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Found 2,003 Skills
Diagnoses GKE JobSet interruptions, restarts, and preemptions for AI/ML training workloads autonomously. Use when troubleshooting JobSet restart loops, spot VM preemptions, node readiness failures, host VM issues, or coordinator worker crashes. Don't use for general GKE cluster creation, basic workload deployment, or non-JobSet application issues.
Generates and updates secure, production-ready Kubernetes YAML manifests optimized for GKE Autopilot and GKE Standard clusters. Use when creating or modifying GKE deployment manifests, configuring container security contexts, setting CPU/memory resource limits, defining readiness/liveness/startup probes, mounting secrets and volumes, configuring GKE Gateway API routes, targeting Spot VMs, or deploying AI model inference workloads (vLLM, TGI, Gemma). Don't use for live cluster operations, pod troubleshooting (use gke-workload-troubleshooting), or cluster infrastructure provisioning (use gke-cluster-creation).
Validate and configure the local Salesforce development environment. Runs a prerequisite scan showing 🔴/🟡/🟢 status for all required tools (Salesforce CLI, Code Analyzer plugin, Node.js, NPM, Git, Salesforce MCP, Source Tracking) and offers to install or update missing/outdated items. TRIGGER when the user runs /salesforce-development:platform-environment-validate, asks to 'check my setup', 'validate tools', 'verify prerequisites', 'am I set up correctly', or reports that a tool is missing or not working. DO NOT TRIGGER for: org authentication issues (use /salesforce-development:login), deployment problems (use platform-metadata-deploy), or general status checks (use /salesforce-development:status).
Use this skill to manage the full lifecycle of a DevOps Center pipeline — list all pipelines, get a single pipeline's details, create a new pipeline linked to a Git repository, add or remove stages, rename a stage, add or remove Salesforce environments on stages, attach or detach projects, and activate or deactivate the pipeline. Invoke when the user wants to set up a release pipeline, wire promotion stages across integration, UAT, staging, and production orgs, connect environments to stages, attach a project, or activate a continuous delivery pipeline. Uses sf devops pipeline and sf devops stage commands with --json output. DO NOT TRIGGER for work-item lifecycle, promotion or deployment execution, conflict detection, or standalone project creation (separate skills).
Beat 4 editorial skill — "Protocol and Infrastructure Updates" signal composition, source validation, and editorial voice guide for aibtc.news correspondents covering API changes, contract deployments, MCP updates, protocol upgrades, bugs, and breaking changes.
[Architecture] Full solution architecture: backend + frontend patterns, design patterns, library ecosystem, CI/CD, deployment, monitoring, testing, code quality, dependency risk. Compare top 3 approaches per concern with recommendation.
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.
Master end-to-end testing to build reliable test suites that catch bugs, improve confidence, and enable fast deployment. Use when implementing E2E tests, debugging flaky tests, or establishing testing standards.
Reusable better-chatbot patterns for custom deployments. Use for server action validators, tool abstraction, multi-AI providers, or encountering auth validation, FormData parsing, workflow execution errors.
Generate complete production-ready SaaS boilerplate with authentication, database schemas, billing integration (Stripe), multi-tenancy, API routes, dashboard UI, and deployment configuration. Supports Next.js App Router, TypeScript, Tailwind, shadcn/ui, Drizzle ORM, and multiple auth/payment providers. Use when starting a new SaaS product, subscription app, or multi-tenant platform.
Create and run LangWatch experiments for pre-deployment batch testing. Use when the user wants to test an agent against a dataset, compare prompts or models, benchmark quality, detect regressions, or add a CI quality gate. Do not use for production monitoring or guardrails.
You are an advanced Docker containerization expert with comprehensive, practical knowledge of container optimization, security hardening, multi-stage builds, orchestration patterns, and production deployment strategies based on current industry best practices.