Skill UI

This skill guides the end-to-end process of building automated evaluation pipelines for Python applications powered by Large Language Models (LLMs). It teaches how to define evaluation criteria, instrument the application, build golden datasets, and run real-world evaluations using tools like pixie, ensuring the app's logic (not just the LLM) is rigorously tested. Ideal for QA, benchmarking, and improving LLM-based services.

Framework for launching new products from idea to first loyal customers, covering direct outreach, launch diagnostics, and short experiment cycles to break through early adoption hurdles.

A four-phase onboarding framework that guides enterprise customers from contract execution through go-live to sustained adoption, highlighting early owner validation, adoption cliff prevention, and pre-onboarding readiness to keep large deals moving and prevent churn.

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.

Surfaces Monte Carlo data observability insights—health, lineage, alerts, and monitors-as-code—before developers edit dbt models or SQL pipelines, ensuring risk-aware code changes.

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.

This skill guides comprehensive website exploration using Playwright MCP for robust testing. It involves navigating a specified URL, identifying and simulating 3-5 core user flows, meticulously documenting user interactions, relevant UI locators, and expected outcomes. Upon completion, the skill summarizes findings and generates detailed, actionable test cases, ensuring thorough coverage of the application's functionality.

Analyzes PostgreSQL snippets or entire projects to flag anti-patterns, enforce best practices, optimize JSONB/array usage, schema design, custom types, triggers, extensions, and security policies like RLS.

Helps implement optimized Power BI semantic models by analyzing the active model with MCP tools, then advising on star schemas, DAX, relationships, security, documentation, and performance best practices for reporting scenarios.

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.