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Found 279 Skills
Use this skill when benchmarking compensation, designing equity plans, building leveling frameworks, or structuring total rewards. Triggers on compensation benchmarking, equity grants, stock options, leveling, pay bands, total rewards, salary ranges, and any task requiring compensation strategy or structure design.
Use when you want to retrieve quantitative RNA expression data and variant eQTL information from the GTEx (Genotype-Tissue Expression) Project across 54 non-diseased tissue sites.
Connect GWAS variants to biological pathways for drug target discovery. Maps disease-associated SNPs to causal genes via eQTL colocalization (GTEx), links genes to enriched pathways (Reactome, KEGG, MetaCyc), and identifies druggable targets within disease-relevant pathways. Use when asked to translate GWAS findings into mechanistic insights, find pathways enriched for disease genes, discover drug targets from genetic evidence, or answer questions like "What pathways are disrupted in type 2 diabetes based on GWAS data?"
Use this skill when implementing AI, AIController, behavior tree, blackboard, AI perception, NavMesh, EQS, navigation, pathfinding, State Tree, or Smart Objects in Unreal Engine. See references/behavior-tree-patterns.md for BT patterns and references/eqs-reference.md for EQS configuration. For AI ability use, see ue-gameplay-abilities.
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'.
Router skill for LLMQuant equity derivatives workflows. Use when the user needs single-stock derivative, convertible, warrant, structured payoff, or hybrid security analysis.
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.
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.
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.
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.
Apply basic game theory concepts including Nash equilibrium, dominant strategies, and the Prisoner's Dilemma to analyze strategic interactions. Use this skill when the user needs to model competitive decisions, predict rival behavior, design incentive mechanisms, or evaluate cooperation vs competition scenarios — even if they say 'what will our competitor do', 'should we cooperate or compete', or 'how do we set up the right incentives'.
TrueNorth market intelligence for crypto, top 300 US equities, and commodities: technical analysis (RSI, MACD, Bollinger Bands), derivatives (funding rates, open interest), DeFi (TVL, fees), token performance, events, liquidation risk, token unlock, stock prices, financial statements, analyst estimates, commodity prices (gold, oil, gas), and more.