向量嵌入
向量检索与嵌入工作流
perplexity
G1Joshi
Perplexity AI search and research. Use for AI search.
local-pois
brave
USE FOR getting local business/POI details. Requires POI IDs obtained from web-search (with result_filter=locations). Returns full business information including ratings, hours, contact info. Max 20 IDs.
answers
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."
suggest
brave
USE FOR query autocomplete/suggestions. Fast (<100ms). Returns suggested queries as user types. Supports rich suggestions with entity info. Typo-resilient.
spellcheck
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.
local-descriptions
brave
USE FOR getting AI-generated POI text descriptions. Requires POI IDs obtained from web-search (with result_filter=locations). Returns markdown descriptions grounded in web search context. Max 20 IDs per request.
investigate-pylon
lightdash
Investigate a Pylon support ticket. Use when asked to investigate, triage, or look into a Pylon issue. Classifies the ticket, searches for existing GitHub/Linear issues, searches docs, inspects code if needed, and drafts a customer reply.
yelp-search
letta-ai
Search Yelp for local businesses, get contact info, ratings, and hours. Use when finding services (cleaners, groomers, restaurants, etc.), looking up business phone numbers to text, or checking ratings before booking. Triggers on queries about finding businesses, restaurants, services, or "look up on Yelp".
web-search
RTGS2017
网络搜索和信息检索技能。用于搜索网页、查询实时信息、获取新闻资讯。当用户询问需要联网查询的问题、最新信息或实时数据时使用。
meta-searching
shrwnsan
Extracts web content and performs reliable searches when standard tools fail due to access restrictions, rate limiting, or validation errors. Use when encountering 403/429/422 errors, blocked documentation sites, or silent search failures. Direct tool execution often fails for these scenarios - search-plus agent delegation provides the most reliable results.
agentgo
liliang-cn
Use AgentGo for local RAG (Retrieval Augmented Generation) operations including document ingestion, semantic search, and Q&A. Supports multi-provider LLM, MCP tools, Skills, and cognitive memory (Hindsight/PageIndex). Use when building local knowledge bases, AI assistants with evolving long-term memory.
microsoft-docs
MicrosoftDocs
Query official Microsoft documentation to understand concepts, find tutorials, and learn how services work. Use for Azure, .NET, Microsoft 365, Windows, Power Platform, and all Microsoft technologies. Get accurate, current information from learn.microsoft.com and other official Microsoft websites—architecture overviews, quickstarts, configuration guides, limits, and best practices.
mapbox-search-integration
mapbox
Complete workflow for implementing Mapbox search in applications - from discovery questions to production-ready integration with best practices
chai1
BioTender-max
Structure prediction for protein, nucleic-acid, and small-molecule complexes with the Chai-1 foundation model (Chai Discovery 2024, github.com/chaidiscovery/chai-lab). Reach for this skill to predict an antibody-antigen or protein-ligand complex from a single FASTA, to re-fold designed binders as an AlphaFold-multimer alternative, or to drive co-folding from Python for batched campaigns on a GPU.
PostgreSQL Semantic Search
laguagu
Claude Code skills for AI apps • Next.js 16 • AI SDK 6 • pgvector • bun • Ralph Loop
llm-context
brave
USE FOR RAG/LLM grounding. Returns pre-extracted web content (text, tables, code) optimized for LLMs. GET + POST. Adjust max_tokens/count based on complexity. Supports Goggles, local/POI. For AI answers use answers. Recommended for anyone building AI/agentic applications.
embedding-pipeline-builder
patricio0312rev
Builds document embedding pipelines with text chunking, embedding generation, indexing, and retrieval optimization. Use when users request "embedding pipeline", "document indexing", "text chunking", "RAG preprocessing", or "semantic indexing".
rag-pipeline-builder
patricio0312rev
Designs retrieval-augmented generation pipelines for document-based AI assistants. Includes chunking strategies, metadata schemas, retrieval algorithms, reranking, and evaluation plans. Use when building "RAG systems", "document search", "semantic search", or "knowledge bases".
coderlm
JaredStewart
"Primary tool for all code navigation and reading in supported languages (Rust, Python, TypeScript, JavaScript, Go, Java, Scala, SQL). Use instead of Read, Grep, and Glob for finding symbols, reading function implementations, tracing callers, discovering tests, and understanding execution paths. Provides tree-sitter-backed indexing that returns exact source code — full function bodies, call sites with line numbers, test locations — without loading entire files into context. Use for: finding functions by name or pattern, reading specific implementations, answering 'what calls X', 'where does this error come from', 'how does X work', tracing from entrypoint to outcome, and any codebase exploration. Use Read only for config files, markdown, and unsupported languages."
codanna-codebase-intelligence
NickCrew
Use codanna MCP tools for semantic code search, call graphs, and impact analysis before grep/find.
refactor
FradSer
This skill should be used when the user asks to refactor specific files or directories, simplify recently changed code, clean up dead code in a limited scope, or invokes /refactor with paths or semantic queries.
designing-systems
fusengine
Use when creating design systems, tokens, color palettes, typography scales, or theming. Covers OKLCH colors, CSS variables, Tailwind v4 @theme.
theming-tokens
fusengine
Use when creating theme systems, color variables, or design system tokens. Covers primitives, semantic, and component tokens.
notion-research-documentation
Prat011
Searches across your Notion workspace, synthesizes findings from multiple pages, and creates comprehensive research documentation saved as new Notion pages. Turns scattered information into structured reports with proper citations and actionable insights.