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Found 1,211 Skills
Guides the agent through installing, authenticating, configuring, and using the Capawesome CLI (@capawesome/cli). Covers installation, interactive and token-based authentication, project linking via capawesome.config.json, the full command reference (app management, native builds, live updates, certificates, environments, channels, deployments, destinations, devices), CI/CD integration with token auth and JSON output, and diagnostics via the doctor command. Do not use for Capawesome Cloud feature setup (native builds workflow, live updates workflow, app store publishing) — use the capawesome-cloud skill instead.
Manage Dokploy infrastructure: projects, applications, databases, domains, compose services, deployments, and servers via the Dokploy REST API. Use whenever the user mentions dokploy, deploying apps, managing servers, creating databases, adding domains, docker compose deployments, checking deployment status/logs, or any PaaS infrastructure management. Even if 'dokploy' isn't mentioned explicitly, trigger when the context involves their self-hosted deployment platform.
Use when the user needs CI/CD pipelines, Docker configuration, Kubernetes deployment, infrastructure-as-code, monitoring, or zero-downtime deployment strategies. Triggers: user says "devops", "docker", "kubernetes", "CI/CD", "infrastructure", "monitoring", "deploy to production", "container", "terraform", "observability".
Use when creating new skills, editing existing skills, or verifying skills work before deployment
Use when planning or reviewing production database migrations, adding columns, indexes, constraints, backfills, renames, table rewrites, or concurrent operations. Covers phased rollouts, lock behavior, rollback strategy, strong_migrations compliance, and deployment ordering for schema changes.
Phoenix operations and deployment: releases, runtime configuration, clustering, libcluster, telemetry/logging, secrets, assets, background jobs, and production hardening on the BEAM.
Deploys and manages services on GuaraCloud — creating projects and services, triggering deployments, rollbacks, scaling, custom domains, and environment variables. Use when the user wants to deploy an app, manage services, configure domains, set env vars, or scale.
The Twelve-Factor App methodology for building scalable, maintainable cloud-native applications. Use when designing backend services, APIs, microservices, or any software-as-a-service application. Triggers on deployment patterns, configuration management, process architecture, logging, and infrastructure decisions.
Early rug-risk triage for token launches and small DeFi deployments from public data—liquidity lock and pool events, dev and sniper wallet clustering, contract authority and transfer-risk checks, coordinated exits, and evidence-backed risk scores. Use when the user asks for rug pull detection, pump-and-dump signals, launch red flags, LP removal forensics, or cross-chain profit exit tracing—not for front-running trades, harassing teams, or certifying scams without on-chain proof.
Static site generators, documentation platforms, and deployment workflows for technical documentation
Next.js adapter for embedding emulators directly in a Next.js app via @emulators/adapter-next. Use when the user needs to embed emulators in Next.js, set up same-origin OAuth for Vercel preview deployments, create an emulate catch-all route handler, configure Auth.js/NextAuth with embedded emulators, add persistence to embedded emulators, or wrap next.config with withEmulate. Triggers include "Next.js emulator", "adapter-next", "embedded emulator", "same-origin OAuth", "Vercel preview", "createEmulateHandler", "withEmulate", or any task requiring emulators inside a Next.js app.
Optimizes LLM inference with NVIDIA TensorRT for maximum throughput and lowest latency. Use for production deployment on NVIDIA GPUs (A100/H100), when you need 10-100x faster inference than PyTorch, or for serving models with quantization (FP8/INT4), in-flight batching, and multi-GPU scaling.