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Found 1,991 Skills
Triton Inference Config - Auto-activating skill for ML Deployment. Triggers on: triton inference config, triton inference config Part of the ML Deployment skill category.
This skill should be used when the user asks to "create a new project", "scaffold a Next.js app", "initialize a new app", "start a new project", "set up a new Next.js project", or mentions "create-next-project". Provides an opinionated full-stack Next.js project initialization with Biome, Tailwind v4, shadcn/ui, TanStack Query, better-auth, and Vercel deployment.
ML inference latency optimization, model compression, distillation, caching strategies, and edge deployment patterns. Use when optimizing inference performance, reducing model size, or deploying ML at the edge.
Model Registry Manager - Auto-activating skill for ML Deployment. Triggers on: model registry manager, model registry manager Part of the ML Deployment skill category.
Feature Store Connector - Auto-activating skill for ML Deployment. Triggers on: feature store connector, feature store connector Part of the ML Deployment skill category.
Check and configure GitHub Pages deployment
Use when managing multiple environments with Pulumi stacks for development, staging, and production deployments.
Create a haloy.yaml configuration file for deploying applications with haloy. Use when the user says "create haloy config", "add haloy.yaml", "configure for haloy", "set up haloy deployment", or "prepare for haloy". Supports single-target and multi-target deployments with optional self-hosted databases. Not for creating Dockerfiles (use the dockerize skill), multi-environment deployments, or docker-compose/Kubernetes setups.
Comprehensive mobile DevOps workflow that orchestrates mobile application development, CI/CD for mobile, app store deployment, and mobile device testing. Handles everything from mobile app build automation and testing to app store submission, monitoring, and mobile-specific DevOps practices.
Expert guidance for authoring and maintaining Helm charts following standardized conventions, global registry support, templating best practices, and Kubernetes deployment patterns.
Use when configuring or working with Solid Queue for background jobs. Applies Rails 8 conventions, database-backed job processing, concurrency settings, recurring jobs, and production deployment patterns.
QCSD Verification phase swarm for CI/CD pipeline quality gates using regression analysis, flaky test detection, quality gate enforcement, and deployment readiness assessment. Consumes Development outputs (SHIP/CONDITIONAL/HOLD decisions, quality metrics) and produces signals for Production monitoring.