Skill UI

Implements a robust caching strategy by using the SHA-256 hash of file content as the primary key, instead of the file path. This pattern is essential for high-cost file processing pipelines (like OCR, PDF parsing) because it ensures cache hits survive file renaming or moving, while still automatically invalidating entries when the content changes. It adheres to the Single Responsibility Principle (SRP) by isolating caching logic into a service layer wrapper.

A specialized skill designed for agents to proactively identify, analyze, and strategize high-impact contributions within trending Open Source repositories. It systematically performs repository discovery, extracts targeted issues (like 'help wanted' or 'good first issue'), and conducts deep feasibility analysis (including mergeability and complexity). Finally, it generates a structured 'Contribution Dossier' with actionable plans, significantly accelerating the process of becoming a top-tier OSS contributor.

This skill utilizes the Microsoft Graph API to parse Office 365 Unified Audit Logs for security incident investigation. It is designed to detect critical indicators of account compromise, including the creation of suspicious email forwarding rules, unauthorized mailbox delegation changes, suspicious OAuth application consent grants, and other signs related to Business Email Compromise (BEC).

This skill provides comprehensive guidelines for detecting Business Email Compromise (BEC), a sophisticated fraud scheme. It covers detection techniques using email gateway rules, behavioral analytics, and robust financial process controls. Learn to identify red flags like unusual payment requests, domain mismatches, and patterns of social engineering to protect against financial loss.

This skill guides users on operating the FrontendIntegration resources and the associated frontend-forge extension using kubectl. It covers the full lifecycle management: creating FI from complete YAML, updating status, enabling/disabling, troubleshooting build output, and managing the extension's installation plan. Ideal for DevOps engineers responsible for robust CI/CD pipeline management.

A comprehensive guide and set of tools for establishing a local development workflow tailored for CoreWeave GPU deployments. This includes steps for building Docker containers, validating Kubernetes YAML manifests using dry-run, and managing the full deployment lifecycle for AI inference services before pushing to the cloud.

A comprehensive diagnostic guide for common issues encountered with CAST AI agents, Kubernetes autoscaling, API connectivity, and resource provisioning. Covers scenarios like agent crashes, 401 errors, and scaling failures, providing specific commands (kubectl, curl, helm) and detailed fixes for robust troubleshooting.

This guide addresses the challenges of automating Apple Notes within Continuous Integration (CI) pipelines on macOS. Because standard CI environments restrict TCC (Transparency, Consent, and Control) permissions, direct automation via osascript usually fails. It provides patterns for using mock clients for unit testing and outlines best practices for running real integration tests on self-hosted runners with proper permissions.

This skill provides methods for managing GPU quota limits and rate restrictions for CoreWeave cloud services. It includes using `kubectl` to check resource quotas and demonstrates implementing robust request queuing mechanisms using Python's `asyncio` library, ensuring stable and efficient resource allocation for high-concurrency inference endpoints.

This comprehensive guide assists developers migrating their Miro integrations from REST API v1 to v2. It details key breaking changes, such as 'Widget' becoming 'Item' and 'Line' becoming 'Connector,' provides updated endpoint maps, and offers step-by-step instructions for upgrading the `@mirohq/miro-api` SDK and adapting request/response payloads. Use this resource when updating your integration to handle the latest Miro platform standards and data structures.

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 guide provides comprehensive guidelines for performing vertical scaling on Qdrant instances. Vertical scaling involves upgrading the computational resources (CPU, RAM, or disk) of existing nodes rather than adding new nodes. It is the recommended first step when single nodes experience resource exhaustion (e.g., RAM usage > 80%, CPU saturation). The guide covers sizing guidelines, best practices for cloud deployment, and clearly defines the thresholds when horizontal scaling becomes necessary.