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Found 1,067 Skills
Build Retrieval-Augmented Generation (RAG) applications that combine LLM capabilities with external knowledge sources. Covers vector databases, embeddings, retrieval strategies, and response generation. Use when building document Q&A systems, knowledge base applications, enterprise search, or combining LLMs with custom data.
Use when debates are trapped in false dichotomies, polarized positions need charitable interpretation, tradeoffs are obscured by binary framing, synthesis beyond 'pick one side' is needed, or when users mention steelman arguments, thesis-antithesis-synthesis, Hegelian dialectic, third way solutions, or resolving seemingly opposed principles.
Detect sector rotation signals by analyzing macroeconomic indicators and business cycle positioning to identify which sectors are likely to outperform or underperform over the next 6–12 months. Use when the user asks about sector rotation, macro-driven sector allocation, business cycle investing, which sectors to overweight or underweight, interest rate impact on sectors, inflation plays, or macro investment strategy.
Use when analyzing markets or interpreting charts - applies technical indicators (RSI, MACD, Moving Averages), identifies support/resistance, analyzes multi-timeframe trends, checks fundamentals and sentiment. Activates when user says "analyze BTC", "what's the trend", "check this chart", mentions ticker symbols, or uses /trading:analyze command.
Create, edit, and analyze office documents (PDF, DOCX, PPTX, XLSX). Use when working with PDFs, Word documents, PowerPoint presentations, or Excel spreadsheets. Covers text extraction, form filling, document creation, and data analysis.
Audit-style editing pass for `output/DRAFT.md`: remove template boilerplate, improve coherence, and enforce citation anchoring. **Trigger**: polish draft, de-template, coherence pass, remove boilerplate, 润色, 去套话, 去重复, 统一术语. **Use when**: a first-pass draft exists but reads like scaffolding (repetition/ellipsis/template phrases) or needs a coherence pass before global review/LaTeX. **Skip if**: the draft already reads human-grade and passes quality gates; or prose is not approved in `DECISIONS.md`. **Network**: none. **Guardrail**: do not add/remove/invent citation keys; do not move citations across subsections; do not change claims beyond what existing citations support.
Production-ready SAP BTP best practices for enterprise architecture, account management, security, and operations. Use when planning BTP implementations, setting up account hierarchies, configuring environments, implementing authentication, designing CI/CD pipelines, establishing governance, building Platform Engineering teams, implementing failover strategies, or managing application lifecycle on SAP BTP. Keywords: SAP BTP, account hierarchy, global account, directory, subaccount, Cloud Foundry, Kyma, ABAP, SAP Identity Authentication, CI/CD, governance, Platform Engineering, failover, multi-region, SAP BTP best practices
Backtest trading strategies on historical data and interpret performance metrics. Provides run_backtest (crypto strategies) and run_prediction_market_backtest (Polymarket strategies). Fast execution (20-60s), minimal cost ($0.001). Returns Sharpe ratio, max drawdown, win rate, profit factor, and trade statistics. Use this skill after building or improving strategies to validate performance before deploying. NEVER deploy without thorough backtesting (6+ months recommended).
Build discounted cash flow (DCF) valuation models in Excel. Use when creating DCF models, calculating enterprise value, or valuing companies. Trigger with phrases like 'excel dcf', 'build dcf model', 'calculate enterprise value'.
Comprehensive Terraform infrastructure-as-code skill covering providers, resources, modules, state management, and enterprise patterns for multi-cloud infrastructure
Comprehensive AWS cloud services skill covering S3, Lambda, DynamoDB, EC2, RDS, IAM, CloudFormation, and enterprise cloud architecture patterns with AWS SDK
Industry-standard gradient boosting libraries for tabular data and structured datasets. XGBoost and LightGBM excel at classification and regression tasks on tables, CSVs, and databases. Use when working with tabular machine learning, gradient boosting trees, Kaggle competitions, feature importance analysis, hyperparameter tuning, or when you need state-of-the-art performance on structured data.