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Found 146 Skills
Guide RCCA/8D problem definition using 5W2H and IS/IS NOT analysis. Transforms scattered failure data into precise, measurable problem statements that bound investigation scope without embedding cause or solution. Use when defining problems for root cause analysis, writing D2 sections of 8D reports, analyzing nonconformances, investigating failures, or when user mentions problem definition, problem statement, RCCA, 8D, failure analysis, or corrective action.
Native SwiftUI WebKit integration with the new WebView struct and WebPage observable class. Covers WebView creation from URLs, WebPage for navigation control and state management, JavaScript execution (callJavaScript with arguments and content worlds), custom URL scheme handlers, navigation management (load, reload, back/forward), navigation decisions, text search (findNavigator), content capture (snapshots, PDF generation, web archives), and configuration (data stores, user agents, JS permissions). Use when embedding web content in SwiftUI apps instead of the old WKWebView + UIViewRepresentable/NSViewRepresentable bridge pattern. This is a brand new API — do NOT use the old WKWebView wrapping approach.
Retrieval-Augmented Generation - chunking strategies, embedding, vector search, hybrid retrieval, reranking, query transformation. Use when building RAG pipelines, knowledge bases, or context-augmented applications.
Use just for command running and task automation. Prefer Justfiles over Makefiles. Keep recipes simple - delegate complex logic to scripts rather than embedding in recipes.
Run ML model inference (YOLO, YOLOv8, CLIP, SAM, Detectron2, etc.) on FiftyOne datasets. Use when running models, applying detection, classification, segmentation, embeddings, or any model prediction task. Also use for end-to-end workflows that include importing data then running inference.
Configure Spice.ai in-memory caching for SQL query results, search results, and embeddings. Use when setting up caching, tuning cache TTL/size/eviction, configuring stale-while-revalidate, custom cache keys, or cache-control headers.
Build complete document knowledge bases with PDF text extraction, OCR for scanned documents, vector embeddings, and semantic search. Use this for creating searchable document libraries from folders of PDFs, technical standards, or any document collection.
Semantic search for Marp presentations using vector embeddings. Use when finding relevant slides by topic, retrieving slide content, or exploring presentation materials. Triggers on "find slides about...", "search presentations for...", "get slide content", "what slides cover...", or any Marp/presentation search query.
Configure pgvector extension for vector search in Supabase - includes embedding storage, HNSW/IVFFlat indexes, hybrid search setup, and AI-optimized query patterns. Use when setting up vector search, building RAG systems, configuring semantic search, creating embedding storage, or when user mentions pgvector, vector database, embeddings, semantic search, or hybrid search.
Guide developers integrating EUrouter into their applications. EUrouter is an OpenAI-compatible AI gateway for EU/GDPR compliance. Use when integrating EUrouter, switching from OpenRouter or OpenAI, configuring EU data residency, routing AI requests to EU providers, managing API keys, or asking about EUrouter's API for chat completions, embeddings, streaming, tool calling, vision, model routing, or GDPR compliance features.
Semantic and multi-modal search across documents using LanceDB vector embeddings. Use when searching knowledge bases, finding information semantically, ingesting documents for RAG, or performing vector similarity search. Triggers on "search documents", "semantic search", "find in knowledge base", "vector search", "index documents", "LanceDB", or RAG/embedding operations.
This skill provides semantic search capabilities using embedding-based similarity matching for code and text. Enables meaning-based search beyond keyword matching, with optional document parsing (PDF, DOCX, PPTX) support.