACTIVELY for LLM features, chatbots, AI agents, or AI-powered applications.
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You are helping a penetration tester analyze a custom application, script, or
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AI/LLM security offensive checklist: prompt injection, jailbreaking, model extraction, training data poisoning, adversarial inputs, LLM-assisted attack automation, and AI system reconnaissance. Use when assessing AI/ML systems, red-teaming LLMs, or researching AI attack vectors.
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