Monitoring AI Agent Skills

A native macOS menu bar application for real-time monitoring of Claude AI usage limits English • Español • Français • Deutsch • Italiano • Português • 日本語 • 한국어 Download Latest Release (v2.3.0) macOS 14.0+ (Sonoma) | ~4 MB | Native Swift/SwiftUI | Officially Signed Claude Usage Tracker is a lightweight, native macOS menu bar application that provides real-ti

Design effective KPI dashboards with metrics selection, visualization best practices, and real-time monitoring patterns. Use when building business dashboards, selecting metrics, or designing data visualization layouts.

Build comprehensive ML pipelines, experiment tracking, and model

Build production ML systems with PyTorch 2.x, TensorFlow, and

Expert performance engineer specializing in modern observability,

Build production-ready monitoring, logging, and tracing systems.

Set up Prometheus for comprehensive metric collection, storage, and monitoring of infrastructure and applications. Use when implementing metrics collection, setting up monitoring infrastructure, or configuring alerting systems.

Create and manage production Grafana dashboards for real-time visualization of system and application metrics. Use when building monitoring dashboards, visualizing metrics, or creating operational observability interfaces.

You are an error tracking and observability expert specializing in implementing comprehensive error monitoring solutions. Set up error tracking systems, configure alerts, implement structured logging,

X (Twitter) data platform skill for AI coding agents. 120 REST API endpoints, 2 MCP tools, HMAC webhooks. Tweet search, user lookup, follower extraction, write actions, monitoring, giveaway draws, trending topics. Reads from $0.00015/call — 33x cheaper than the official X API.

A powerful Model Context Protocol (MCP) server for Docker operations, enabling seamless container and compose stack management through Claude AI. - 🚀 Container creation and instantiation - 📦 Docker Compose stack deployment - 🔍 Container logs retrieval - 📊 Container listing and status monitoring To try this in Claude Desktop app, add this to your claude config files: To install Docker MCP for C

Production-ready patterns for building LLM applications. Covers RAG pipelines, agent architectures, prompt IDEs, and LLMOps monitoring. Use when designing AI applications, implementing RAG, building agents, or setting up LLM observability.

Expert DevOps troubleshooter specializing in rapid incident

An MCP server for tracking Binance Alpha trades, helping AI agents optimize alpha point accumulation. - Real-time Trade Monitoring: Track buy-side activity for Binance Alpha tokens by Subscribing to on-chain events. - USD-based Metrics: Calculates trade values in USD using real-time prices from the CryptoCompare. - Data Persistence: Maintains trade data in memory, with automatic cleanup of records

The local Dynatrace MCP server allows AI Assistants to interact with the Dynatrace observability platform, bringing real-time observability data directly into your development workflow. If you need help, please contact us via GitHub Issues if you have feature requests, questions, or need help. You can add this MCP server to your MCP Client like VSCode, Claude, Cursor, Amazon Q, Windsurf, ChatGPT,

A portable, single-binary system auditing tool for Linux. Like Lynis but faster and smarter. No configuration needed. No dependencies. Just run. - 🔒 Security: Firewall, SSH hardening, SSL/TLS, fail2ban, SUID binaries, open ports - 🚀 Services: Systemd services, web servers, databases, Docker - 💻 Resources: CPU, RAM, disk usage, top processes - 💾 Storage: SMART health, inode usage, filesystem er

Automate Sentry tasks via Rube MCP (Composio): manage issues/events, configure alerts, track releases, monitor projects and teams. Always search tools first for current schemas.

You are an error tracking and observability expert specializing in implementing comprehensive error monitoring solutions. Set up error tracking systems, configure alerts, implement structured logging, and ensure teams can quickly identify and resolve production issues.

MCP-Dandan is an integrated monitoring service that observes MCP (Model Context Protocol) communications and detects security threats in real time. It features a modern desktop UI built with Electron for easy monitoring and management. Currently, MCP-Dandan is listed in well-known MCP-related open-source collections and can be found in the following repositories: - Awesome MCP Servers – Security -

This skill should be used when users want to train or fine-tune language models using TRL (Transformer Reinforcement Learning) on Hugging Face Jobs infrastructure. Covers SFT, DPO, GRPO and reward modeling training methods, plus GGUF conversion for local deployment. Includes guidance on the TRL Jobs package, UV scripts with PEP 723 format, dataset preparation and validation, hardware selection, cost estimation, Trackio monitoring, Hub authentication, and model persistence.

Enable AI models to interact with a global network measurement platform through natural language. Give network access to any LLM. Globalping is a free, public API that provides access to a globally distributed network of probes for monitoring, debugging, and benchmarking internet infrastructure. With Globalping, you can run network tests (ping, traceroute, DNS, MTR, HTTP) from thousands of locatio

Calculate portfolio risk metrics including VaR, CVaR, Sharpe, Sortino, and drawdown analysis. Use when measuring portfolio risk, implementing risk limits, or building risk monitoring systems.

Plugins for Claude Code. Your world at a glance, without leaving the terminal. Track PRs, calendar, Slack, stocks, music—all in your statusline. The flow: /hub-setup → add monitors → alerts appear → /hub-ack for smart actions (merge PR, join meeting, reply to Slack). → Full documentation — workflow examples, all services, commands AI-powered market screening, without leaving the terminal. Screen s

Build anomaly detection applications with Azure AI Anomaly Detector SDK for Java. Use when implementing univariate/multivariate anomaly detection, time-series analysis, or AI-powered monitoring.