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Apache Airflow DAG Best Practices

airflow-dag-patterns

sickn33/antigravity-awesome-skills

A comprehensive guide to building production-ready Apache Airflow Directed Acyclic Graphs (DAGs). This skill covers best practices for operators, sensors, testing, deployment, and designing robust data pipelines. Use this when orchestrating complex workflows, managing ETL processes, or ensuring reliable batch job execution in a production environment.

Backtesting Trading Strategies Framework

backtesting-trading-strategies

jeremylongshore/claude-code-plugins-plus-skills

This comprehensive framework allows users to validate and test both crypto and traditional trading strategies against extensive historical market data. It calculates essential performance metrics (Sharpe Ratio, Sortino Ratio, Max Drawdown), simulates trade execution, generates equity curves, and includes advanced parameter grid search optimization tools for robust strategy validation.

Juicebox CI/CD Data Analysis Testing

juicebox-ci-integration

jeremylongshore/claude-code-plugins-plus-skills

Configure automated Continuous Integration and Continuous Deployment (CI/CD) pipelines for Juicebox AI data analysis integrations. This setup utilizes GitHub Actions to run comprehensive unit tests (with mocked datasets) and integration tests (connecting to live APIs) on every PR and merge to main. It ensures that data upload logic, analysis execution, and result parsing workflows are robust and reliable before deployment.

AI Agent Observability and Metrics Monitoring

lindy-observability

jeremylongshore/claude-code-plugins-plus-skills

This guide details how to implement comprehensive observability for AI agents. It covers monitoring key metrics such as task success rates, step failures, execution duration, and credit consumption. Use this when setting up performance dashboards, configuring real-time alerts (via webhooks/Prometheus), or tracking agent reliability over time.

Simple Analytics Automation

simple-analytics-automation

ComposioHQ/awesome-claude-skills

Streamlines Simple Analytics tasks by orchestrating Composio toolkits through Rube MCP, guiding tool discovery, connection checks, schema-aware arguments, and execution workflows.

Simulate DeFi Flash Loan Arbitrage

simulating-flash-loans

jeremylongshore/claude-code-plugins-plus-skills

This advanced tool simulates complex DeFi flash loan strategies across major protocols like Aave, dYdX, and Balancer. It calculates net profitability, estimates gas costs, and assesses comprehensive risks (MEV, liquidity, execution). Use it to evaluate arbitrage opportunities, analyze liquidation potential, or compare multiple lending providers before executing real transactions.

Analyzing LNK and Jump List Artifacts

analyzing-lnk-file-and-jump-list-artifacts

mukul975/Anthropic-Cybersecurity-Skills

This skill details the forensic analysis of Windows LNK shortcut files and Jump Lists. These artifacts record critical user activity, including file access and program execution, even after the original source files have been deleted. It covers using specialized tools (LECmd, JLECmd) and Python parsing techniques to reconstruct user timelines, making it essential for incident response and deep digital forensics examinations.

Analyzing Windows Amcache Forensic Artifacts

analyzing-windows-amcache-artifacts

mukul975/Anthropic-Cybersecurity-Skills

This guide details a comprehensive workflow for digital forensic investigations focusing on Amcache.hve registry hive. It teaches how to use AmcacheParser to extract evidence of program execution, application installation, and driver loading, including correlating SHA-1 hashes with threat intelligence and reconstructing timelines. This is crucial for DFIR work to identify deleted executables and malicious activity.

Analyzing Windows Prefetch for Forensics

analyzing-windows-prefetch-with-python

mukul975/Anthropic-Cybersecurity-Skills

This skill parses Windows Prefetch (.pf) files to reconstruct detailed application execution history. It is crucial for digital forensics, allowing analysts to track execution timelines, identify suspicious or renamed binaries, and investigate potential malware activity or lateral movement during incident response. It uses Python to extract run counts and accessed file details.

Windows Artifact Analysis Using EZ Tools

performing-windows-artifact-analysis-with-eric-zimmerman-tools

mukul975/Anthropic-Cybersecurity-Skills

This suite provides comprehensive utilities for digital forensic investigations, allowing users to analyze critical Windows artifacts. Tools like KAPE, MFTECmd, PECmd, and RECmd parse registry hives, $MFT records, prefetch files, and event logs. It is essential for building a robust timeline of program execution, file access patterns, and system persistence during DFIR incident response.

Serverless GPU Cloud for ML Workloads

serverless-modal

wanshuiyin/Auto-claude-code-research-in-sleep

Utilize Modal, a serverless GPU cloud, for running complex machine learning workloads, including training, fine-tuning, and inference. This tool provides a zero-config environment, eliminating the need for SSH setup or Docker management. It features automatic scale-to-zero billing and local-first execution, making high-powered GPU compute accessible for debugging and small-scale experiments.

Power BI Performance Triage

power-bi-performance-troubleshooting

github/awesome-copilot

Provides systematic Power BI performance troubleshooting guidance covering model optimization, DAX design, report layout, and capacity diagnostics, plus tool-driven measurement tips for faster page loads, interactions, and query execution.

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