Data Science

Expert interior designer with deep knowledge of space planning, color theory (Munsell, NCS), lighting design (IES standards), furniture proportions, and AI-assisted visualization. Use for room layout optimization, lighting calculations, color palette selection for interiors, furniture placement, style consultation. Activate on "interior design", "room layout", "lighting design", "furniture placement", "space planning", "Munsell color". NOT for exterior/landscape design, architectural structure, web/UI design (use web-design-expert), brand color theory (use color-theory-palette-harmony-expert), or building codes/permits.

Statistical analysis methods, hypothesis testing, and probability for data analytics

Use when working with SQLite databases in DataPeeker analysis sessions - querying data, importing CSVs, exploring schemas, formatting output, or optimizing performance. Provides task-oriented guidance for effective SQLite CLI usage in data analysis workflows.

Intelligent task routing and agent selection based on task analysis. Determines optimal agent for execution based on keywords and complexity. Keywords - route task, select agent, task routing, agent selection, workflow routing, task assignment, dispatch task

Expert in 2000s-era music visualization (Milkdrop, AVS, Geiss) and modern WebGL implementations. Specializes in Butterchurn integration, Web Audio API AnalyserNode FFT data, GLSL shaders for audio-reactive visuals, and psychedelic generative art. Activate on "Milkdrop", "music visualization", "WebGL visualizer", "Butterchurn", "audio reactive", "FFT visualization", "spectrum analyzer". NOT for simple bar charts/waveforms (use basic canvas), video editing, or non-audio visuals.

Analyze fundamental data primitives, type systems, and state management patterns in a codebase. Use when (1) evaluating typing strategies (Pydantic vs TypedDict vs loose dicts), (2) assessing immutability and mutation patterns, (3) understanding serialization approaches, (4) documenting state shape and lifecycle, or (5) comparing data modeling approaches across frameworks.

Comprehensive portfolio analysis using Alpaca MCP Server integration to fetch holdings and positions, then analyze asset allocation, risk metrics, individual stock positions, diversification, and generate rebalancing recommendations. Use when user requests portfolio review, position analysis, risk assessment, performance evaluation, or rebalancing suggestions for their brokerage account.

Master data manipulation, analysis, and visualization with Pandas, NumPy, and Matplotlib

Provides detailed file statistics including lines, size, and modification time when user asks for file info or stats

Analyzes bear-put-spread debit spreads for bearish directional plays with defined risk. Requires numpy>=1.24.0, pandas>=2.0.0, matplotlib>=3.7.0, scipy>=1.10.0. Use when expecting moderate price decline, comparing put spread configurations, analyzing debit spread opportunities, or evaluating defined-risk bearish positions on mid to large-cap stocks.

Execute tests with coverage analysis using bmad-commands, identify coverage gaps, and suggest missing tests. This skill should be used for test execution and quality validation.

Apply Edward de Bono's Six Thinking Hats methodology to software testing for comprehensive quality analysis. Use when designing test strategies, conducting test retrospectives, analyzing test failures, evaluating testing approaches, or facilitating testing discussions. Each hat provides a distinct testing perspective: facts (White), risks (Black), benefits (Yellow), creativity (Green), emotions (Red), and process (Blue).

Design computational models for cognitive simulation and analysis.

Specialized knowledge for real estate marketing analytics, including SEM campaign optimization, lead generation analysis, marketing channel performance, and geographic market insights. Use when working with real estate marketing data, Snowflake databases (RDC_ANALYTICS, RDC_MARKETING schemas), analyzing paid search campaigns, lead pricing trends, conversion funnels, or cross-channel attribution. Triggers include queries about Google Ads performance, lead quality analysis, market-level metrics, campaign budget optimization, or any real estate marketing KPIs.

Comprehensive code review framework for evaluating implementations against plans, requirements, and quality standards. Provides structured analysis with prioritized, actionable feedback.

Systematic debugging methodology, root cause analysis, performance profiling, and troubleshooting strategies for JavaScript and web applications. Covers VSCode debugging tools, console techniques, and professional debugging workflows.

Scrape and analyze Reddit for real user signals about product viability, pain severity, willingness to pay, and competitor saturation. Validate product ideas before building by systematically analyzing discussions, complaints, feature requests, and purchasing behavior across relevant subreddits. Integrates with Firecrawl for scraping, Supabase for storage, and Superset for trend visualization.

Performance measurement, attribution modeling, and marketing ROI analysis. Use when setting up tracking, analyzing campaign performance, building attribution models, or creating marketing reports.

Route-aware gap analysis. For Brownfield - uses /speckit.analyze to compare specs against implementation. For Greenfield - validates spec completeness and asks about target tech stack for new implementation. This is Step 4 of 6 in the reverse engineering process.

Use when analyzing website traffic, investigating SEO issues, diagnosing high bounce rates, evaluating content performance, or optimizing site conversions - proactive SEO consultant with Plausible Analytics access that investigates patterns, fetches actual page content, and provides specific actionable recommendations based on real data analysis