Skill UI

Nextflow is a powerful workflow language and runtime for building reproducible, portable, and scalable data pipelines, especially dominant in bioinformatics. This skill covers the entire workflow lifecycle: from authoring complex pipelines using the modern DSL2 syntax, to configuring containerized execution (Docker, Singularity), scaling to High-Performance Computing (HPC) or cloud environments, and running/debugging existing nf-core workflows.

A robust API-backed skill for fetching YouTube transcripts, searching video content, browsing channels, and extracting playlists. It functions reliably from any cloud server environment, bypassing limitations found in local tools like yt-dlp or reliance on Google API keys. Ideal for building research corpora, competitive intelligence monitoring, and systematic content analysis.

This skill performs an observability-first audit of deployed Vercel applications. It comprehensively analyzes production metrics, project configurations, and codebase scans to identify potential cost overruns and performance bottlenecks. It provides version-aware, actionable recommendations for improving application efficiency and reducing cloud expenditure.

HasData is a comprehensive cloud platform designed for extracting structured public web data. It supports three core execution modes: Web Scraping API for arbitrary URLs (including JS rendering), pre-parsed Scraper APIs for known platforms (like Google or Amazon), and asynchronous Scraper Jobs for bulk or recursive crawling. Ideal for market research, e-commerce intelligence, job data collection, and local business lead generation.

This skill provides a robust method for uploading local digital assets, including images, mockups, and full HTML files, to a Stitch project. It bypasses the limitations of standard tool calls by streaming files directly over HTTP, ensuring that large visual assets or complex web pages can be processed accurately for your design and prototyping workflow. Ideal for integrating local design iterations into cloud-based prototypes.

This workflow systematically analyzes deployed AWS resources and Infrastructure-as-Code (IaC) definitions. It collects usage metrics from CloudWatch and Cost Explorer to identify over-provisioning, unused resources, and inefficient configurations (e.g., right-sizing EC2, S3 lifecycle policies). It generates actionable cost optimization recommendations and creates structured GitHub issues for tracking and implementing savings.

This comprehensive workflow analyzes the health status of various AWS resources (EC2, Lambda, RDS, DynamoDB, etc.). It uses AWS CLI to diagnose potential issues by analyzing CloudWatch logs, metrics, and performance data. The process culminates in classifying root causes and generating actionable, tiered remediation plans (Immediate, Short-term, Long-term) to ensure system resilience and stability.

This automated workflow performs a comprehensive review against the AWS Well-Architected Framework (WAF). It scans IaC definitions (Terraform, CloudFormation, CDK) and deployed resources to identify compliance gaps, security risks, and optimization opportunities across six core pillars. Findings are structured and automatically generated as actionable GitHub issues with remediation code examples.

This tool conducts structured reviews of various Infrastructure-as-Code (IaC) tools (e.g., Terraform, Pulumi) across multiple cloud providers. It generates an actionable report that categorizes findings by severity (Critical, High, Medium, Low), providing detailed remediation steps and a reusable best-practice checklist for continuous security, compliance, and operational auditing.

This workflow transforms long YouTube talks and lectures into a personal, structured, and local markdown library. Each video becomes a self-contained file containing slide snapshots, full timestamped transcripts, and editable study notes. It eliminates reliance on cloud services, giving users full ownership of their academic material.

This skill guides the architecture and implementation of SAML 2.0 identity federation between on-premises Active Directory and Microsoft Entra ID (Azure AD). It covers establishing seamless Single Sign-On (SSO) capabilities, eliminating the need for separate credentials and ensuring secure, cross-domain authentication for cloud applications.

This framework provides comprehensive detection capabilities for compromised cloud credentials across major platforms including AWS, Azure, and GCP. It analyzes critical threat indicators such as anomalous API activity, impossible travel patterns (impossible login locations), and unauthorized resource provisioning. Designed for incident response, security monitoring, and building robust detection rules to mitigate account takeover and credential abuse.