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Found 2,418 Skills
C++ Reinforcement Learning best practices using libtorch (PyTorch C++ frontend) and modern C++17/20. Use when: - Implementing RL algorithms in C++ for performance-critical applications - Building production RL systems with libtorch - Creating replay buffers and experience storage - Optimizing RL training with GPU acceleration - Deploying RL models with ONNX Runtime
Build Progressive Web Apps with Next.js: service workers, offline support, caching strategies, push notifications, install prompts, and web app manifest. Use when creating PWAs, adding offline capability, configuring service workers, implementing push notifications, handling install prompts, or optimizing PWA performance. Triggers: PWA, progressive web app, service worker, offline, cache strategy, web manifest, push notification, installable app, Serwist, next-pwa, workbox, background sync.
Use the whoo CLI to retrieve and interpret WHOOP health data: recovery score, HRV, sleep quality, strain, SpO2, and body measurements. Invoke when the user asks about their WHOOP metrics, readiness, fitness recovery, sleep performance, wearable health data, or wants to pull or analyze WHOOP data for any date range.
Enforces TheOne Studio React Native development standards including TypeScript patterns, React/Hooks best practices, React Native architecture (Zustand/Jotai, Expo Router), and mobile performance optimization. Triggers when writing, reviewing, or refactoring React Native code, implementing mobile features, working with state management/navigation, or reviewing pull requests.
Query Developer Experience (DX) data via the DX Data MCP server PostgreSQL database. Use this skill when analyzing developer productivity metrics, team performance, PR/code review metrics, deployment frequency, incident data, AI tool adoption, survey responses, DORA metrics, or any engineering analytics. Triggers on questions about DX scores, team comparisons, cycle times, code quality, developer sentiment, AI coding assistant adoption, sprint velocity, or engineering KPIs.
APM - traces, services, dependencies, performance analysis.
Swift language patterns and best practices including concurrency, performance, and modern idioms. Use for Swift language-level code review or architecture guidance.
Test application performance, scalability, and resilience. Use when planning load testing, stress testing, or optimizing system performance.
Use when building SwiftUI views, managing state with @Observable, implementing NavigationStack or NavigationSplitView navigation patterns, composing view hierarchies, presenting sheets, wiring TabView, applying SwiftUI best practices, or structuring an MV-pattern app. Covers view architecture, state management, navigation, view composition, layout, List, Form, Grid, theming, environment, deep links, async loading, and performance.
Coordinates performance optimization: algorithm, query, and runtime workers in parallel
Review git diffs, staged changes, and GitHub PRs. Change-focused analysis across seven pillars (Security, Performance, Architecture, Error Handling, Testing, Maintainability, Paranoia) with numeric scoring 1-10. Supports GitHub PR review, staged changes, and arbitrary diffs. Use when: reviewing a PR, reviewing staged changes, reviewing a diff, pre-commit review. Triggers: review PR, review my changes, review the diff, review staged, review-pr, check my changes.
Use when monitoring Xiaohongshu marketing campaign performance, tracking promotion effectiveness, analyzing advertising ROI, measuring influencer collaboration results, evaluating activity success rates, or optimizing marketing spend allocation