Skill UI

Helps analyze current CPU, memory, storage, and network utilization to forecast future infrastructure needs, identify bottlenecks, and recommend scaling tactics with cost context for proactive capacity management.

Helps analyze current CPU, memory, storage, and network utilization to forecast future infrastructure needs, identify bottlenecks, and recommend scaling tactics with cost context for proactive capacity management.

This skill provides comprehensive observability for the Databricks platform. It enables users to monitor job run histories, track cluster utilization and associated costs (DBU), detect slow SQL queries, and audit access logs. Use it for setting up robust monitoring dashboards, ensuring pipeline health, and optimizing resource consumption across the entire data stack.

A comprehensive guide to optimizing Fireflies.ai subscription costs. Learn how to reduce expenses by auditing user utilization, configuring selective recording policies, managing storage retention, and accurately right-sizing your plan (Pro, Business, Enterprise). Ideal for teams reviewing billing or implementing cost-saving measures.

A comprehensive toolkit for monitoring the health and performance of Fireflies.ai integration. It tracks crucial metrics such as API connectivity, webhook delivery status, transcript processing latency, and seat utilization. Built using Prometheus metrics and suitable for Grafana dashboards, ensuring reliable data pipeline monitoring for engineering teams.

This tool is designed to optimize your Instantly.ai usage and associated costs. It performs detailed audits on account utilization, tracks key campaign metrics (open rate, reply rate, bounce rate), and compares your current activity against various pricing tiers (Growth, Hypergrowth, Light Speed). Use this when reviewing billing, assessing efficiency, or selecting the most cost-effective plan.

This skill is designed to help users optimize the operational costs of the TwinMind AI platform. It provides detailed usage monitoring and guidance for selecting the most appropriate subscription tier (Free, Pro, or Enterprise). Users can manage advanced features such as high-accuracy transcription (Ear-3) and AI summarization across multiple models (GPT-4, Claude, Gemini), ensuring efficient resource utilization and cost control for large-scale meeting AI operations.

A comprehensive guide demonstrating the full lifecycle of GPU resource utilization on Vast.ai. This includes searching for available hardware using CLI and REST APIs, provisioning a dedicated GPU instance (e.g., using PyTorch images), connecting via SSH, running deep learning workloads, and finally, securely destroying the instance to stop billing. Ideal for testing cloud integration or managing ML compute pipelines.

This skill provides comprehensive monitoring capabilities for GPU instances running on Vast.ai. It collects key metrics including GPU utilization, instance uptime, temperature, and accumulated costs. Use this when setting up operational monitoring dashboards, configuring critical alerts (e.g., idle GPUs, high temperature, budget overruns), or automating resource usage tracking in a cloud computing environment.

A comprehensive checklist for deploying large-scale, production-ready GPU workloads on Vast.ai. It covers critical lifecycle stages including account authentication, instance validation, data encryption, persistent checkpointing strategies, fault tolerance for spot instances, robust monitoring (utilization & cost), and strict cost controls, ensuring reliable and stable ML/AI deployments.

A comprehensive guide for optimizing licensing costs associated with AI developer tools (like Windsurf). It provides structured methods for auditing seat utilization, matching feature tiers to specific team roles, calculating the ROI per seat, and implementing continuous usage monitoring to maximize cost efficiency and minimize wasteful spending.

This comprehensive skill guides the deployment and utilization of MISP, a powerful open-source threat intelligence platform. It covers configuring various threat feeds (TAXII, CSV, etc.) and using the PyMISP Python API to programmatically automate the collection, storage, and correlation of Indicators of Compromise (IOCs) and threat events from diverse community and commercial sources.