Kubernetes native configuration management with Kustomize. Use for environment-specific configs, resource patching, manifest organization, multi-environment deployments, and…
Use when customizing Kubernetes configurations without templates using Kustomize overlays and patches.
Kustomize Kubernetes configuration — bases, overlays, patches, generators, transformers
Use when managing environment-specific Kubernetes configurations with Kustomize overlays and patches.
Framework for building LLM-powered applications with agents, chains, and RAG. Supports multiple providers (OpenAI, Anthropic, Google), 500+ integrations, ReAct agents, to — from…
Deploy LangChain applications to production with LangServe, Docker, and cloud platforms (Cloud Run, AWS Lambda).
Production readiness checklist for LangChain applications. Use when preparing for launch, validating deployment readiness, or auditing existing production LangChain systems.
A powerful Python-based visual framework for building and deploying AI-powered agents and workflows with Model Context Protocol (MCP) integration, drag-and-drop interface, and…
Docker volume backup and restore for self-hosted Langfuse. Use when: backing up a self-hosted Langfuse instance, restoring Langfuse after a crash or migratio...
Deploy Langfuse with your application across different platforms. Use when deploying Langfuse to Vercel, AWS, GCP, or Docker, or integrating Langfuse into your deployment…
Configure Langfuse across development, staging, and production environments. Use when setting up multi-environment deployments, configuring per-environment keys, or implementing…
Manage Langfuse instances (cloud or self-hosted) from the CLI — export/import prompts for backup and cross-env migration, send smoke-test traces, check health across multiple…
Architect-level development, audit, and migration of multi-agent systems using LangGraph (v1+) and LangChain (v1+).
LangSmith Agent Builder - No-code platform for creating AI agents with built-in tools (Gmail, Slack, GitHub, Linear), OAuth integrations, MCP server support, Slack deployment, and…
Playbook for launching, monitoring, stopping, and debugging NeMo-RL recipes on a Kubernetes cluster via the nrl-k8s CLI.
Help a technical founder build whatever they want on Claude Managed Agents — an internal worker, a piece of their product, a customer-facing agent.
LazyDocker is a terminal UI for Docker and Docker Compose that provides container management, log viewing, resource monitoring, and image inspection through a keyboard-driven…
Retrieval-augmented Lean4 proof generation. Queries 94k+ exemplars from DeepSeek-Prover V1+V2, uses hybrid search (BM25 + semantic + graph), generates via Claude, compiles in…
Creates runbook.md for DevOps setup. L3 Worker invoked CONDITIONALLY when hasDocker detected.
Builds and launches Docker containers with health verification using best practices
Best practices for GitHub Actions workflows including security, performance, and maintenance
Comprehensive Slint GUI development expert based on official source code. Covers Rust integration, component design, layouts, styling, animations, cross-platform deployment, and…
Meta-skill that indexes, optimizes, and auto-generates Claude skills with GitOps automation, OCA GitHub bot integration, and Odoo developer tools.
librel - Release management tools. VersionBumper handles semver version bumping for packages. ChangeDetector identifies changed packages between git commits.
Optimized Kubernetes distributions and configurations for resource-constrained edge and IoT deployments
Deploy applications that integrate with Lindy AI agents. Use when deploying webhook receivers, callback handlers, or applications connected to Lindy agents.
Production readiness checklist for Lindy AI agent deployments. Use when preparing agents for production, auditing live agents, or validating go-live readiness.
Deploy Linear-integrated applications and track deployments. Use when deploying to production, linking deploys to issues, or setting up deployment tracking with…
Production readiness checklist for Linear integrations. Use when preparing to deploy, reviewing production requirements, or auditing existing Linear deployments.
Linkerd service mesh — lightweight Kubernetes mesh, mTLS, traffic splitting, observability
Run chart-focused lint and install checks so changed Helm charts are validated before release or merge.
Run ansible-lint against playbooks, roles, and collections so risky patterns and common mistakes are caught before automation is merged or executed.
Validate workflow syntax, expressions, and shell steps before broken GitHub Actions changes reach CI.
Inspect a live Kubernetes cluster for unhealthy resource settings, missing probes, and other operational smells.
Check Terraform before plan or apply so invalid attributes, provider-specific mistakes, and custom rule violations are caught early.
Check certificates and precertificates for Web PKI standards violations before CA issuance, trust-store submission, or deployment.
Unified LLM API with LiteLLM. Call 100+ LLM providers with one interface. Use for multi-provider AI, cost optimization, fallbacks, and LLM gateway deployment.
Build voice AI agents with LiveKit Agents SDK. Use when the user asks to "build a voice agent", "create a LiveKit agent", "add voice AI", "implement handoffs", "structure agent…
Runs LLM inference on CPU, Apple Silicon, and consumer GPUs without NVIDIA hardware. Use for edge deployment, M1/M2/M3 Macs, AMD/Intel GPUs, or when CUDA is unavailable — from…
Expert LLM architect specializing in large language model architecture, deployment, and optimization.
Use when user needs LLM system architecture, model deployment, optimization strategies, and production serving infrastructure.
当需要部署或训练 LLM/VLM 时使用；覆盖 vLLM OpenAI-compatible 服务、多模态输入限制、Qwen3.5 工具调用、thinking/reasoning 控制、CUDA Graph 策略，以及 ms-swift SFT/DPO/GRPO full training、数据校验、显存排错和训练检查。
LLM deployment and serving — vLLM, Ollama, TGI, llama.cpp. Model quantization, GPU optimization, API serving
LLM inference infrastructure, serving frameworks (vLLM, TGI, TensorRT-LLM), quantization techniques, batching strategies, and streaming response patterns.
Install and configure LLMem for an agent harness. Handles CLI install, plugin deployment, skill registration, and provider setup.
LMCache multiprocess (MP) mode — standalone LMCache server in its own pod/process that vLLM connects to over ZMQ.
Creates infrastructure.md and runbook.md (Docker-conditional). Use for DevOps documentation in any project.
Sets up Docker, CI/CD, and environment configuration with auto-detection. Use when adding DevOps infrastructure to a project.
Configures health check endpoints for Kubernetes readiness/liveness/startup probes. Use when deploying to Kubernetes.
Builds and launches Docker containers with health verification. Use when validating that containerized services start correctly.
LobeChat - Open-source AI agent workspace with multi-provider LLM support, plugin system, knowledge base RAG, 505+ agents, and self-hosting options via Docker/Vercel
Software Development for Dummies: Guides no brainers through the software development process, providing step-by-step instructions and best practices for requirements gathering,…
Как поднять локальный стенд Sb0rka (docker-compose: Postgres, auth, api, drones, proxy) и получить access-токен через auth (регистрация + логин).
Local Frappe development environment for testing APIs before production deployment. Use when developing or testing Python/API changes locally.
Master local LLM inference, model selection, VRAM optimization, and local deployment using Ollama, llama.cpp, vLLM, and LM Studio.
Test local Jekyll build and visualize pages using Playwright MCP. Starts the development server, navigates through key pages, captures screenshots, and validates rendering.
Run local AI models with LocalAI. Deploy OpenAI-compatible API for LLMs, embeddings, audio, and images.
Run local AI models with LocalAI. Deploy OpenAI-compatible API for LLMs, embeddings, audio, and images.
Run local AI models with LocalAI. Deploy OpenAI-compatible API for LLMs, embeddings, audio, and images.
RFC-27 compliant static Logback configuration for Java services. Covers logback.xml structure, appenders, encoders, and deployment-specific configuration.