datarobot-model-deployment
Tools for deploying, managing, and monitoring DataRobot models, including prediction environment configuration, champion/challenger workflows, and deployment operations.
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476 skills found
Tools for deploying, managing, and monitoring DataRobot models, including prediction environment configuration, champion/challenger workflows, and deployment operations.
Analyze UI/UX quality against 4 authoritative standards (NNg, Laws of UX, Apple HIG, WCAG) to receive actionable design and accessibility improvements for mobile and web components.
A structured design and planning tool for Vizro dashboards, enforcing a 3-step workflow (requirements, layout, visualization) to ensure production-ready dashboard development.
Proactive context window management for AI agents via intelligent token monitoring, snapshot creation, and selective state rehydration to maintain continuity during long sessions.
Evidence-first literature collector for automated research pipelines. Scales paper pools to 1200+ with metadata normalization, provenance tracking, and multi-source ingestion.
Generate incident response timelines and structured report packs from event logs to facilitate efficient detection-to-recovery tracking.
Create and test AI-ready MCP tools for any web application. Inject code, automate browser interactions, and turn websites into intelligent agents.
Intelligent tool selector for code search. Routes queries between semantic (claudemem) and native tools (Grep/Glob) to optimize efficiency, token usage, and search accuracy.
Statistical visualization library for Python. Create publication-quality graphics like box plots, heatmaps, and violin plots with pandas integration and automatic statistical estimation.
Review backend pull requests with security enforcement and GitHub CLI integration in a strict read-only environment.
Real-time web search and content extraction tool using the Tavily API for research, news gathering, and up-to-date information retrieval.
A framework for managing the end-to-end LLM project lifecycle, from evaluating task-model fit and pipeline architecture design to implementing structured output parsing and agent-assisted development.