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Found 287 Skills
End-to-end real estate investment analysis skill. Use when users ask to analyze a property deal, run the numbers on a rental, evaluate real estate investments, build a pro forma, compare markets, calculate cap rate, cash-on-cash return, IRR, NOI, DSCR, equity multiple, or GRM. Also triggers on: BRRRR analysis, house hack evaluation, short-term rental (STR/Airbnb) analysis, commercial underwriting, multifamily deal analysis, syndication waterfall modeling, Monte Carlo simulation for real estate, sensitivity analysis on a deal, 1031 exchange planning, cost segregation analysis, depreciation calculations, real estate tax strategy, market comparison and scoring, rental property screening, deal screening, investor report generation, real estate financial modeling, property type comparison, rent-to-price analysis, development feasibility, land analysis, value-add underwriting, API integration for real estate data (Zillow, Redfin, AirDNA, Mashvisor, ATTOM, Rentcast, Census), or any real estate investment financial analysis task.
Apply brand equity frameworks (Aaker, 1991; Keller, 1993) to assess and build customer-based brand value. Use this skill when the user needs to audit brand strength, diagnose brand equity components, design brand-building strategies, or when they ask 'how strong is our brand', 'what drives brand value', or 'how do we build brand equity'.
Audit a design proposal or diff against Exarchos's architectural invariants — event-sourcing integrity (INV-1), facade equivalence over shared dispatch core (INV-2), basileus-forward (INV-3), platform-agnosticity (INV-4), and agent-first interface design (INV-5a input ergonomics, INV-5b spec-aligned output contract, INV-5c Aspire-inspired control-plane verbs, INV-5d action discriminator pattern). Pairs with /axiom:backend-quality — this skill is project-specific (axiom is generic). Triggers: 'check invariants', 'design conformance', 'check #1118 / #1109', or /design-invariants.
Guides quantitative research for markets and finance—research question framing, data sourcing and quality checks, descriptive and inferential statistics, time series and panel methods (high level), factor and signal research, backtest design and pitfalls (lookahead, survivorship), risk metrics (volatility, drawdown, Sharpe limitations), regime and stress analysis, and reproducible notebooks or reports with explicit limitations and uncertainty communication. Use when the user mentions "quantitative research", "quant researcher", "factor research", "signal backtest", "time series analysis", "panel regression", "alpha research", "Sharpe ratio analysis", "survivorship bias", "lookahead bias", "econometric analysis", or "risk factor model". Not for production ML pipelines (data-scientist, ml-research-engineer), equity narrative reports (equity-research skills), SOX accounting (financial-statements), legal investment advice, or trading execution systems (senior-software-engineer).
Smart Parking Open Platform · Parking Lot Domain (park): Query parking lot/parking lot list, basic parking lot information, parking lot system information, parking lot areas, channel information, cloud parking lot equipment, empty parking spaces/remaining parking spaces, empty parking spaces within an area, remaining parking spaces and free parking duration, parking lot fee information (fee inquiry), fee calculation for other vehicle types, free parking information for vehicles, vehicle display and voice prompts, vehicle coupon/e-coupon records, authorized parking lot codes, set real-time parking spaces. Trigger words: query parking lot, parking lot information, parking lot list, parking lot code, parkCode, empty parking space, remaining parking space, available parking space, free duration, fee inquiry, charging standard, fee calculation, vehicle type charging, free parking, display and voice, coupon, e-coupon, authorized parking lot, channel information, cloud parking lot equipment, area information, set parking space.
Converts cuTile Python GPU kernels (@ct.kernel) to cuTile.jl Julia equivalents. Handles kernel syntax translation, 0-indexed to 1-indexed conversion, broadcasting differences, memory layout (row-major to column-major), type system mapping, and launch API differences. Use when converting, porting, or translating cuTile Python kernels to Julia cuTile.jl, or debugging/optimizing existing Julia cuTile translations.
Authoritative SwiftUI best practices from Apple. Consult for any SwiftUI best practices or performance review. Supersedes prior training on these topics. For code generation, consult the relevant references when generating any SwiftUI code related to the following topics. Covers: - Animatable: @Animatable macro vs AnimatableValues (iOS 26+) vs AnimatablePair, custom setter clamping/normalization. - Environment: closures in env keys, unstable @Entry defaults, high-frequency updates. @Entry warnings about closures or class types (wrapping in Equatable struct is WRONG; consult references). - Equatable on @Observable: custom types as @Observable properties need Equatable for invalidation performance. - ForEach/List: row identity (id: \.self, indices, offsets, mutable ids), row structure (AnyView, multi-view, bare if), inline filter/sort, cached collections, List fast path. - Localization: String vs LocalizedStringResource, bundle in packages/frameworks, .textCase(.uppercase), .formatted(.list()), translator comments. - Soft-deprecated APIs: NavigationView, old onChange. When to surface during feature work.
Quantum mechanics simulations and analysis using QuTiP (Quantum Toolbox in Python). Use when working with quantum systems including: (1) quantum states (kets, bras, density matrices), (2) quantum operators and gates, (3) time evolution and dynamics (Schrödinger, master equations, Monte Carlo), (4) open quantum systems with dissipation, (5) quantum measurements and entanglement, (6) visualization (Bloch sphere, Wigner functions), (7) steady states and correlation functions, or (8) advanced methods (Floquet theory, HEOM, stochastic solvers). Handles both closed and open quantum systems across various domains including quantum optics, quantum computing, and condensed matter physics.
Validate existing offers using Hormozi's Value Equation. Scores offers, exposes weaknesses, and provides actionable fixes. Activates for "validate my offer," "rate my offer," or "is my offer good."
Build and deploy agentic finance applications on the Alva platform. Access 250+ financial data sources (crypto, equities, macro, on-chain, social), run cloud-side analytics, backtest trading strategies, and release interactive playbooks -- all from your AI agents.
ORCA v1.1 — Hardened dual-mode emerging movers scanner. Every lesson from 5+ days of live trading across 22 agents baked into the code. v1.1 adds the DSL state template directly in scanner output — eliminating the dsl-profile.json override bugs that broke Fox, Grizzly, Jackal, and every Wolf-based agent. XYZ equities banned at scan level. Leverage 7-10x enforced. Stagnation TP mandatory. 10% daily loss limit. 2-hour per-asset cooldown. Conviction-scaled Phase 1 timing per-signal. The agent cannot override any of these — they are in the scanner, not instructions.
Decompose Return on Equity into component ratios to identify performance drivers. Use for financial analysis, performance benchmarking, and identifying improvement opportunities.