數據科學

Use when analyzing failures, outages, incidents, or negative outcomes, conducting blameless postmortems, documenting root causes with 5 Whys or fishbone diagrams, identifying corrective actions with owners and timelines, learning from near-misses, establishing prevention strategies, or when user mentions postmortem, incident review, failure analysis, RCA, lessons learned, or after-action review.

Plausible Analytics API for querying website statistics and managing sites. Use this skill to get visitor counts, pageviews, traffic sources, and manage analytics sites.

Use when making high-stakes decisions under uncertainty that require stakeholder buy-in. Invoke when evaluating strategic options (build vs buy, market entry, resource allocation), quantifying tradeoffs with uncertain outcomes, justifying investments with expected value analysis, pitching recommendations to decision-makers, or creating business cases with cost-benefit estimates. Use when user mentions "should we", "ROI analysis", "make a case for", "evaluate options", "expected value", "justify decision", or needs to combine estimation, decision analysis, and persuasive communication.

Use when evaluating business model viability, analyzing profitability per customer/product/transaction, validating startup metrics (CAC, LTV, payback period), making pricing decisions, assessing scalability, comparing business models, or when user mentions unit economics, CAC/LTV ratio, contribution margin, customer profitability, break-even analysis, or needs to determine if a business can be profitable at scale.

Analyzes CSV files and generates comprehensive summary statistics and visualizations using Python and pandas - automatically and immediately without asking what the user wants.

Use when making quick order-of-magnitude estimates under uncertainty (market sizing, resource planning, feasibility checks), decomposing complex quantities into estimable parts, bounding unknowns with upper/lower limits, sanity-checking strategic assumptions, or when user mentions Fermi estimation, back-of-envelope calculation, order of magnitude, ballpark estimate, triangulation, or needs to assess feasibility before detailed analysis.

Use when comparing multiple named alternatives across several criteria, need transparent trade-off analysis, making group decisions requiring alignment, choosing between vendors/tools/strategies, stakeholders need to see decision rationale, balancing competing priorities (cost vs quality vs speed), user mentions "which option should we choose", "compare alternatives", "evaluate vendors", "trade-offs", or when decision needs to be defensible and data-driven.

Code review, security audits, bug detection, alternative implementations, second opinions via OpenAI Codex. Use when user asks for code review, security analysis, implementation advice, bug detection, code patterns, or wants a second opinion on code. Supports uncommitted changes review. Do not use for architecture design or web searches.

Use when starting technical work requiring structured approach - writing tests before code (TDD), planning data exploration (EDA), designing statistical analysis, clarifying modeling objectives (causal vs predictive), or validating results. Invoke when user mentions "write tests for", "explore this dataset", "analyze", "model", "validate", or when technical work needs systematic scaffolding before execution.

Analyze student git activity, lab submissions, and project work for software engineering courses. Use when asked to "update student analysis", "check student activity", "analyze the class", or when working with student rosters and git repositories. Handles inconsistencies in student behavior like multiple usernames, name variations, and missing data.

Technical research methodology with YAGNI/KISS/DRY principles. Phases: scope definition, information gathering, analysis, synthesis, recommendation. Capabilities: technology evaluation, architecture analysis, best practices research, trade-off assessment, solution design. Actions: research, analyze, evaluate, compare, recommend technical solutions. Keywords: research, technology evaluation, best practices, architecture analysis, trade-offs, scalability, security, maintainability, YAGNI, KISS, DRY, technical analysis, solution design, competitive analysis, feasibility study. Use when: researching technologies, evaluating architectures, analyzing best practices, comparing solutions, assessing technical trade-offs, planning scalable/secure systems.

Google Gemini CLI orchestration for AI-assisted development. Capabilities: second opinion/cross-validation, real-time web search (Google Search), codebase architecture analysis, parallel code generation, code review from different perspective. Actions: query, search, analyze, generate, review with Gemini. Keywords: Gemini CLI, second opinion, cross-validation, Google Search, web research, current information, parallel AI, code review, architecture analysis, gemini prompt, AI comparison, real-time search, alternative perspective, code generation. Use when: needing second AI opinion, searching current web information, analyzing codebase architecture, generating code in parallel, getting alternative code review, researching current events/docs.

Use when adding logging, debugging production issues, checking service health, or performing routine operations (adding personalities, database queries). Covers structured logging, correlation IDs, Railway log analysis, and common operations.

Technical implementation planning and architecture design. Capabilities: feature planning, system architecture, technical evaluation, implementation roadmaps, requirement breakdown, trade-off analysis, codebase analysis, solution design. Actions: plan, architect, design, evaluate, breakdown technical solutions. Keywords: implementation plan, technical design, architecture, system design, roadmap, requirements analysis, trade-offs, technical evaluation, feature planning, solution design, scalability, security, maintainability, sprint planning, task breakdown. Use when: planning new features, designing system architecture, evaluating technical approaches, creating implementation roadmaps, breaking down complex requirements, assessing technical trade-offs.

Systematic problem-solving techniques for stuck-ness. Techniques: simplification cascade (complexity spirals), collision-zone thinking (innovation blocks), meta-pattern recognition (recurring issues), inversion exercise (assumption constraints), scale game (uncertainty). Actions: simplify, analyze, recognize patterns, invert assumptions, scale thinking. Keywords: problem solving, complexity spiral, innovation block, stuck, simplification, meta-pattern, assumption inversion, scale uncertainty, breakthrough thinking, root cause, systematic analysis, Microsoft Amplifier, debugging approach, creative solution. Use when: complexity spiraling, hitting innovation blocks, seeing recurring patterns, constrained by assumptions, uncertain about scale, generally stuck on problems.

3D web graphics with Three.js (WebGL/WebGPU). Capabilities: scenes, cameras, geometries, materials, lights, animations, model loading (GLTF/FBX), PBR materials, shadows, post-processing (bloom, SSAO, SSR), custom shaders, instancing, LOD, physics, VR/XR. Actions: create, build, animate, render 3D scenes/models. Keywords: Three.js, WebGL, WebGPU, 3D graphics, scene, camera, geometry, material, light, animation, GLTF, FBX, OrbitControls, PBR, shadow mapping, post-processing, bloom, SSAO, shader, instancing, LOD, WebXR, VR, AR, product configurator, data visualization, architectural walkthrough, interactive 3D, canvas. Use when: creating 3D visualizations, building WebGL/WebGPU apps, loading 3D models, adding animations, implementing VR/XR, creating interactive graphics, building product configurators.

Task decomposition, dependency analysis, and parallel execution orchestration. Use when breaking down features into tasks, analyzing task dependencies, planning parallel execution strategies, or coordinating multi-agent workflows. Covers dependency detection, execution grouping, resource conflict prevention, and performance optimization.

데이터 분석 전문가. pandas, numpy, 시각화, 통계 분석 지원.

Railway deployment operations for Tzurot v3 - Service management, log analysis, environment variables, health checks, and troubleshooting. Use when deploying, debugging production issues, or managing Railway infrastructure.

Consults external AI models (100+ via LiteLLM) for complex analysis. Use for architectural review, security audit, deep code understanding, or when extended reasoning is needed. Runs async with session management.