Embeddings
Vector embeddings and similarity
pinecone:cli
by pinecone-io
Guide for using the Pinecone CLI (pc) to manage Pinecone resources from the terminal. The CLI supports ALL index types (standard, integrated, sparse) and all vector operations — unlike the MCP which only supports integrated indexes. Use for batch operations, vector management, backups, namespaces, CI/CD automation, and full control over Pinecone resources.
omicverse-visualization-for-bulk-color-systems-and-single-cell-d
by Starlitnightly
Guide users through OmicVerse plotting utilities showcased in the bulk, color system, and single-cell visualization tutorials, including venn/volcano charts, palette selection, and advanced embedding layouts.
octocode-plan
by bgauryy
Use when the user asks to "plan this feature", "plan refactor", "research & plan", "plan auth/API/work", or needs multi-step work with evidence-based planning before coding. Understands → Researches (via Local Search/Research) → Plans → Implement. No guessing; validates with code.
UI/UX Pro Max - Design Intelligence
by apconw
Aix-DB 基于 LangChain/LangGraph 框架，结合 MCP Skills 多智能体协作架构，实现自然语言到数据洞察的端到端转换。
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.
chinese-learning-assistant
by aiskillstore
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Search Memory
by nowledge-co
Search memory store when past insights would improve response. Recognize when user's stored breakthroughs, decisions, or solutions are relevant. Search proactively based on context, not just explicit requests.
plagiarism-checker
by bitwize-music-studio
Scans lyrics for phrases that may match existing songs using web search and LLM knowledge. Use before release to check for unintentional borrowing.
predictive-intelligence
by groeimetai
This skill should be used when the user asks to "predictive intelligence", "machine learning", "ML", "classification", "similarity", "clustering", "prediction", "AI", or any ServiceNow Predictive Intelligence development.
session-search
by pchalasani
For CLI agents WITHOUT subagent support (e.g., Codex CLI). Search previous code agent sessions for specific work, decisions, or code patterns.
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.
postgres-hybrid-text-search
by timescale
Use this skill to implement hybrid search combining BM25 keyword search with semantic vector search using Reciprocal Rank Fusion (RRF). Trigger when user asks to: - Combine keyword and semantic search - Implement hybrid search or multi-modal retrieval - Use BM25/pg_textsearch with pgvector together - Implement RRF (Reciprocal Rank Fusion) for search - Build search that handles both exact terms and meaning Keywords: hybrid search, BM25, pg_textsearch, RRF, reciprocal rank fusion, keyword search, full-text search, reranking, cross-encoder Covers: pg_textsearch BM25 index setup, parallel query patterns, client-side RRF fusion (Python/TypeScript), weighting strategies, and optional ML reranking.
uloop-unity-search
by hatayama
"Search Unity project for assets. Use when: finding scenes, prefabs, scripts, materials, or other assets by name/type, or when user asks to search project files. Returns asset paths and metadata."
pinecone:mcp
by pinecone-io
Reference for the Pinecone MCP server tools. Documents all available tools - list-indexes, describe-index, describe-index-stats, create-index-for-model, upsert-records, search-records, cascading-search, and rerank-documents. Use when an agent needs to understand what Pinecone MCP tools are available, how to use them, or what parameters they accept.
bulktrajblend-trajectory-interpolation
by Starlitnightly
Extend scRNA-seq developmental trajectories with BulkTrajBlend by generating intermediate cells from bulk RNA-seq, training beta-VAE and GNN models, and interpolating missing states.
smithery-ai-cli
by smithery-ai
Find, connect, and use MCP tools and skills via the Smithery CLI. Use when the user searches for new tools or skills, wants to discover integrations, connect to an MCP, install a skill, or wants to interact with an external service (email, Slack, Discord, GitHub, Jira, Notion, databases, cloud APIs, monitoring, etc.).
durable-ui
by sailscastshq
Durable UI patterns for modern web development — persisting client-side state across page loads, browser sessions, and shareable URLs. Use this skill when implementing localStorage persistence, URL query parameter state, form draft auto-save, multi-step wizard persistence, click-outside dismissal, modal/dialog backdrop patterns, or any client-side state and interaction pattern that should be resilient and well-behaved. Works with React, Vue, and Svelte.
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.
uloop-get-logs
by hatayama
"Check Unity Console logs. Use when: checking logs, debugging errors, investigating failures, or when user asks about console output. Key options: --log-type (Error/Warning/Log/All), --max-count, --search-text. Retrieves errors, warnings, and Debug.Log messages."
find-similar
by inkeep
Find similar or analogous code patterns elsewhere in a codebase. Use when answering "Do we do something similar elsewhere?" or "What existing patterns match this?" Returns factual findings about similar code - locations, similarity type, and confidence.
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.
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.
content-marketing
by RefoundAI
Help users build content marketing strategies. Use when someone is starting a blog, building SEO, creating thought leadership content, or deciding on content formats and distribution channels.