Skill UI

This skill provides a comprehensive guide to configuring event-driven workflows and robust notification systems for Databricks jobs. It covers setting up various notification destinations (Slack, Teams, Email, PagerDuty) and triggering alerts based on job lifecycle events (success, failure, start). Furthermore, it demonstrates advanced monitoring using system audit tables and creating automated SQL alerts for critical data pipeline monitoring.

Enables Claude to apply anomaly-detection-system workflows for spotting outliers, fraud, or unusual patterns across datasets, selecting tailored algorithms like Isolation Forest and summarizing deviations for any data monitoring or security use case.

This skill provides comprehensive monitoring and comparative analysis of cross-chain bridges in the DeFi ecosystem. It tracks key metrics such as Total Value Locked (TVL), transaction volume, typical fees, and real-time transfer status across major networks (e.g., Ethereum, Arbitrum, Polygon). Use this tool to research bridge safety, compare transfer routes before depositing funds, or track specific transaction hashes across multiple protocols like Wormhole, LayerZero, and Stargate.

This skill allows users to track large cryptocurrency transactions and the movements of "whale" wallets across multiple blockchains. It monitors exchange inflows and outflows, helping users analyze potential market trends, identifying accumulation or selling pressure from major holders. Ideal for crypto analysts and investors needing real-time market insights.

This skill provides comprehensive, structured audit logging for OpenRouter API interactions. It automatically captures essential metadata like total cost, token usage, model details, latency, and status, while also performing PII redaction. The resulting audit trail is stored in an append-only SQLite database, making it ideal for building compliance-ready systems, detailed cost monitoring, and deep debugging of production environments.

This skill provides comprehensive tracking and analysis of OpenRouter API usage metrics. It collects critical data points such as per-request total cost, prompt and completion token counts, latency, and usage patterns. Use this skill when building financial dashboards, optimizing AI spending, monitoring API consumption, or generating detailed usage reports.

A comprehensive foundation skill for monitoring cryptocurrency markets. It provides real-time quotes, 24-hour change metrics, and deep historical price data for over 10,000 coins. Users can track specific symbols, view predefined watchlists (e.g., DeFi, Top 10), or export detailed OHLCV data in CSV format. This skill serves as the foundational data layer for crypto portfolio management, tax calculation, and DeFi analysis applications.

Build a production-ready, AI-powered data collection agent for any public source (job boards, prices, news, etc.). This agent automatically scrapes data, enriches it using free LLMs (like Gemini Flash), and stores the results in databases such as Notion, Sheets, or Supabase. It runs on a free schedule using GitHub Actions and learns from user feedback, making it ideal for continuous data monitoring and tracking.

This skill provides interactive, periodic monitoring of deep learning training runs. It continuously checks critical metrics—such as loss trends, evaluation scores, and gradient norms—against defined baselines to detect signs of divergence, NaN values, plateaus, or general instability. It delivers a structured report and recommends whether to continue, wait, or stop the training process, ensuring computational resources are not wasted on failing models.

This skill provides comprehensive management for annotation schemas (configs) and human review workflows (queues) within the Arize platform. It supports defining categorical, continuous, and freeform label types. Users can programmatically apply these annotations to project spans and datasets using the Python SDK, facilitating structured human feedback loops and improving model monitoring.

Reviews Python + BigQuery pipelines to flag runaway costs, missing dry-run safeguards, unsafe backfills, write idempotency issues, and monitoring gaps, returning a structured report with exact function/line references for minimal fixes.

This skill provides a robust solution for monitoring critical forecast changes within Clari. Since Clari lacks native real-time webhooks for all data, this system implements change detection by polling periodic data exports and comparing current snapshots against historical records. It calculates the percentage change and can trigger immediate alerts via platforms like Slack, ensuring users are always aware of significant shifts in revenue forecasts or sales pipelines.