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Found 1,837 Skills
Spatial organization of knowledge in navigable directories
Kinetica SQL query knowledge. Activate when the user is writing analytical queries for Kinetica, asking about Kinetica-specific functions, or working with geospatial, time-series, graph, or vector data.
Guide for implementing the Syncfusion WinUI Segmented Control for creating mutually exclusive option selectors. Use this skill when implementing segmented controls, segment pickers, tab selectors, or mutually exclusive option selectors in WinUI applications. Essential for segment-based navigation, filter toggles, view switchers, button groups with single selection, or any scenario requiring mutually exclusive selection from 2+ options in WinUI.
INVOKE THIS SKILL when building ANY retrieval-augmented generation (RAG) system. Covers document loaders, RecursiveCharacterTextSplitter, embeddings (OpenAI), and vector stores (Chroma, FAISS, Pinecone).
This skill should be used when the user asks to "implement agent memory", "persist state across sessions", "build knowledge graph", "track entities", or mentions memory architecture, temporal knowledge graphs, vector stores, entity memory, or cross-session persistence.
Lists Power Platform connections in the current environment. Use when you need a connection ID before adding a connector to a code app.
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.
Archive accumulated phase directories from completed milestones
Comprehensive automation for Letterly transcriptions. This skill exports the latest CSV from Letterly, processes "magic" notes into Obsidian markdown with custom metadata, semantically links them using a vector database, and moves them to the final Transcriptions directory. Use when the user asks to "process new letterly transcriptions", "sync letterly", or "import magic notes from letterly".
Enable and configure Moltbot/Clawdbot memory search for persistent context. Use when setting up memory, fixing "goldfish brain," or helping users configure memorySearch in their config. Covers MEMORY.md, daily logs, and vector search setup.
Comprehensive toolkit for developing with the CocoIndex library. Use when users need to create data transformation pipelines (flows), write custom functions, or operate flows via CLI or API. Covers building ETL workflows for AI data processing, including embedding documents into vector databases, building knowledge graphs, creating search indexes, or processing data streams with incremental updates.
Redis performance optimization and best practices. Use this skill when working with Redis data structures, Redis Query Engine (RQE), vector search with RedisVL, semantic caching with LangCache, or optimizing Redis performance.