Embeddings
Vector embeddings and similarity
llm-application-dev
by skillcreatorai
Building applications with Large Language Models - prompt engineering, RAG patterns, and LLM integration. Use for AI-powered features, chatbots, or LLM-based automation.
claude-cookbooks
by 2025Emma
Claude AI cookbooks - code examples, tutorials, and best practices for using Claude API. Use when learning Claude API integration, building Claude-powered applications, or exploring Claude capabilities.
memory
by yonatangross
"Read-side memory operations: search, recall, load, sync, history, visualize. Use when searching past decisions, loading session context, or viewing the knowledge graph."
rag-retrieval
by yonatangross
Retrieval-Augmented Generation patterns for grounded LLM responses. Use when building RAG pipelines, embedding documents, implementing hybrid search, contextual retrieval, HyDE, agentic RAG, multimodal RAG, query decomposition, reranking, or pgvector search.
ai
by telagod
AI/LLM 能力索引。Agent 开发、LLM 安全、RAG 系统。当用户提到 AI、LLM、Agent、RAG、Prompt 时路由到此。
box-automation
by aAAaqwq
Automate Box cloud storage operations including file upload/download, search, folder management, sharing, collaborations, and metadata queries via Rube MCP (Composio). Always search tools first for current schemas.
codebase-search
by Helweg
Semantic code search by meaning. Use codebase_peek to find WHERE code is (saves tokens), codebase_search to see actual code. For exact identifiers, use grep instead.
outlook-emails-lawvable
by lawvable
Read, search, and download emails and attachments from Microsoft Outlook via OAuth2. Use when the user asks to (1) check, read, or fetch emails or messages from Outlook, (2) search emails by keyword, sender, or subject, (3) download email attachments such as contracts, NDAs, or documents, (4) chain email content into other skills (e.g. "read the latest email from X and review the attached NDA"), or (5) any task involving Microsoft Outlook, Office 365, or Exchange email access.
zai-cli
by numman-ali
Z.AI CLI providing: - Vision: image/video analysis, OCR, UI-to-code, error diagnosis (GLM-4.6V) - Search: real-time web search with domain/recency filtering - Reader: web page to markdown extraction - Repo: GitHub code search and reading via ZRead - Tools: MCP tool discovery and raw calls - Code: TypeScript tool chaining Use for visual content analysis, web search, page reading, or GitHub exploration. Requires Z_AI_API_KEY.
semtools
by massgen
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.
ast-grep
by ast-grep
Guide for writing ast-grep rules to perform structural code search and analysis. Use when users need to search codebases using Abstract Syntax Tree (AST) patterns, find specific code structures, or perform complex code queries that go beyond simple text search. This skill should be used when users ask to search for code patterns, find specific language constructs, or locate code with particular structural characteristics.
google-drive
by sanjay3290
Interact with Google Drive - search files, find folders, list contents, download files, upload files, create folders, move, copy, rename, and trash files. Use when user asks to: search Google Drive, find a file/folder, list Drive contents, download or upload files, create folders, move files, or organize Drive content. Lightweight integration with standalone OAuth authentication supporting full read/write access.
gmail
by sanjay3290
Interact with Gmail - search emails, read messages, send emails, create drafts, and manage labels. Use when user asks to: search email, read email, send email, create email draft, mark as read, archive email, star email, or manage Gmail labels. Lightweight alternative to full Google Workspace MCP server with standalone OAuth authentication.
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.
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.
docx-processing-superdoc
by lawvable
Searches, replaces, and reads text in Word documents. Use when the user asks to edit, search, or extract text from .docx files.
exa
by refly-ai
"Perform semantic search using Exa AI. Use when you need to: (1) find content by meaning not keywords, (2) discover similar documents, or (3) perform neural web searches."
gmail
by refly-ai
Integrate with Gmail for email management and automation. Use when you need to: (1) send and compose emails with attachments, (2) read and search emails by criteria, (3) manage drafts and email labels, or (4) reply to email threads and conversations.
apollo
by refly-ai
"Search sales leads with Apollo.io. Use when you need to: (1) find company and contact information, (2) enrich lead data, or (3) search for B2B prospects."
deepsearch
by bytedance
深度研究代理系统社区版，对复杂主题进行多轮迭代的网络搜索和综合分析。使用场景：当用户需要对特定主题进行深入、全面的研究时，特别是需要基于最新网络信息生成详细分析报告的情况。支持多轮迭代搜索、智能搜索方向调整和综合分析报告生成。本skill是一个工作流描述文档，没有执行脚本，依赖web-search skill进行网页搜索。
huashu-info-search
by alchaincyf
多渠道搜索新产品新技术，交叉验证后存入知识库。当用户提到"最新信息"、"新产品"、"搜索资料"、"查资料"、"了解XX"时使用。
sqlite-vec
by existential-birds
sqlite-vec extension for vector similarity search in SQLite. Use when storing embeddings, performing KNN queries, or building semantic search features. Triggers on sqlite-vec, vec0, MATCH, vec_distance, partition key, float[N], int8[N], bit[N], serialize_float32, serialize_int8, vec_f32, vec_int8, vec_bit, vec_normalize, vec_quantize_binary, distance_metric, metadata columns, auxiliary columns.
search
by tavily-ai
"Search the web using Tavily's LLM-optimized search API. Returns relevant results with content snippets, scores, and metadata. Use when you need to find web content on any topic without writing code."
pgvector-semantic-search
by timescale
Use this skill for setting up vector similarity search with pgvector for AI/ML embeddings, RAG applications, or semantic search. Trigger when user asks to: - Store or search vector embeddings in PostgreSQL - Set up semantic search, similarity search, or nearest neighbor search - Create HNSW or IVFFlat indexes for vectors - Implement RAG (Retrieval Augmented Generation) with PostgreSQL - Optimize pgvector performance, recall, or memory usage - Use binary quantization for large vector datasets Keywords: pgvector, embeddings, semantic search, vector similarity, HNSW, IVFFlat, halfvec, cosine distance, nearest neighbor, RAG, LLM, AI search Covers: halfvec storage, HNSW index configuration (m, ef_construction, ef_search), quantization strategies, filtered search, bulk loading, and performance tuning.