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Found 68 Skills
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".
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"
Build and maintain a Stockbee-style daily 20% mover study for US equities by scanning +20%/-20% movers, classifying catalysts and setup context, updating forward outcomes, and summarizing cohort patterns. Use when the user asks to run a daily 20% study, backfill historical 20% movers, find recurring edge patterns, or build a model book of explosive market moves.
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.
Compare the differences in business quality, growth, profitability, valuation and catalysts of peer candidate companies horizontally, and provide conclusions on relative strengths and weaknesses. It is applicable to scenarios such as choosing between two candidate stocks, selecting the best among peers in an industry, and establishing a priority tracking order.
Totango platform help — SuccessBLOCs, SuccessPlays, Health Scores, Customer 360, Touchpoints, Customer Data Hub, Unison AI, Catalyst, email campaigns, REST API. Use when implementation is taking too long and you need a setup plan, SuccessPlays aren't triggering or running on the wrong accounts, health scores don't match actual churn risk, integrations keep breaking or disconnecting from Salesforce or HubSpot, reports and dashboards feel rigid and you can't build custom views, Totango API returns errors or you need to query accounts, or you're migrating to Totango from Gainsight or ChurnZero. Do NOT use for general customer success strategy (use /sales-customer-success) or NPS/CSAT survey methodology (use /sales-customer-feedback).
Router skill for LLMQuant event workflows. Use when the user needs earnings event briefs, M&A tracking, regulatory risk, catalysts, event calendars, or cross-asset event impact.
Investment proposal generation via Longbridge Securities — produces a structured investment memo covering: executive summary, company overview, investment thesis (3–5 core points), financial analysis, valuation, catalysts and timeline, risk factors, and position recommendation. Triggers: "投资提案", "投资建议书", "投资报告", "投资摘要", "核心逻辑", "投资理由", "建仓建议", "投資提案", "投資建議書", "投資報告", "投資摘要", "核心邏輯", "建倉建議", "investment proposal", "investment memo", "investment summary", "investment rationale", "position recommendation", "investment case", "buy memo".
Apple Human Interface Guidelines for Mac. Use when building macOS apps with SwiftUI or AppKit, implementing menu bars, toolbars, window management, or keyboard shortcuts. Triggers on tasks involving Mac UI, desktop apps, or Mac Catalyst.
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".
Event-driven investment strategy — identify and analyse corporate events (M&A, spinoffs, buybacks, index rebalancing, lockup expiry) that create pricing dislocations. Framework: event identification → sentiment scoring → historical price reaction → position sizing. Uses Longbridge news / filings / calendar data as signal inputs. Triggers: "事件驱动", "并购套利", "指数调整", "解禁套利", "事件策略", "公司事件策略", "事件投资", "套利机会", "事件驅動", "並購套利", "指數調整", "解禁套利", "事件策略", "公司事件策略", "event-driven", "event strategy", "merger arbitrage", "index rebalancing", "lockup expiry", "event investing", "corporate event trading", "special situation", "spinoff", "buyback catalyst".