數據科學

Configures logging systems, log aggregation, and log analysis pipelines

Create compelling story-format summaries using deep analysis to find the best narrative framing.Supports multiple formats: 3-part narrative, n-length with inline links, abridged 5-line, or numbered CSE5.USE WHEN user says 'create story explanation', 'narrative summary', 'explain as a story','tell as story', 'story with links', '5-line summary', 'CSE', 'CSE5'.

This skill should be used when the user asks to "debug notebook", "inspect notebook outputs", "find notebook error", "read traceback from ipynb", "why did notebook fail", or needs to understand runtime errors in executed Jupyter notebooks from any source (marimo, jupytext, papermill).

Intelligent POC-to-production code extraction with architectural awareness. Analyzes dependencies, adapts patterns, makes extraction strategy decisions (copy/adapt/rewrite), maintains system coherence. Performs pre-extraction analysis, transformation reasoning, quality gate enforcement, evidence-based commits. Use when extracting code requires understanding architecture, adapting patterns, threading parameters, or maintaining coherence across modules. Triggers on understand and extract, analyze dependencies, adapt pattern, extraction strategy, architectural extraction, intelligent migration.

Explain code with ASCII diagrams, analogies, and Mermaid visualizations. Triggers: explain this code, how does this work, what does this do, explain architecture, visualize code, diagram this, help me understand

Style and render geographic data with renderers, symbols, and visual variables. Use for creating thematic maps, heatmaps, class breaks, unique values, labels, and 3D visualization.

Create professional architecture diagrams using D2, Draw.io, Mermaid, and OCI official icons for enterprise-grade visualizations

Create new AI-powered features using xAI Grok. Use when user mentions "new AI feature", "add Grok", "create prompt", "AI analysis", or "generate with AI".

Build features in the SCM (School Coaching Manager) section. Use for creating pages, hooks, and visualizations for podsie tracking, roadmaps, velocity, and assessment data.

Comprehensive energy analysis using EnergyPlus, commissioning best practices, and ASHRAE standards for building energy modeling, code compliance verification, and performance optimization

Systematic code review using quality gates, SOLID principles, error handling patterns, and test coverage analysis. Provides structured feedback with severity levels and actionable improvements.

Triggering and managing AI reflection cycles in StickerNest. Use when the user wants to run AI evaluation, trigger reflection, check AI quality, improve AI prompts, analyze AI performance, or audit AI generations. Covers reflection triggers, evaluation analysis, and improvement actions.

Authentication and authorization including JWT, OAuth2, OIDC, sessions, RBAC, and security analysis. Activate for login, auth flows, security audits, threat modeling, access control, and identity management.

Testing patterns including pytest, unittest, mocking, fixtures, and test-driven development. Activate for test writing, coverage analysis, TDD, and quality assurance tasks.

Guide selection and interpretation of statistical hypothesis tests. Use when: (1) Choosing appropriate test for research data, (2) Checking assumptions before analysis, (3) Interpreting test results correctly, (4) Reporting statistical findings, (5) Troubleshooting assumption violations.

Landing page component registry integration for searching, browsing, and pulling pre-built React/TypeScript components from the monet MCP server. Use this skill when users want to (1) search for UI components (hero sections, pricing tables, testimonials, etc.), (2) pull/add components to their project, (3) browse available component categories, (4) get component details or code, or (5) explore the component registry statistics.

ICT-based MNQ futures trading analysis system for MFFU prop firm evaluation. Use when user provides market data (PDH, PDL, FVG levels, liquidity sweeps) and asks for trade analysis, entry/exit points, or bias confirmation. Also handles advanced concepts: breaker blocks, rejection blocks, SMT divergence, Power of 3, Judas Swing, OTE, NWOG, NDOG. Triggers on keywords like "trade setup", "NQ analysis", "entry", "SL", "TP", "bias", "liquidity sweep", "FVG", "order block", "ICT", "MMXM", "MMBM", "MMSM", "market maker model", "smart money reversal", "SMR", "breaker", "rejection block", "SMT", "Power of 3", "Judas swing", "OTE", "opening gap", "NWOG", "NDOG".

Analyzes and explains Actoris trust scores, their components, and how to optimize them. Use when you need to understand trust mechanics, interpret trust scores, or provide recommendations for improving agent trustworthiness.

Analyze vocabulary entries for semantic relationships, usage patterns, and learning progression optimization. Use when processing vocabulary data, generating study materials, or analyzing language learning content.

Create data visualizations using various charting libraries. Use when visualizing data or creating interactive charts.