Loading...
Loading...
Found 31 Skills
Custom Watchlist Tracking Radar. Monitors users' custom watchlists and generates scheduled morning/evening briefings. Based on the Longbridge Open Platform, it scans 7-dimensional catalyst signals including earnings beats, policy changes, abnormal capital flows, insider trading, and analyst rating changes, and generates pre-market/post-market incremental briefings grouped by market. Supports four markets: US stocks, A-shares, Hong Kong stocks, and Singapore stocks. This skill is triggered when users ask investment-related questions such as "What should I pay attention to today?", "Show me the morning briefing", "Morning report", "Evening report", "Review", "Any news on my watchlist", "morning briefing", "catalyst update", etc.
Zoho Catalyst integration. Manage data, records, and automate workflows. Use when the user wants to interact with Zoho Catalyst data.
Build and maintain a calendar of upcoming catalysts across a coverage universe — earnings dates, conferences, product launches, regulatory decisions, and macro events. Helps prioritize attention and position ahead of events. Triggers on "catalyst calendar", "upcoming events", "what's coming up", "earnings calendar", "event calendar", or "catalyst tracker".
Structure multi-POV stories through catalyst environments. Use when building interconnected narratives, when perspectives need meaningful intersection, or when a shared setting needs to generate distinct storylines.
Market intelligence: strategy screener, popularity rankings, top movers with news correlation, quote anomalies, index/ETF constituent stocks, morning briefings, catalyst monitoring for watchlist, event-driven strategies, ETF fund flows, sector rotation, market microstructure, supply chain analysis, industry overviews, and ARK-style disruptive innovation analysis. Triggers: "筛选", "策略筛选", "排行", "热度", "异动", "成分股", "晨报", "早报", "催化剂", "事件驱动", "ETF资金流", "板块轮动", "产业链", "行业概览", "颠覆式创新", "ARK", "篩選", "排行", "異動", "成分股", "晨報", "ETF資金流", "板塊輪動", "產業鏈", "screener", "rank", "anomaly", "constituent", "morning brief", "catalyst", "event strategy", "ETF flow", "ETF资金流", "ETF申赎", "ETF資金流", "etf flow", "资金申赎", "etf 资金", "sector rotation", "supply chain", "ARK", "disruptive innovation", "板块筛选", "行业筛选", "板塊篩選", "強勢板塊", "弱勢板塊", "top sectors", "催化劑", "事件驅動", "行業概覽", "顛覆式創新", "策略篩選", "熱度"
Terramate CLI, Cloud, and Catalyst best practices and usage guides. This skill should be used when working with Terramate stacks, orchestration, code generation, Cloud integration, or Catalyst components and bundles.
Native macOS development with AppKit, Catalyst, and macOS-specific APIs. Use when building Mac-native apps, menu bar apps, system extensions, or macOS-specific features.
Batch identify candidate stocks with mature breakout patterns, healthy volume-price structures, and good catalyst alignment, and output priorities, trigger conditions, and failure boundaries. Suitable for scenarios such as short-to-medium-term stock selection, pre-market candidate pool sorting, and screening leading candidate stocks in sector rotation.
Maintain and update investment theses for portfolio positions and watchlist names. Track key data points, catalysts, and thesis milestones over time. Use when updating a thesis with new information, reviewing position rationale, or checking if a thesis is still intact. Triggers on "update thesis for [company]", "is my thesis still intact", "thesis check", "add data point to [company]", or "review my positions".
Access PUDL table data plus table/column/source metadata in Jupyter or Marimo notebooks for debugging and visualization. Use when users ask what a table contains, how to read it, or how columns are defined.
Explore and query any dataset annotated with a Frictionless Data Package descriptor (datapackage.json). Use this skill whenever a user wants to discover what tables or resources a dataset contains, look up column names and descriptions, surface usage warnings embedded in metadata, or understand how to load data from Parquet files, DuckDB or SQLite databases, or CSV files described by a datapackage.json. Also use when the user has a datapackage.json and wants to know what's in it, how to query it efficiently, or how to connect its metadata to actual data files. Pairs well with dataset-specific skills (like `pudl`) that layer domain knowledge on top.
Automates Apple Voice Memos (Mac Catalyst, no dictionary) via JXA using filesystem/SQLite access and System Events UI scripting. Use when asked to "automate Voice Memos", "export voice recordings", "access Voice Memos database", or "transcribe voice memos".