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Found 1,816 Skills
Expert in building scalable ML systems, from data pipelines and model training to production deployment and monitoring.
Helm chart development patterns for packaging and deploying Kubernetes applications. Use when creating reusable Helm charts, managing multi-environment deployments, or building application catalogs for Kubernetes.
Deploy ECS tasks and services with GitHub Actions CI/CD. Use for building Docker images, pushing to ECR, updating ECS task definitions, deploying ECS services, integrating with CloudFormation stacks, configuring AWS OIDC authentication for GitHub Actions, and implementing production-ready container deployment pipelines. Automate ECS deployments with proper security (OIDC or IAM keys), multi-environment support, blue/green deployments, ECR private repositories with image scanning, and CloudFormation infrastructure updates.
Deploy applications and websites to Vercel. Use this skill when the user requests deployment actions such as 'Deploy my app', 'Deploy this to production', 'Create a preview deployment', 'Deploy and give me the link', or 'Push this live'. No authentication required - returns preview URL and claimable deployment link.
6-phase investigation workflow for understanding existing systems. Auto-activates for research tasks. Optimized for exploration and understanding, not implementation. Includes parallel agent deployment for efficient deep dives and automatic knowledge capture to prevent repeat investigations.
LLM and ML model deployment for inference. Use when serving models in production, building AI APIs, or optimizing inference. Covers vLLM (LLM serving), TensorRT-LLM (GPU optimization), Ollama (local), BentoML (ML deployment), Triton (multi-model), LangChain (orchestration), LlamaIndex (RAG), and streaming patterns.
Implement graceful server shutdown to handle in-flight requests before stopping. Use for zero-downtime deployments and proper resource cleanup.
Set up GitHub CLI and Vercel CLI, authenticate both, create a repo, and link it to Vercel for automatic deployments. One-time setup that makes all other Treehaus builder skills work.
Use this skill when users need to create, generate, or validate Salesforce Custom Object metadata. Trigger when users mention custom objects, creating objects, object metadata, .object files, sharing models, name fields, or validation rules on objects. Also use when users say things like "create a custom object", "generate object metadata", "set up an object for...", or when they're troubleshooting object deployment errors especially around sharing models and Master-Detail relationships. Always use this skill for any custom object metadata work.
Deploy open models or custom weights from Model Garden to Agent Platform endpoints, check deployment status, verify serving endpoints, or clean up resources by undeploying models and deleting endpoints. Use when asked to deploy models on Agent Platform, list available Model Garden models, check if a model is deployable, query deployment cost, troubleshoot deployment errors (like quota limits), or undeploy/clean up endpoints. Also use when copying and deploying a 1P Tuned Model. Don't use for public Vertex AI deployments (use the `vertex-deploy` skill) or for running model evaluations (use the `agent-platform-eval` skill).
Build, deploy, and manage Cargo Hosting apps and workers with the Cargo CLI — Vite SPAs served on *.cargo.app and serverless edge HTTP handlers, plus the deployments that ship and promote them. Use when the user wants to scaffold, deploy, promote, or manage a hosted app or worker on Cargo.
Automate Flutter app builds and deployments to both the App Store and Google Play using Fastlane with this step-by-step guide.