Skill UI

A comprehensive tool for interacting with Notion via its API. It allows users to perform workspace-wide searches, run complex queries against structured databases using compound filters (AND/OR), retrieve specific pages, and deeply traverse and extract all nested block content. Supports pagination for handling large datasets, enabling full data visibility and structured data extraction.

This skill provides a comprehensive operational checklist for identifying and exploiting HTTP Parameter Pollution (HPP) vulnerabilities. It details how various web technologies (ASP.NET, PHP, Python, etc.) handle duplicate parameters differently (e.g., first-wins, last-wins, concatenation). Use this skill during penetration testing to discover flaws in parameter parsing, which can lead to bypassing WAFs, performing logic manipulation, or achieving unauthorized access.

A comprehensive guide and implementation pattern for querying, searching, and paginating OneNote content using the Microsoft Graph API. This skill addresses the limitations of the standard OneNote search endpoint, providing robust methods for cross-notebook querying, advanced OData filtering on metadata, and client-side full-text indexing for body content. Ideal for building complex knowledge retrieval systems that handle large, distributed result sets.

A comprehensive guide for optimizing OneNote Graph API interactions at scale. It addresses common performance bottlenecks such as slow data retrieval from large notebooks, handling excessive image sizes, implementing efficient payload selection ($select), and paginating massive data sets using $top. Essential for building stable, high-performance automation workflows.

This skill provides comprehensive functionality for provisioning, managing, and scaling Oracle Cloud Infrastructure (OCI) compute instances using the Python SDK. It addresses common challenges like "out of host capacity" errors by implementing robust retry logic across multiple Availability Domains (ADs). Users can select optimal Flex shapes (AMD, ARM, Intel), manage the entire instance lifecycle (start, stop, reboot, terminate), and retrieve network details, ensuring reliable cloud workload deployment.

This skill provides a comprehensive Python guide to building a production-ready Virtual Cloud Network (VCN) on Oracle Cloud Infrastructure (OCI). It details the entire process from scratch, including creating the VCN, setting up Internet and NAT Gateways, configuring route tables, and defining Network Security Groups (NSGs). This is essential for engineers needing to provision complex, secure, and highly functional network architectures for development or production use.

This skill provides a comprehensive solution for deploying containerized applications to Oracle Cloud Infrastructure (OCI). It supports two primary deployment paths: OKE (Oracle Kubernetes Engine) for full Kubernetes orchestration, and Container Instances for a simpler, serverless alternative. Use this skill for automating the entire lifecycle, including pushing images to OCIR, provisioning OKE clusters via Python SDK, and executing Kubernetes deployments using kubectl.

This skill addresses the challenge of managing Dev/Staging/Prod separation in OCI without native account separation. It uses Python to centralize configuration profiles, compartment IDs, and implements safety guardrails (like blocking destructive actions in production) to prevent accidental cross-environment deployments, ensuring repeatable and secure cloud workflows.

This skill allows users to programmatically set up a comprehensive observability stack for Oracle Cloud Infrastructure (OCI) resources. It guides the creation of metric queries, alarm rules, custom metric publishing, and detailed log searches using the Python SDK. By automating monitoring and alerting, users gain full control over their infrastructure visibility, eliminating reliance on the OCI Console UI for critical operational checks.

Provides a comprehensive, production-ready standard 3-tier reference architecture for Oracle Cloud Infrastructure (OCI). The design covers essential components like VCN, public/private subnets, Internet Gateway, NAT Gateway, Service Gateway, and Autonomous Database. It includes deployment steps using Terraform and OCI SDK Python code, making it ideal for designing new cloud environments or migrating existing patterns from other major cloud providers.

This guide provides advanced techniques for optimizing performance within Palantir Foundry. It covers efficient pagination, implementing client-side caching, using batch object retrieval (solving the N+1 problem), and tuning Spark transforms with memory configuration and incremental updates. Use this when experiencing slow API responses or inefficient data pipeline builds in Foundry.

This guide provides production-ready patterns for integrating with the Palantir Foundry Platform SDK. It covers essential best practices like implementing thread-safe singletons, structured error handling, automatic pagination for large data sets, and robust retry mechanisms with exponential backoff. Ideal for refactoring existing Foundry integrations or establishing team coding standards.