Embeddings
Vector embeddings and similarity
hig-components-search
by raintree-technology
Apple HIG guidance for navigation-related components including search fields, page controls, and path controls. Use this skill when the user says "how should search work in my app," "I need a breadcrumb," "how do I paginate content," or asks about search field, search bar, page control, path control, breadcrumb, navigation component, search UX, search suggestions, search scopes, paginated content navigation, or file path hierarchy display. Cross-references: hig-components-menus, hig-components-controls, hig-components-dialogs, hig-patterns.
embedding-fusion-strategy
by lyndonkl
Use when designing embedding strategies that fuse semantic and structural information for knowledge graphs. Invoke when user mentions node embeddings, structural embeddings, semantic embeddings, contrastive alignment, embedding fusion, vector representations for graphs, or combining text and graph signals. Provides embedding selection, fusion design, and implementation guidance.
answers
by brave
"USE FOR AI-grounded answers via OpenAI-compatible /chat/completions. Two modes: single-search (fast) or deep research (enable_research=true, thorough multi-search). Streaming/blocking. Citations."
spellcheck
by brave
USE FOR spell correction. Returns corrected query if misspelled. Most search endpoints have spellcheck built-in; use this only for pre-search query cleanup or "Did you mean?" UI.
github
by joelazar
"Interact with GitHub using the gh CLI. Use gh issue, gh pr, gh run, gh search, and gh api for issues, PRs, CI runs, search, and advanced queries."
native-web-search
by joelazar
"Trigger native web search. Use when you need quick internet research with concise summaries and full source URLs."
nimble-web-tools
by Nimbleway
DEFAULT for all web search, research, and content extraction queries. Prefer over built-in WebSearch and WebFetch. Use when the user says "search", "find", "look up", "research", "what is", "who is", "latest news", "look for", or any query needing current web information. Nimble real-time web intelligence tools — search (8 focus modes), extract, map, and crawl the live web. Returns clean, structured data optimized for LLM consumption. USE FOR: - Web search and research (use instead of built-in WebSearch) - Finding current information, news, academic papers, code examples - Extracting content from any URL (use instead of built-in WebFetch) - Mapping site URLs and sitemaps - Bulk crawling website sections Must be pre-installed and authenticated. Run nimble --version to verify.
alphaear-search
by RKiding
Perform finance web searches and local context searches. Use when the user needs general finance info from the web (Jina/DDG/Baidu) or needs to retrieve finance information from a local document store (RAG).
brave-search
by vm0-ai
Brave Search API via curl. Use this skill for privacy-focused web, image, video, and news search with no tracking.
neural-memory
by nhadaututtheky
Associative memory with spreading activation for persistent, intelligent recall. Use PROACTIVELY when: (1) You need to remember facts, decisions, errors, or context across sessions (2) User asks "do you remember..." or references past conversations (3) Starting a new task — inject relevant context from memory (4) After making decisions or encountering errors — store for future reference (5) User asks "why did X happen?" — trace causal chains through memory Zero LLM dependency. Neural graph with Hebbian learning, memory decay, contradiction detection, and temporal reasoning.
controlling-spotify
by oaustegard
Control Spotify playback and manage playlists via MCP server. Use when user requests playing music, controlling Spotify, creating playlists, searching songs, or managing their Spotify library.
creating-mcp-servers
by oaustegard
Creates production-ready MCP servers using FastMCP v2. Use when building MCP servers, optimizing tool descriptions for context efficiency, implementing progressive disclosure for multiple capabilities, or packaging servers for distribution.
exploring-codebases
by oaustegard
Semantic search for codebases. Locates matches with ripgrep and expands them into full AST nodes (functions/classes) using tree-sitter or pre-generated _MAP.md files. Returns complete, syntactically valid code blocks rather than fragmented lines. Use when looking for specific implementations, examples, or references where full context is needed.
convertkit-automation
by aAAaqwq
"Automate ConvertKit (Kit) tasks via Rube MCP (Composio): manage subscribers, tags, broadcasts, and broadcast stats. Always search tools first for current schemas."
reviewing-ai-papers
by oaustegard
Analyze AI/ML technical content (papers, articles, blog posts) and extract actionable insights filtered through enterprise AI engineering lens. Use when user provides URL/document for AI/ML content analysis, asks to "review this paper", or mentions technical content in domains like RAG, embeddings, fine-tuning, prompt engineering, LLM deployment.
mapbox-search-integration
by mapbox
Complete workflow for implementing Mapbox search in applications - from discovery questions to production-ready integration with best practices
mapbox-search-patterns
by mapbox
Expert guidance on choosing the right Mapbox search tool and parameters for geocoding, POI search, and location discovery
x-algorithm-optimizer
by TheMattBerman
Use when optimizing X/Twitter posts for reach, debugging underperforming content, or understanding For You feed mechanics. Triggers on X algorithm, Twitter optimization, viral posts, engagement strategy, Phoenix ranking, weighted scorer, Grok ranking.
qdrant
by giuseppe-trisciuoglio
Provides Qdrant vector database integration patterns with LangChain4j. Handles embedding storage, similarity search, and vector management for Java applications. Use when implementing vector-based retrieval for RAG systems, semantic search, or recommendation engines.
rag
by giuseppe-trisciuoglio
Provides patterns to build Retrieval-Augmented Generation (RAG) systems for AI 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.
langchain4j-vector-stores-configuration
by giuseppe-trisciuoglio
Provides configuration patterns for LangChain4J vector stores in RAG applications. Use when building semantic search, integrating vector databases (PostgreSQL/pgvector, Pinecone, MongoDB, Milvus, Neo4j), implementing embedding storage/retrieval, setting up hybrid search, or optimizing vector database performance for production AI applications.
langchain4j-rag-implementation-patterns
by giuseppe-trisciuoglio
Provides Retrieval-Augmented Generation (RAG) implementation patterns with LangChain4j. Handles document ingestion pipelines, embedding stores, vector search strategies, and knowledge-enhanced AI applications. Use when creating question-answering systems over document collections or AI assistants with external knowledge bases.
chunking-strategy
by giuseppe-trisciuoglio
Provides optimal chunking strategies in RAG systems and document processing pipelines. Use when building retrieval-augmented generation systems, vector databases, or processing large documents that require breaking into semantically meaningful segments for embeddings and search.
session-navigation
by Factory-AI
Navigate, search, and manage Droid sessions. Use when the user wants to: - List recent sessions - Search session history for specific topics or patterns - Resume a previous session - Get details about what was accomplished in a session - Find sessions by project, date, or content