全部能力

Build RAG (Retrieval Augmented Generation) pipelines with web search and LLMs. Tools: Tavily Search, Exa Search, Exa Answer, Claude, GPT-4, Gemini via…

Qdrant provides client SDKs for various programming languages, allowing easy integration with Qdrant deployments.

钉钉 AI 表格（多维表格）操作。当用户提到"钉钉AI表格"、"AI表格"、"多维表格"、"工作表"、"字段"、"记录"、"新增记录"、"查询记录"、"更新记录"、"删除记录"、"新建字段"、"删除字段"、"dingtalk AI table"、"dingtalk…

Read Twitter/X for financial research using opencli (read-only). Use this skill whenever the user wants to read their Twitter feed, search for financial tweets, view bookmarks, look up user profiles, or gather market sentiment from Twitter/X. Triggers include: "check my feed", "search Twitter for", "show my bookmarks", "who follows", "look up @user", "what's trending about", "market sentiment on Twitter", "what are people saying about AAPL", "recent tweets from @elonmusk", "show me @user's posts", "fintwit", any mention of Twitter/X in context of reading financial news or market research. This skill is READ-ONLY — it does NOT support posting, liking, retweeting, or any write operations.

Configure GOB local file storage for GrepAI. Use this skill for simple, single-machine setups.

Write publication-ready ML/AI papers for NeurIPS, ICML, ICLR, ACL, AAAI, COLM. Use when drafting papers from research repos, structuring arguments, verifying…

You are a documentation expert specializing in creating comprehensive, maintainable documentation from code. Generate API docs, architecture diagrams, user…

Optimize for search engine visibility, ranking, and AI citations. Use when asked to improve SEO, optimize for search, fix meta tags, add structured data, or…

Comprehensive scientific literature search across PubMed, arXiv, bioRxiv, medRxiv. Natural language queries powered by Valyu semantic search.

Complete biomedical information search combining PubMed, preprints, clinical trials, and FDA drug labels. Powered by Valyu semantic search.

掌握 OpenAPI 3.1 的 API 文档编写，结合 AI 驱动工具与现代开发者体验实践。创建交互式文档，生成 SDK，并构建…

Write a detailed component specification including props, states, variants, accessibility requirements, and usage guidelines.

You are a documentation expert specializing in creating comprehensive, maintainable documentation from code. Generate API docs, architecture diagrams, user…

B2B case study writing with STAR framework, data visualization, and research. Covers structure, customer quotes, metrics presentation, and distribution…

Sports news via RSS/Atom feeds and Google News. Fetch headlines, search by query, filter by date. Covers football news, transfer rumors, match reports, and any sport via Google News. Use when: user asks for recent news, headlines, transfer rumors, or articles about any sport. Good for "what's the latest on [team/player]" questions. Supports any Google News query and curated RSS feeds (BBC Sport, ESPN, The Athletic, Sky Sports). Don't use when: user asks for structured data like standings, scores, statistics, or xG — use the sport-specific skill instead: football-data (soccer), nfl-data (NFL), nba-data (NBA), wnba-data (WNBA), nhl-data (NHL), mlb-data (MLB), tennis-data (tennis), golf-data (golf), cfb-data (college football), cbb-data (college basketball), or fastf1 (F1). Don't use for prediction market odds — use polymarket or kalshi. News results are text articles, not structured data.

Cubox CLI is a callable personal reading memory system that enables you to search, read, and use saved content, perform semantic (RAG-based) queries, access…

Visualizes Azure infrastructure from ARM templates, Azure CLI, or descriptions. Use when user has Azure resources to diagram.

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.

Use when auditing the codebase through the evaluation platform with mandatory research, coordinated domain audit workers, and structured summaries.

Research agent for external documentation, best practices, and library APIs via MCP tools