全部能力

智能多主题深度研究工具，支持任意材料输入，使用独立研究 Agent进行并行深度检索并生成系统化研究文档。本技能应在用户需要深度研究多个相关课题、进行系统性信息检索、整合多角度分析时使用。

Search your personal knowledge base when past insights would improve response. Recognize when stored breakthroughs, decisions, or solutions are relevant.…

Use this skill when gathering knowledge at scale before making decisions - technology evaluation, SOTA analysis, codebase archaeology, competitive analysis, or…

Generate a concise 4-5 page equity research earnings preview for a single company. Analyzes the most recent earnings transcript, competitor landscape,…

Conduct comprehensive literature reviews using multi-perspective dialogue simulation. Generate diverse expert personas, conduct grounded Q&A conversations, and…

Create institutional-quality equity research initiation reports through a 5-task workflow. Tasks must be executed individually with verified prerequisites -…

Retrieve real-time commodity price quotes using Octagon MCP. Use when checking current commodity prices, analyzing day ranges, comparing to moving averages,…

Semantic search skill using Exa API for embeddings-based search, similar content discovery, and structured research. Use when you need semantic search, find…

Make a demo of a research paper in a marimo notebook fully automatically without extra user input.

Comprehensive Tailwind CSS v4 documentation snapshot and workflow guidance. Use when answering Tailwind v4 questions, selecting utilities/variants, configuring…

Polymarket sports prediction markets — live odds, prices, order books, events, series, and market search. No auth required. Covers NFL, NBA, MLB, football (EPL, UCL, La Liga), tennis, cricket, MMA, esports. Supports moneyline, spreads, totals, and player props. Use when: user asks about sports betting odds, prediction markets, win probabilities, market sentiment, or "who is favored to win" questions. Don't use when: user asks about actual match results, scores, or statistics — use the sport-specific skill: 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 historical match data. Don't use for news — use sports-news instead. Don't confuse with Kalshi — Polymarket focuses on crypto-native prediction markets with deeper sports coverage; Kalshi is a US-regulated exchange with different market structure.

搜索飞书云文档、消息和应用。当用户请求"搜索文档"、"搜索消息"、"搜索应用"、"找文档"、 "找一下"、"search docs"、"查找飞书文档"、"有没有关于 xxx 的文档"时使用。 也适用于：用户想查找某个主题的飞书文档或 Wiki、按关键词检索消息记录、查找内部应用。 搜索 API 必须使用 User Access Token，本技能包含完整的认证前置检查流程。

Structure compelling design presentations for stakeholders, reviews, and showcases.

RevenueCat metrics, customer data, and documentation search. Use when querying subscription analytics, MRR, churn, customers, or RevenueCat docs.

Scientific research and analysis skills

Guides MongoDB users through implementing and optimizing Atlas Search (full-text), Vector Search (semantic), and Hybrid Search solutions. Use this skill when users need to build search functionality for text-based queries (autocomplete, fuzzy matching, faceted search), semantic similarity (embeddings, RAG applications), or combined approaches. Also use when users need text containment, substring matching ('contains', 'includes', 'appears in'), case-insensitive or multi-field text search, or filtering across many fields with variable combinations. Provides workflows for selecting the right search type, creating indexes, constructing queries, and optimizing performance using the MongoDB MCP server.

新闻搜索、新闻摘要、新闻汇总、热点新闻、最新新闻、新闻整理、新闻收集。帮你搜索最近几天的相关新闻（12-25条），生成精美的HTML摘要页面，每条新闻都有摘要和AI深度解读功能，自动打开浏览器展示

Search academic literature using Semantic Scholar, arXiv, and OpenAlex APIs. Returns structured JSONL with title, authors, year, venue, abstract, citations,…

Single entry skill for open-websearch setup and focused live retrieval, preferring local CLI/daemon paths while remaining compatible with workspace-exposed MCP…

Use when building ML/AI apps in Rust. Keywords: machine learning, ML, AI, tensor, model, inference, neural network, deep learning, training, prediction,…