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Prototype, inspect, and improve product UI, UX, and design implementation flows.
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This skill helps you build autonomous AI agents with tool use and planning strategies to automate multi-step workflows.
Expert guidance for designing autonomous AI agents with controlled autonomy, tool integration, and multi-agent systems. \n \n Covers core agent patterns: ReA…
This skill designs autonomous AI agents with tool use, memory, planning, and multi-agent orchestration to stay controllable and robust.
This skill assists you craft and edit text in Microsoft Office applications using AI prompts and best practices.
This skill helps you design and deploy production-grade LLM apps, RAG systems, and intelligent agents with robust safety and observability.
This skill helps AI agents detect and generate contextually appropriate humor using 12 bisociation patterns with ethical gating.
Operational patterns for LLM inference: latency budgeting, tail-latency control, caching, batching/scheduling, quantization/compression, parallelism, and reliable serving at scale. Emphasizes production-grade performance, cost control, and observability.
This skill turns raw data and questions into validated, documented models ready for production:
End-to-end data science and ML engineering workflows: problem framing, data/EDA, feature engineering (feature stores), modelling, evaluation/reporting, plus SQL transformations with SQLMesh. Use for dataset exploration, feature design, model selection, metrics and slice analysis, model cards/eval reports, experiment reproducibility, and production handoff (...
Modern Best Practices (January 2026):
Operational patterns, templates, and decision rules for time series forecasting (modern best practices): tree-based methods (LightGBM), deep learning (Transformers, RNNs), future-guided learning, temporal validation, feature engineering, generative TS (Chronos), and production deployment. Emphasizes explainability, long-term dependency handling, and adaptiv...
Production MLOps and ML/LLM/agent security skill for deploying and operating ML systems in production (registry + CI/CD, serving, monitoring/drift, evaluation loops, incident response/runbooks, and governance), including GenAI security (prompt injection, jailbreaks, RAG security, privacy, and supply chain).
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4988 candidates for Design. Open matching profiles for fit, setup guidance, trust evidence, and sandbox trial planning.
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