Loading...
Loading...
Found 171 Skills
Druckenmiller Strategy Synthesizer - Integrates 8 upstream skill outputs (Market Breadth, Uptrend Analysis, Market Top, Macro Regime, FTD Detector, VCP Screener, Theme Detector, CANSLIM Screener) into a unified conviction score (0-100), pattern classification, and allocation recommendation. Use when user asks about overall market conviction, portfolio positioning, asset allocation, strategy synthesis, or Druckenmiller-style analysis. Triggers on queries like "What is my conviction level?", "How should I position?", "Run the strategy synthesizer", "Druckenmiller analysis", "総合的な市場判断", "確信度スコア", "ポートフォリオ配分", "ドラッケンミラー分析".
Systematic 7-step methodology for comprehensive patent prior art searches and patentability assessments using BigQuery and CPC classification
Core ML, Create ML, Vision framework, Natural Language framework, on-device ML integration. Use when user wants image classification, text analysis, object detection, sound classification, model optimization, or custom model integration. Covers Core ML vs Foundation Models decision.
Resolve merge conflicts systematically with context-aware 3-tier classification and escalation protocol
Reddit community moderation via PRAW with LLM-powered report classification: fetch modqueue, classify reports against subreddit rules and author history, and take mod actions (approve, remove, lock). Supports interactive, auto, and dry-run modes.
4-phase code review methodology: UNDERSTAND changes, VERIFY claims against code, ASSESS security/performance/architecture risks, DOCUMENT findings with severity classification. Use when reviewing pull requests, auditing code before release, evaluating external contributions, or pre-merge verification. Use for "review PR", "code review", "audit code", "check this PR", or "review my changes". Do NOT use for writing new code or implementing features.
Customer query skill. Suitable for requirements such as searching customer lists by keywords and obtaining customer GTMs classifications. This skill is used when users need to: (1) Search for customers by keyword, (2) Obtain the list of GTM business lines.
Analyze inventory health using turnover ratios, ABC classification, safety stock calculations, and stockout vs overstock diagnostics. Use this skill when the user needs to optimize inventory levels, reduce carrying costs, prevent stockouts, or classify products by inventory priority — even if they say 'we have too much stock', 'we keep running out of bestsellers', 'how much safety stock do we need', or 'which products should we focus on'.
Drug regulatory and approval research -- FDA substance registry lookup, drug classification by ATC/EPC/MoA via RxClass, Orange Book generic availability and patent status, DailyMed label parsing (adverse reactions, dosing, contraindications), and clinical trial search. Use when users ask about FDA-approved drugs, drug regulatory status, generic availability, patent expiration, drug class membership, drug labeling, or substance identification.
/cs:caio-review <plan> — Eval-demanding Chief AI Officer interrogation of any plan that involves AI: model selection, risk classification, cost economics, or AI hiring.
BaoStock A-share Data Platform, free and open-source, supports queries for stock quotes, K-lines, financial data, industry classification, and index constituent stocks; used when users need to obtain A-share historical quotes, financial statements, trading calendars and other data
Guide for building Graph Neural Networks with PyTorch Geometric (PyG). Use this skill whenever the user asks about graph neural networks, GNNs, node classification, link prediction, graph classification, message passing networks, heterogeneous graphs, neighbor sampling, or any task involving torch_geometric / PyG. Also trigger when you see imports from torch_geometric, or the user mentions graph convolutions (GCN, GAT, GraphSAGE, GIN), graph data structures, or working with relational/network data. Even if the user just says 'graph learning' or 'geometric deep learning', use this skill.