Claude Skills 列表

You are an SLO (Service Level Objective) expert specializing in implementing reliability standards and error budget-based engineering practices. Design comprehensive SLO...

Complete Odoo backup and restore strategy: database dumps, filestore backup, automated scheduling, cloud storage upload, and tested restore procedures.

Production-ready Docker and docker-compose setup for Odoo with PostgreSQL, persistent volumes, environment-based configuration, and Nginx reverse proxy.

Configure New Relic observability platform for infrastructure and application monitoring.

Generate ready-to-use CI/CD pipeline configurations that install and run Newman for automated API testing.

Configure NFS servers and clients. Implement network file sharing for Linux systems. Use when setting up shared storage.

Design secure, multi-tenant LLM hosting platforms with tenant isolation, quotas, billing attribution, noisy-neighbor protection, and per-tenant policy controls.

Run a local process inside a live Kubernetes cluster's network, env and traffic with mirrord, so changes are tested against real services without deploying.

Generate production-ready mise.toml setups for local development, CI/CD pipelines, and toolchain standardization.

Deploy ML models on Kubernetes with KServe (formerly KFServing) and NVIDIA Triton Inference Server.

Manage and secure company devices with MDM solutions

CRITICAL: Use for Makepad packaging and deployment. Triggers on: deploy, package, APK, IPA, 打包, 部署, cargo-packager, cargo-makepad, WASM, Android, iOS, distribution, installer,...

Install and configure the Manifest observability plugin for your agents. Use when setting up telemetry, configuring API keys, or troubleshooting the plugin.

Configure a Mac mini as a reliable local LLM server with remote access, observability, and power-safe operation. Use when building an always-on private AI inference server on...

Add or verify a Mailtrap sending domain, troubleshoot DNS propagation, publish SPF/DKIM/DMARC records, and complete compliance.

Configure load balancers and traffic distribution. Implement health checks and SSL termination. Use when distributing traffic across servers.

Configure Grafana Loki for log aggregation and analysis.

Deploy an API gateway for LLM traffic with load balancing, rate limiting, key management, semantic caching, fallback routing, and cost tracking.

Auto-scale LLM inference clusters on Kubernetes using KEDA, custom GPU metrics, and horizontal pod autoscaling.

Build production LLMOps platforms with CI/CD, model promotion workflows, evaluation gates, rollback, and governance across cloud and self-hosted inference.