Skill UI

Guides agents through validation, dry-run MCP tool usage, and monitors-as-code YAML generation so Monte Carlo monitors can be established via CLI or CI/CD without directly creating assets.

An expert agent designed to collect critical data assets—including metadata, data lineage, and query logs—from any data warehouse platform. It uses the push ingestion API to send this data directly to Monte Carlo. This method is essential for integrating data sources that cannot be reliably covered by standard pull collectors, such as custom lineage paths or historical query logs.

This skill automatically generates an interactive SQL Notebook designed to validate changes in dbt models or snapshots. It processes changes identified from a GitHub PR or local repository, generating comparison queries that compare 'before' (production) and 'after' (development) data states. It is essential for embedding data observability and quality checks into CI/CD pipelines.

This skill provides comprehensive automation for managing OneDrive file lifecycles. Users can perform advanced operations including searching across metadata and content, uploading and downloading files, organizing folders, creating share links, and granularly managing permissions for specific users. It utilizes a structured workflow approach via Rube MCP, making it ideal for automating business processes involving cloud document storage and collaboration.

A structured methodology for coordinating multiple, simultaneous investigation threads to determine the root cause of complex system failures, performance regressions, or integration bugs. This skill decomposes a large problem into independent tracks (e.g., database, application code, infrastructure), assigns ownership, and manages structured sync points (Continue/Pivot/Converge) to converge on a solution faster than serial debugging. Essential for high-stakes production incident response.

The Phoenix CLI is a powerful tool for debugging complex LLM and agent workflows. It allows users to fetch detailed traces, spans, and sessions, analyze errors, and structure findings using open and axial coding techniques. It is essential for investigating complex LLM failures, building robust failure taxonomies, and guiding the next steps in application evaluation after initial instrumentation.

A comprehensive expert prompt for evaluating Power BI data models. It guides the assessment of model architecture (Star Schema, relationships), storage optimization (Import, DirectQuery, Dual), data quality, performance scalability, and governance best practices. Use this when reviewing an existing BI model to ensure it is robust, maintainable, and highly performant.

Generates professional conference presentation slides from a compiled research paper. This skill produces dual outputs: a polished Beamer LaTeX PDF for high-quality typesetting, and an editable PPTX for flexible adjustments. It supports multiple talk types (Poster, Spotlight, Oral, Invited) and includes detailed guidelines for speaker notes and talk scripting, making it essential for academic researchers preparing for major ML and systems conferences.

Automates converting PPTX, PDF, HTML, or Google Slides inputs into a GitHub Pages repo, covering conversion, asset handling, repo creation, and returning the live URL so presentations or HTML content can be shared quickly.

This guide serves as a comprehensive reference for source-file migration patterns required when upgrading to React 19. It details critical API changes, such as updating `ReactDOM.render` to `createRoot().render()`, modernizing ref handling, and adjusting legacy context usage. It is essential for developers migrating large, existing React applications to ensure compatibility with the latest React standards.

This skill provides granular control over the browser launch environment. Users can specify whether the browser window should be visible (`headed`) or if the underlying automation mechanism should switch from default managed CDP to Playwright management (`private_mode`). This is essential for complex automation, testing, and web scraping scenarios requiring specific environmental setups.

This skill is designed to manage complex, multi-step tasks by coordinating the efforts of multiple specialized AI agents. It provides structured methods for listing available agents, initiating real-time conversations, submitting complex background tasks (such as data analysis or report generation), tracking task status, and maintaining conversational context using session IDs. It is essential when a core task requires diverse expert knowledge or sequential collaboration.