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Found 258 Skills
Test Case Generator - Based on the theories of Equivalence Partitioning and Boundary Value Analysis, generates high-quality test cases in batches by Test Points (POINT), output in Markdown format. Used when users execute the /testcase-gen command or need to generate test cases.
This skill should be used when the user asks to "plan team structure", "determine hiring needs", "design org chart", "calculate compensation", "plan equity allocation", or requests organizational design and headcount planning for a startup.
A Python package useful for chemistry (mainly physical/analytical/inorganic chemistry). Features include balancing chemical reactions, chemical kinetics (ODE integration), chemical equilibria, ionic strength calculations, and unit handling. Use when working with chemical equations, reaction balancing, kinetic modeling, equilibrium calculations, speciation, pH calculations, ionic strength, activity coefficients, or chemical formula parsing.
Master the essential audio post-production techniques—normalization, compression, EQ, and noise reduction—using the correct processing order to achieve professional-quality audio. Use when: Editing podcast episodes or video soundtracks; Cleaning up recorded voiceovers; Improving audio quality for marketing content; Preparing audio files for distribution; Troubleshooting common audio issues
Apply signaling theory (Spence, 1973) to analyze how agents communicate private information through costly, credible signals under information asymmetry. Use this skill when the user needs to evaluate whether a corporate action serves as a credible signal, analyze dividend or IPO signaling, assess separating vs pooling equilibria, or when they ask 'why do firms pay dividends', 'is this signal credible', or 'how does underpricing signal quality'.
Analyze compensation — benchmarking, band placement, and equity modeling. Trigger with "what should we pay a [role]", "is this offer competitive", "model this equity grant", or when uploading comp data to find outliers and retention risks.
Router skill for LLMQuant equities workflows. Use when the user needs stock analysis, equity comparison, research memos, merger-arb memos, or sell/take-profit work.
Use this skill when working with symbolic mathematics in Python. This skill should be used for symbolic computation tasks including solving equations algebraically, performing calculus operations (derivatives, integrals, limits), manipulating algebraic expressions, working with matrices symbolically, physics calculations, number theory problems, geometry computations, and generating executable code from mathematical expressions. Apply this skill when the user needs exact symbolic results rather than numerical approximations, or when working with mathematical formulas that contain variables and parameters.
Systematic multi-factor stock screening using formal factor models to identify stocks with favorable factor exposures. Use when the user asks about factor investing, multi-factor screening, value/momentum/quality factor analysis, factor scoring, factor timing, smart beta strategies, quantitative stock screening, or systematic equity selection based on academic factors.
Use when extracting entities and relationships, building ontologies, compressing large graphs, or analyzing knowledge structures - provides structural equivalence-based compression achieving 57-95% size reduction, k-bisimulation summarization, categorical quotient constructions, and metagraph hierarchical modeling with scale-invariant properties. Supports recursive refinement through graph topology metrics including |R|/|E| ratios and automorphism analysis.
Implements comprehensive backtesting capabilities for Pine Script indicators and strategies. Use when adding performance metrics, trade analysis, equity curves, win rates, drawdown tracking, or statistical validation. Triggers on "backtest", "performance", "metrics", "win rate", "drawdown", or testing requests.
Comprehensive equity research snapshot — integrates analyst consensus estimates, company fundamentals (revenue / profit / valuation), 60-day price history, and recent major news to produce an investment research snapshot similar to a sell-side equity research brief. Triggers: "股票研究", "个股分析", "研究报告", "个股快照", "综合分析", "股票调研", "股票深度", "個股分析", "研究報告", "個股快照", "綜合分析", "股票研究", "stock research", "equity research", "stock analysis", "research snapshot", "investment brief", "stock deep dive", "comprehensive analysis", "NVDA research", "700.HK analysis".