Skill UI

This skill provides comprehensive access to the Hugging Face Hub ecosystem via MCP server tools. Users can search for state-of-the-art models, datasets, and research papers, retrieve detailed repository information, fetch documentation, run compute jobs on GPU/CPU, and interact with Gradio Spaces as fully functional AI tools. Ideal for ML development, research, and application prototyping.

The `hf-mem` skill estimates the necessary VRAM or system memory required to load Safetensors or GGUF model weights for inference directly from the Hugging Face Hub. It uses efficient HTTP Range requests, avoiding local downloads. Users can determine if a model fits on their GPU or instance, including optional estimations for the KV cache and setting limits like maximum sequence length.

A comprehensive utility for building reusable, command-line scripts and utilities to interact with the Hugging Face API. It enables complex data workflows by allowing users to chain, pipe, and process data fetched from models, datasets, and various endpoints. Ideal for automation, enrichment, and advanced data pipelines.

This skill integrates with Monte Carlo's observability platform to provide a comprehensive health report for data assets. It checks critical metrics including data freshness, active alerts, monitoring coverage, asset importance, and the health of upstream dependencies. Activates when users inquire about the status, reliability, or quality of a data table.

This skill provides comprehensive monitoring advisory services for data assets and AI agents. It helps users assess data coverage gaps, analyze use-case criticality, and automatically create data quality monitors (table, metric, validation). Furthermore, it enables monitoring of AI agent performance, latency, and observability, ensuring robust data governance across the entire ML lifecycle.

This skill analyzes your data warehouse to pinpoint stale, unused, or redundant tables that contribute to unnecessary storage costs. It classifies waste patterns (e.g., Zombie, Temporary) and computes safety tiers, helping users understand which assets can safely be dropped or archived to optimize spending and improve data governance.

Neon Object Storage provides S3-compatible, branch-aware object storage directly integrated with your Neon Postgres project. It ensures that files (images, documents, user uploads) remain perfectly synchronized with the database schema across all development branches (dev, preview, staging, production). Use this skill when you need a single backend for both database rows and file assets, eliminating the need for separate cloud storage providers.

This skill provides comprehensive guidance on choosing and creating the appropriate Neon Postgres branch for development and testing workflows. Users must decide between a 'Normal' branch (for realistic migration testing with live data) or a 'Schema-Only' branch (for highly sensitive data environments). It details the decision rules, tool selection (CLI/MCP), and procedures for branch creation and resetting.

A comprehensive skill to diagnose and fix excessive Postgres egress (network data transfer) that leads to high cloud database bills. It guides the user through using `pg_stat_statements` to identify the most data-intensive queries. Key fixes include limiting selected columns (avoiding SELECT *), implementing pagination (LIMIT/OFFSET), and identifying high-frequency data sources for caching.

Generate comprehensive, ready-to-use CI/CD pipeline configurations for running automated API tests using Newman. This skill provides templates for major platforms like GitHub Actions, GitLab CI, Jenkins, and Azure DevOps. It ensures seamless integration of Postman collections into automated build processes, including setting up environment variables, running tests, and publishing detailed JUnit and HTML reports.

Provides a comprehensive guide for authentically marketing and growing open source projects. Covers best practices for GitHub optimization (README, repository setup), community building, and implementing sustainable growth strategies, ensuring the project is discoverable and valuable.

This skill automatically generates fully structured, import-ready Postman Collection v2.1 JSON files. It can interpret both natural language descriptions of REST APIs (endpoints, methods, parameters) and raw cURL commands. Use it whenever you need to quickly set up a comprehensive API testing suite in Postman without manual JSON construction, ensuring all variables and environments are properly extracted.