Loading...
Loading...
Found 844 Skills
Patterns for sharing code between macOS and iOS in SwiftUI apps. Covers project structure (70% shared / 15% macOS / 15% iOS), platform abstraction via protocols and #if os() conditional compilation, adaptive navigation (NavigationSplitView on Mac/iPad → NavigationStack on iPhone), shared components with platform styling, iOS-specific extensions (custom keyboard extension, interactive widgets, share extension, action extension, Control Center widget, lock screen widget), App Groups for data sharing with extensions, CloudKit sync monitoring, JSON export/import, schema versioning and migration, URL scheme deep linking, and the full macOS→iOS migration checklist. Use when building apps that target both macOS and iOS, when adding iOS support to a macOS app, when building widgets or keyboard extensions, or when setting up iCloud sync with SwiftData.
Manage agent fleet through CRUD operations and lifecycle patterns. Use when creating, commanding, monitoring, or deleting agents in multi-agent systems, or implementing proper resource cleanup.
System-wide keyboard shortcut registration on macOS using NSEvent monitoring (simple, app-level) and Carbon EventHotKey API (reliable, system-wide). Covers NSEvent.addGlobalMonitorForEvents and addLocalMonitorForEvents, CGEvent tap for keystroke simulation, Carbon RegisterEventHotKey for system-wide hotkeys, modifier flag handling (.deviceIndependentFlagsMask), common key code mappings, debouncing, Accessibility permission requirements (AXIsProcessTrusted), and SwiftUI .onKeyPress for in-app shortcuts. Use when implementing global keyboard shortcuts, hotkey-triggered panels, or system-wide key event monitoring.
Takes activated influencers and their deliverables and generates a structured monitoring checklist specifying what to capture on each platform, when to check, and what to do if content goes missing. This skill should be used when building a content monitoring plan for a creator campaign, creating a checklist to track influencer deliverables across platforms, setting up a capture schedule for Instagram Stories before they expire, planning when to screenshot or capture creator posts, building a monitoring cadence for TikTok and YouTube deliverables, organizing content capture across multiple creators and platforms, making sure no creator content slips through the cracks, preparing a content tracking plan before a campaign goes live, or setting up a system to catch expiring Stories and time-sensitive posts. For checking whether submitted content matches the brief, see content-to-brief-compliance-checker. For tracking which creators have posted versus who is overdue, see creator-posting-compliance-tracker.
Implement Real User Monitoring (RUM) to capture actual user performance data including Core Web Vitals and page load times. Use when setting up user experience monitoring or tracking custom performance events. Trigger with phrases like "setup RUM", "track Core Web Vitals", or "monitor real user performance".
Comprehensive Kubernetes and OpenShift cluster management skill covering operations, troubleshooting, manifest generation, security, and GitOps. Use this skill when: (1) Cluster operations: upgrades, backups, node management, scaling, monitoring setup (2) Troubleshooting: pod failures, networking issues, storage problems, performance analysis (3) Creating manifests: Deployments, StatefulSets, Services, Ingress, NetworkPolicies, RBAC (4) Security: audits, Pod Security Standards, RBAC, secrets management, vulnerability scanning (5) GitOps: ArgoCD, Flux, Kustomize, Helm, CI/CD pipelines, progressive delivery (6) OpenShift-specific: SCCs, Routes, Operators, Builds, ImageStreams (7) Multi-cloud: AKS, EKS, GKE, ARO, ROSA operations
End-to-end application deployment orchestration for the Kubernetes homelab. Use when: (1) Deploying a new application to the cluster, (2) Adding a new Helm release to the platform, (3) Setting up monitoring, alerting, and health checks for a new service, (4) Research before deploying, (5) Testing deployment on dev cluster before GitOps promotion. Triggers: "deploy app", "add new application", "deploy to kubernetes", "install helm chart", "/deploy-app", "set up new service", "add monitoring for", "deploy with monitoring"
Provides NodeReal MegaNode blockchain infrastructure APIs for 25+ chains including BSC, Ethereum, opBNB, Optimism, Polygon, Arbitrum, and Klaytn. Covers standard JSON-RPC endpoints, Enhanced APIs (nr_ methods for ERC-20 token balances, NFT holdings, asset transfers), MegaFuel gasless transactions via BEP-322 paymaster, Direct Route MEV protection, Debug/Trace APIs, WebSocket subscriptions, ETH Beacon Chain consensus layer, Portal API usage monitoring, API Marketplace (NFTScan, Contracts API, SPACE ID, Greenfield, BNB Staking, PancakeSwap, zkSync), non-EVM chains (Aptos, NEAR, Avalanche), and JWT authentication. Use when building blockchain dApps with NodeReal, querying token or NFT data, setting up RPC infrastructure, configuring gasless transactions, protecting against MEV, tracing transactions, verifying smart contracts, resolving .bnb domains, or monitoring validators and API usage.
Open-source AI observability platform for LLM tracing, evaluation, and monitoring. Use when debugging LLM applications with detailed traces, running evaluations on datasets, or monitoring production AI systems with real-time insights.
Configure Prometheus Alertmanager with routing trees, receivers (Slack, PagerDuty, email), inhibition rules, silences, and notification templates for actionable incident alerting. Use when implementing proactive monitoring with automated incident detection, routing alerts to the appropriate team by severity, reducing alert fatigue through grouping and deduplication, integrating with on-call systems like PagerDuty, or migrating from legacy alerting to Prometheus-based alerting.
Unified YouTube script creation for cardiology channels in Hinglish. Uses the COMPLETE research-engine pipeline (channel scraping, comment analysis, narrative monitoring, gap finding, view prediction) combined with RAG + PubMed for evidence. Data-driven topic selection, 15-30 min educational videos with 6-point voice check.
Monitor topics of interest and proactively alert when important developments occur. Use when user wants automated monitoring of specific subjects (e.g., product releases, price changes, news topics, technology updates). Supports scheduled web searches, AI-powered importance scoring, smart alerts vs weekly digests, and memory-aware contextual summaries.