Data Science

This skill should be used when the user asks to "create a plot", "make a chart", "visualize data", "create a heatmap", "make a scatter plot", "plot time series", "create publication figures", "customize plot styling", "use matplotlib", "use seaborn", or needs guidance on Python data visualization, statistical graphics, or figure export.

Eliminate options that violate hard constraints before detailed analysis. Use when: (1) asked to filter ideas against requirements, (2) hard constraints stated and options await triage, (3) many possibilities generated without feasibility assessment, (4) distinguishing non-starters from viable candidates.

Systematically enumerate how code can fail to prevent claiming safety without evidence. Use when: (1) asked to identify failure modes, enumerate risks, or stress-test reliability assumptions, (2) code is characterized as safe or production-ready without enumerated failure scenarios, (3) a code review covers only successful execution paths, (4) changes are ready for approval without failure analysis, (5) code lacks input validation, error handling, or defensive checks, (6) test coverage includes only successful cases.

Strategic analyst that maps competitive landscapes, identifies white space opportunities, and provides positioning recommendations. Use when users need competitive analysis, market positioning strategy, differentiation tactics, or "how do I stand out?" guidance across any domain (portfolios, products, services). NOT for market size estimation or financial forecasting.

Create charts, graphs, and visualizations from data. Use when the user needs to visualize data, create charts, or generate reports with graphics.

Comprehensive web application reconnaissance and mapping coordinator that orchestrates passive browsing, active endpoint discovery, attack surface analysis, and headless browser automation for complete application coverage.

Comprehensive financial statement analysis including ratio calculation, trend analysis, and peer comparison. Evaluates liquidity, profitability, efficiency, and leverage metrics. Requires numpy>=1.24.0, pandas>=2.0.0, matplotlib>=3.7.0. Use when analyzing company fundamentals, comparing financial performance, or conducting equity research.

Python data analysis with pandas, numpy, and analytics libraries

Use when completing implementation, before escalating to human review, or when human checkpoint is reached - performs AI-assisted code review covering security, AI-specific issues, logic errors, and architecture to ensure humans see fresh analysis

Use when user says "generate stories", "brainstorm features", "update story tree", "what should we build", "show story tree", "show me a map", "story map", "tree diagram", "show stories", "view stories", "list stories", or asks for feature ideas or story visualization - autonomously maintains hierarchical story backlog by analyzing git commits, identifying under-capacity nodes, and generating evidence-based stories to fill gaps. Works with SQLite database using closure table pattern, prioritizes shallower nodes first, and tracks implementation status through commit analysis.

Understand the security risks inherent in AI-generated code and vibe coding. Use this skill when you need to understand why AI generates insecure code, statistics on vulnerabilities, real-world breach examples, or overall security awareness for AI-assisted development. Triggers include "vibe coding security", "AI code security", "AI vulnerabilities", "security risks AI code", "why AI insecure", "AI security awareness", "AI generated code risks".

Explain the DAIC (Discuss-Align-Implement-Check) workflow, help users understand current mode, what's allowed in each mode, and how to transition between modes - ANALYSIS-ONLY skill

Master data visualization with chart selection, dashboard design, Tableau, Power BI, and effective data storytelling.

Proactively detect and diagnose DAPR runtime issues based on error patterns, log analysis, and common misconfigurations. Provides immediate solutions for service invocation failures, state management issues, pub/sub problems, and deployment errors. Use when encountering DAPR errors or unexpected behavior.

Build charts and graphs with Chart.js, Recharts, Victory. Line charts, bar charts, pie charts, real-time data visualization. Keywords - charts, graphs, data visualization, chart js, recharts, victory, line chart, bar chart, pie chart

Evaluate extensibility patterns, abstraction layers, and configuration approaches in frameworks. Use when (1) assessing base class/protocol design, (2) understanding dependency injection patterns, (3) evaluating plugin/extension systems, (4) comparing code-first vs config-first approaches, or (5) determining framework flexibility for customization.

Multi-AI code review orchestration using Codex, Gemini, Claude with automatic fallback. Triggers when user requests AI code review, cross-validation, or multi-AI analysis. Integrates with existing auto-ai-review.sh workflow.

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes - four-phase framework (root cause investigation, pattern analysis, hypothesis testing, implementation) that ensures understanding before attempting solutions

Long-running design anthropologist that builds comprehensive visual databases from 500-1000 real-world examples, extracting color palettes, typography patterns, layout systems, and interaction design across any domain (portfolios, e-commerce, SaaS, adult content, technical showcases). This skill should be used when users need exhaustive design research, pattern recognition across large example sets, or systematic visual analysis for competitive positioning.

Visualize datasets in 2D using embeddings with UMAP or t-SNE dimensionality reduction. Use when users want to explore dataset structure, find clusters in images, identify outliers, color samples by class or metadata, or understand data distribution. Requires FiftyOne MCP server with @voxel51/brain plugin installed.