Total 36,018 skills
Showing 12 of 36018 skills
Declare databases, Pub/Sub, cron jobs, and secrets with Encore.ts.
Manage environment variables across Vercel environments. Sync with Vercel CLI, handle local overrides, and load env vars in scripts.
Add a complete account settings page with profile editing, password changes, email updates, session management, and account deletion.
Manage repositories, check pipelines, review merge requests, and monitor CI/CD on GitLab
Advanced Compose Multiplatform UI patterns for shared composables. Use when working with visual UI components, state management patterns (remember, derivedStateOf, produceState), recomposition optimization (@Stable/@Immutable visual usage), Material3 theming, custom ImageVector icons, or determining whether to share UI in commonMain vs keep platform-specific. Delegates navigation to android-expert/desktop-expert. Complements kotlin-expert (handles Kotlin language aspects of state/annotations).
Configure Prettier for code formatting and TypeScript for typechecking. Includes VSCode settings and EditorConfig for consistent code style. Skips ESLint/Biome to avoid config complexity.
Write a description to description GitHub Pull Request.
Run systematic growth experiments to increase acquisition, activation, retention, and revenue. Use when optimizing conversion funnels, running A/B tests, improving metrics, or when users mention growth, experimentation, optimization, or scaling user acquisition.
Validate Next.js 16 configuration and detect/prevent deprecated patterns. Ensures proxy.ts usage, Turbopack, Cache Components, and App Router best practices. Use before any Next.js work or when auditing existing projects.
Set up serverless Postgres with Neon or Vercel Postgres for Cloudflare Workers/Edge. Includes connection pooling, git-like branching, and Drizzle ORM integration. Use when: setting up edge Postgres, troubleshooting "TCP not supported", connection pool exhausted, SSL config errors, or Node v20 transaction issues.
Research ideation partner. Generate hypotheses, explore interdisciplinary connections, challenge assumptions, develop methodologies, identify research gaps, for creative scientific problem-solving.
Cross-platform Python library for quantum computing, quantum machine learning, and quantum chemistry. Enables building and training quantum circuits with automatic differentiation, seamless integration with PyTorch/JAX/TensorFlow, and device-independent execution across simulators and quantum hardware (IBM, Amazon Braket, Google, Rigetti, IonQ, etc.). Use when working with quantum circuits, variational quantum algorithms (VQE, QAOA), quantum neural networks, hybrid quantum-classical models, molecular simulations, quantum chemistry calculations, or any quantum computing tasks requiring gradient-based optimization, hardware-agnostic programming, or quantum machine learning workflows.