Skill UI

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.

A comprehensive skill for analyzing AWS spending patterns and identifying areas of waste. It provides actionable strategies to reduce cloud costs by detecting idle resources (like unattached EBS volumes or unused Elastic IPs), recommending Reserved Instances, and generating reports using AWS CLI and Cost Explorer data.

A comprehensive workflow for systematically reviewing medical evidence. It allows users to search databases for clinical studies, build curated citation collections, grade evidence using established frameworks like GRADE, and generate professionally formatted, structured reports in academic citation styles (e.g., AMA). Ideal for conducting literature reviews and supporting clinical research. This tool helps transform raw medical data into actionable, structured knowledge.

This module provides minimal working examples for the OpenEvidence API, designed for clinical intelligence applications. Users can perform complex clinical queries to get treatment recommendations, check potential drug interactions based on patient context, and search for authoritative medical guidelines from major health organizations (e.g., ACC/AHA). Ideal for developing evidence-based healthcare decision support systems.

This comprehensive workflow guides developers through implementing full-stack product analytics using PostHog. It covers key areas including defining event taxonomies, capturing user actions (client-side), identifying and updating user properties, and performing B2B group analytics. It also demonstrates server-side event tracking using posthog-node, ensuring a complete, accurate, and traceable view of user behavior and product usage across web, mobile, and API sources.

This guide provides minimal working examples demonstrating the three core PostHog functionalities: event capture, user identification, and feature flag evaluation. It covers both server-side (Node.js, Python) and client-side (JavaScript) SDK usage, as well as direct API calls, making it perfect for initial integration setup, testing, and learning basic product analytics patterns.

The LinkedIn Automation CLI Tool allows users to programmatically interact with LinkedIn content and functionality. It supports fetching detailed profiles, searching people and companies, and managing connections directly from scripts or AI agents. Ideal for building automated research, recruiting, or outreach workflows, providing structured JSON output for reliable integration into custom systems.

Programmatically query ChEMBL bioactive molecules, targets, and approved drugs via the Python client; filter by structure, properties, activities, and indications to support inhibitor hunting or SAR studies for medicinal chemistry.

Generates publication-ready clinical decision support documents for pharma and clinical research, covering biomarker-stratified cohort analysis, evidence-graded treatment recommendations, statistical comparisons, and regulatory-ready LaTeX/PDF outputs.

Access the ClinicalTrials.gov API v2 to search trials by condition, drug, location, sponsor or status, fetch details via NCT ID, and export JSON/CSV data for research analysis, patient matching, and trial monitoring.

Provide REST API access to ClinPGx, the successor to PharmGKB, for querying gene-drug interactions, CPIC/DPWG/FDA guidelines, allele functions, and evidence that supports precision dosing and pharmacogenomics-driven clinical decisions.

Query NCBI ClinVar for variant clinical significance, mixing gene/condition searches, API/FTP downloads, and VCF annotations to support genomic medicine interpretation workflows.