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Found 444 Skills
Build LLM applications using Dify's visual workflow platform. Use when creating AI chatbots, implementing RAG pipelines, developing agents with tools, managing knowledge bases, deploying LLM apps, or building workflows with drag-and-drop. Supports hundreds of LLMs, Docker/Kubernetes deployment.
Configures automated infrastructure monitoring with mobile alerts (ntfy.sh and Home Assistant) and implements auto-recovery for common failures. Use when setting up monitoring, configuring mobile notifications, enabling auto-recovery, or troubleshooting alert delivery. Triggers on "setup monitoring", "configure alerts", "mobile notifications", "enable auto-recovery", "monitoring not working", or "not getting alerts". Works with ntfy.sh push notifications, Docker container health checks, Bash monitoring scripts, and optional Home Assistant automation integration.
Deploys applications to TrueFoundry. Handles single HTTP services, async/queue workers, multi-service projects, and declarative manifest apply. Supports `tfy apply`, `tfy deploy`, docker-compose translation, and CI/CD pipelines. Use when deploying apps, applying manifests, shipping services, or orchestrating multi-service deployments.
Install and configure NVIDIA NemoClaw (sandboxed OpenClaw agent platform) on Linux. Handles cloudflared tunnels, Docker cgroup fixes, OpenShell, sandbox creation, remote access via Cloudflare Tunnel, and known bug workarounds. Triggers: "install nemoclaw", "setup nemoclaw", "nvidia nemoclaw", "openclaw setup", "nemoclaw on spark", "nemoclaw on dgx".
Expert knowledge for Azure Translator development including troubleshooting, best practices, decision making, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when using Translator text/document APIs, custom models, glossaries, Docker containers, or Power Automate flows, and other Azure Translator related development tasks. Not for Azure AI Language (use azure-language-service), Azure AI Speech (use azure-speech), Azure AI Immersive Reader (use azure-immersive-reader), Azure AI Search (use azure-cognitive-search).
MUST USE for anything related to mise, development tool versions, or dev environment setup. Triggers: (1) User mentions mise, mise.toml, .tool-versions, or mise commands like 'mise use', 'mise install', 'mise run'. (2) User wants to install, switch, pin, upgrade, or check versions of dev tools — node, python, go, ruby, java, rust, etc. — at project or global level, even without mentioning mise (e.g. 'set up node 22', 'what python version', 'upgrade go', 'check for outdated tools', 'configure dev environment'). (3) User wants to manage per-project environment variables via config files (e.g. 'add DATABASE_URL env var', 'set up env vars for different environments'). (4) User wants to define or run project tasks via mise (e.g. 'create a build task', 'run tests with mise'). Do NOT trigger for: Dockerfiles, package.json scripts, Makefiles, nvm/pyenv/rbenv commands, pip/npm package installation, git tags, CI/CD config, or deployment.
Interactive setup guide for using Infisical as a secret management tool in your projects. Helps users integrate Infisical into local development (CLI), Docker containers (build-time and runtime secret injection), CI/CD pipelines (GitHub Actions, GitLab CI), Kubernetes (Operator + CRDs), and application code (Node.js, Python, Go, Java, .NET, Ruby SDKs). Also walks through choosing and configuring machine identity auth methods (Universal Auth, AWS Auth, Kubernetes Auth, OIDC, etc.). Use this skill whenever someone asks about: using Infisical, injecting secrets, infisical run, infisical init, connecting their app to Infisical, Docker secrets, Kubernetes secrets operator, machine identity setup, SDK initialization, CI/CD secret injection, or 'how do I get my secrets into my app'.
Production-grade Helm 4 chart development, release management, and debugging. This skill should be used when users ask to create Helm charts, deploy with Helm, manage releases (install/upgrade/rollback), push charts to OCI registries, debug failed deployments, configure chart dependencies, create umbrella charts, set up GitOps with ArgoCD/Flux, or troubleshoot Helm issues. Auto-detects from Dockerfile/code, generates production-hardened charts with library patterns. Complements kubernetes skill.
WordPress Playground for instant browser-based WordPress testing. Use for quick demos, plugin testing, or ephemeral development environments without Docker.
Fine-tune LLMs with Unsloth using GRPO or SFT. Supports FP8, vision models, mobile deployment, Docker, packing, GGUF export. Use when: train with GRPO, fine-tune, reward functions, SFT training, FP8 training, vision fine-tuning, phone deployment, docker training, packing, export to GGUF.
Build MCP servers in Python with FastMCP. Workflow: define tools and resources, build server, test locally, deploy to FastMCP Cloud or Docker. Use when creating MCP servers, exposing tools/resources/prompts to LLMs, building Claude integrations, or troubleshooting FastMCP module-level server, storage, lifespan, middleware, OAuth, or deployment errors.
Expert-level Kamal deployment guidance for deploying containerized applications to any server. Use this skill when users ask about Kamal, container deployment, zero-downtime deployments, deploying Rails/web apps to VPS/cloud servers, kamal setup, kamal deploy, Docker deployment without Kubernetes, or deploying to Hetzner/DigitalOcean/AWS with Kamal. Also use when users mention DHH's deployment tool, 37signals deployment, or want an alternative to Heroku/Render/Vercel with self-hosted infrastructure.