Skill UI

This guide outlines the implementation of Remote Browser Isolation (RBI) as a core component of a Zero Trust architecture. It details policies for URL risk classification, Data Loss Prevention (DLP) controls, and Content Disarm and Reconstruction (CDR). This is essential for hardening web access, protecting against zero-day exploits, phishing, and preventing data exfiltration from untrusted web content.

This skill provides comprehensive guardrails for handling Protected Health Information (PHI) in US healthcare software. It guides development teams on data classification, security best practices, access control, and audit logging to ensure strict adherence to HIPAA regulations. Use it when dealing with patient data storage, transmission, or processing to prevent breaches and maintain compliance.

This skill guides users on setting up and running LLM-as-judge evaluations using Arize. It covers defining evaluators (including prompts, classification choices, and models) and executing tasks against real data spans or experiments. It supports key metrics like hallucination, faithfulness, and correctness, and facilitates continuous monitoring for comprehensive LLM performance analysis.

Aeon is a comprehensive, scikit-learn compatible Python toolkit designed for advanced time series analysis. It supports a wide range of temporal machine learning tasks, including classification, regression, clustering, forecasting, anomaly detection, and similarity search. Use this skill when working with sequential patterns, time-indexed observations, or complex temporal data that requires specialized algorithms.

A comprehensive resource detailing the use of scikit-learn, the industry-standard Python library for classical machine learning. Use this skill for the entire ML lifecycle, including supervised tasks (classification, regression), unsupervised tasks (clustering, dimensionality reduction), data preprocessing, model evaluation, and building production-ready pipelines.

PyTorch Geometric (PyG) is the definitive standard library for building Graph Neural Networks (GNNs) atop PyTorch. It provides specialized data structures for handling diverse graph types, including heterogeneous graphs. The library offers over 60 GNN layer implementations (such as GCN, GAT, GraphSAGE), full support for dataset loading (Planetoid, TUDataset, OGB), and necessary data transformations. It is essential for deep learning tasks involving node classification, graph classification, and link prediction.

The Hugging Face Transformers library is a comprehensive toolkit providing access to thousands of pre-trained models across diverse domains including Natural Language Processing (NLP), Computer Vision, Audio, and Multimodal tasks. It enables developers to easily load models, perform high-level inference (e.g., text generation, classification, QA), and fine-tune models on custom datasets using streamlined APIs like Pipelines and the Trainer class. Ideal for building advanced, state-of-the-art AI applications.

This skill provides comprehensive methods for interacting with the Figma API. It covers retrieving and managing comments, accessing version history, and handling sensitive user data. Emphasis is placed on implementing robust privacy controls, PII redaction, data classification, and ensuring compliance with regulations like GDPR/CCPA.

Implements robust data governance for Canva Connect API interactions. This skill covers data classification (PII, Secrets, Business), token redaction, temporary URL expiry, and enforces strict data retention policies. It is essential for developers building integrations that must adhere to global privacy standards like GDPR and CCPA, ensuring secure data handling from ingestion to deletion.

A comprehensive runbook for responding to critical incidents involving Flexport API integrations. It covers various failure scenarios, including complete API outages, webhook delivery loss, and complex supply chain data synchronization issues. The guide provides severity classification (P1-P4), diagnostic commands, and step-by-step playbooks for rapid triage and mitigation.

This collection provides production-ready, idiomatic patterns for the @hubspot/api-client SDK, specifically tailored for TypeScript. It addresses critical development concerns including creating typed wrappers, implementing robust, structured error classification (handling rate limits, authentication issues, etc.), and managing efficient batch operations (create, read, upsert) for HubSpot CRM data. Use this when building scalable, reliable, and maintainable HubSpot integrations.

This guide teaches best practices for configuring robust, enterprise-grade Role-Based Access Control (RBAC) within Palantir Foundry. Learn how to define project roles (Viewer, Editor, Owner), manage organization-level groups to enforce least privilege, establish secure service user accounts for external integrations, and utilize marking-based data classification to ensure data governance and security across large datasets.