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Found 1,622 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.
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.
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.
This skill should be used when the user asks to 'start a grid bot', 'create a grid bot', 'stop the grid bot', 'show my grid bots', 'grid bot status', 'grid bot P&L', 'create a DCA bot', 'start a DCA bot', 'dollar cost average into BTC', 'set up a martingale bot', 'show my DCA bots', 'stop the DCA bot', 'DCA P&L', or any request involving creating, stopping, querying, or monitoring grid or DCA (Dollar Cost Averaging / Martingale) bots on OKX CEX. Grid and DCA each cover both spot and contract variants. Requires API credentials. Do NOT use for regular spot/swap/futures orders (use okx-cex-trade), market data (use okx-cex-market), or account balance/portfolio (use okx-cex-portfolio).
Postmark platform help — transactional email delivery via REST API (`POST /email`, `POST /email/batch`), SMTP relay, Message Streams (transactional vs broadcast isolation), Handlebars Templates with layout inheritance, Inbound Email parsing, Webhooks (bounce, delivery, open, click, spam complaint, subscription change, inbound), DMARC Monitoring, Bounce Management (Rebound), Suppressions, Statistics, Bulk API, Sender Signatures, and domain authentication. Use when asking 'how do I do X in Postmark', sending transactional email with Postmark, configuring Message Streams, setting up Postmark templates, processing inbound email via Postmark, managing bounces and suppressions, or troubleshooting Postmark deliverability. Do NOT use for general email marketing strategy (use /sales-email-marketing), cross-platform email deliverability (use /sales-deliverability), email open/click tracking strategy (use /sales-email-tracking), or SendGrid-specific questions (use /sales-sendgrid).
When the user wants to optimize maintenance strategies, improve equipment reliability, reduce downtime, or implement predictive maintenance. Also use when the user mentions "preventive maintenance," "predictive maintenance," "TPM," "Total Productive Maintenance," "MTBF," "MTTR," "reliability analysis," "equipment maintenance," "condition monitoring," "CBM," "failure analysis," or "spare parts optimization." For quality improvements, see quality-management. For OEE, see lean-manufacturing.
Browser automation and testing using chrome-devtools MCP server. Use when automating web browsers, taking screenshots, inspecting console logs, monitoring network requests, testing responsive layouts, collecting performance metrics, or debugging web applications. Critical for visual testing workflows and browser-based automation tasks.
Manages planned cluster maintenance across all tiers. Self-Hosted covers node drain procedures for OS patching, hardware changes, and configuration updates. Advanced/BYOC covers maintenance window configuration, patch scheduling, deferral policies, and monitoring during CRL-managed maintenance. Standard and Basic maintenance is fully managed with no customer action. Use when planning maintenance, configuring maintenance windows, or preparing applications for maintenance events.
The operational playbook for launching a feature well. Positioning, internal alignment, customer comms, sales enablement, support readiness, rollout strategy, monitoring with pre-defined rollback triggers, post-launch measurement against spec hypotheses, and the discipline that distinguishes shipping from releasing from actually launching. Triggers on launch plan, feature launch, launch checklist, ship vs release, rollout strategy, gradual rollout, sales enablement, support readiness, launch announcement, post-launch measurement, launch failure, declared victory too early. Also triggers when planning a launch (any size, any segment), auditing an existing launch process, fixing the we shipped it but the metric did not move problem, or building a launch checklist for the team.
Use when the user wants Instagram research or workflow guidance for lead generation, influencer discovery, brand monitoring, competitor analysis, content analytics, trend research, or audience analysis, including profile analysis, feed collection, post or reel inspection, transcript extraction, comment analysis, reel discovery, highlight retrieval, or embed generation.
How to launch distributed Megatron-LM training jobs on a SLURM cluster. Covers a minimal sbatch skeleton, environment-variable setup for torch.distributed.run, CUDA_DEVICE_MAX_CONNECTIONS rules across hardware and parallelism modes, container conventions, monitoring, and per-rank failure diagnosis.