Embeddings
Vector embeddings and similarity
bedrock
by itsmostafa
AWS Bedrock foundation models for generative AI. Use when invoking foundation models, building AI applications, creating embeddings, configuring model access, or implementing RAG patterns.
ask
by agenticnotetaking
Query the bundled research knowledge graph for methodology guidance. Routes questions through a 3-tier knowledge base — WHY (research claims), HOW (guidance docs), WHAT IT LOOKS LIKE (domain examples) — plus structured reference documents. Returns research-backed answers grounded in specific claims with practical application to the user's system. Triggers on "/ask", "/ask [question]", "why does my system...", "how should I...".
competitor-teardown
by inference-sh
"Structured competitive analysis with feature matrices, SWOT, positioning maps, and UX review. Covers research frameworks, pricing comparison, review mining, and visual deliverables. Use for: market research, competitive intelligence, investor decks, product strategy, sales enablement. Triggers: competitor analysis, competitive analysis, competitor teardown, market research, competitive intelligence, swot analysis, competitor comparison, market landscape, competitor review, competitive landscape, feature comparison, market positioning"
logo-design-guide
by inference-sh
"Logo design principles and AI image generation best practices for creating logos. Covers logo types, prompting techniques, scalability rules, and iteration workflows. Use for: brand identity, startup logos, app icons, favicons, logo concepts. Triggers: logo design, create logo, brand logo, logo generation, ai logo, logo maker, icon design, brand mark, logo concept, startup logo, app icon logo"
knowledge
by boshu2
'Query knowledge artifacts across all locations. Triggers: "find learnings", "search patterns", "query knowledge", "what do we know about", "where is the plan".'
hig-components-dialogs
by raintree-technology
Apple HIG guidance for presentation components including alerts, action sheets, popovers, sheets, and digit entry views. Use this skill when the user says "should I use an alert or a sheet," "how do I show a confirmation dialog," "when should I use a popover," "my modals are annoying users," or asks about alert design, action sheet, popover, sheet, modal, dialog, digit entry, confirmation dialog, warning dialog, modal presentation, non-modal content, destructive action confirmation, or overlay UI patterns. Cross-references: hig-components-menus, hig-components-controls, hig-components-search, hig-patterns.
building-native-ui
by freekmurze
Complete guide for building beautiful apps with Expo Router. Covers fundamentals, styling, components, navigation, animations, patterns, and native tabs.
linear-search
by Finesssee
Search Linear issues and projects. Use when finding issues, looking up bugs, or searching the backlog.
harmony-batch-correction
by jaechang-hits
"Batch correction for single-cell RNA-seq (and other omics) with Harmony. Removes technical batch effects from PCA embeddings while preserving biological variation. Use after PCA, before UMAP/neighbors. Fast and scalable to millions of cells. Python (harmonypy, scanpy integration) and R (Seurat) APIs."
geniml
by jaechang-hits
"Geniml is a Python library for genomic interval machine learning. Train and apply region2vec embeddings to convert BED file regions into numeric vectors, load and index genomic interval datasets for ML pipelines, search embedding spaces with BEDSpace, and evaluate embedding quality. Use for chromatin accessibility clustering, regulatory element classification, cross-sample region comparison, and building ML models on genomic intervals."
code-stats
by NeverSight
"Analyze codebase with tokei (fast line counts by language) and difft (semantic AST-aware diffs). Get quick project overview without manual counting. Triggers on: how big is codebase, count lines of code, what languages, show semantic diff, compare files, code statistics."
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.
openai-docs
by boshu2
"Use when the user asks how to build with OpenAI products or APIs and needs up-to-date official documentation with citations (for example: Codex, Responses API, Chat Completions, Apps SDK, Agents SDK, Realtime, model capabilities or limits); prioritize OpenAI docs MCP tools and restrict any fallback browsing to official OpenAI domains."
file-search
by NeverSight
"Modern file and content search using fd, ripgrep (rg), and fzf. Triggers on: fd, ripgrep, rg, find files, search code, fzf, fuzzy find, search codebase."
ai-rag-pipeline
by inference-sh
"Build RAG (Retrieval Augmented Generation) pipelines with web search and LLMs. Tools: Tavily Search, Exa Search, Exa Answer, Claude, GPT-4, Gemini via OpenRouter. Capabilities: research, fact-checking, grounded responses, knowledge retrieval. Use for: AI agents, research assistants, fact-checkers, knowledge bases. Triggers: rag, retrieval augmented generation, grounded ai, search and answer, research agent, fact checking, knowledge retrieval, ai research, search + llm, web grounded, perplexity alternative, ai with sources, citation, research pipeline"
search-company-knowledge
by atlassian
"Search across company knowledge bases (Confluence, Jira, internal docs) to find and explain internal concepts, processes, and technical details. When Claude needs to: (1) Find or search for information about systems, terminology, processes, deployment, authentication, infrastructure, architecture, or technical concepts, (2) Search internal documentation, knowledge base, company docs, or our docs, (3) Explain what something is, how it works, or look up information, or (4) Synthesize information from multiple sources. Searches in parallel and provides cited answers."
senior-prompt-engineer
by borghei
Expert prompt engineering for LLM applications including prompt design, optimization, RAG systems, agent architectures, and AI product development.
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。
postgresql-table-design
by HermeticOrmus
Design a PostgreSQL-specific schema. Covers best-practices, data types, indexing, constraints, performance patterns, and advanced features
Confidence Check
by SuperClaude-Org
Pre-implementation confidence assessment (≥90% required). Use before starting any implementation to verify readiness with duplicate check, architecture compliance, official docs verification, OSS references, and root cause identification.
rag
by sjtu-sai-agents
Retrieval-Augmented Generation (RAG) system for semantic search and knowledge retrieval. Use when implementing knowledge-grounded AI, building document Q&A systems, or integrating LLMs with external knowledge bases. Supports vector-based similarity search using FAISS and transformer embeddings.
web-search
by bytedance
使用内置 web_search 函数进行网页搜索并返回摘要结果, 准备清晰具体的 query。运行脚本 python scripts/web_search.py "query"。根据返回的摘要列表组织答案，不新增或臆造内容。
image-video-gen
by bytedance
"根据文字描述生成视频，一个生成图片和视频的工作流技能。依赖 skills: web-search, image-generate, video-generate。注意：此 workflow 没有执行脚本，只是一个描述性的文档。"
ai-sdk
by nuxt-content
'Answer questions about the AI SDK and help build AI-powered features. Use when developers: (1) Ask about AI SDK functions like generateText, streamText, ToolLoopAgent, or tools, (2) Want to build AI agents, chatbots, or text generation features, (3) Have questions about AI providers (OpenAI, Anthropic, etc.), streaming, tool calling, or structured output.'