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Found 1,317 Skills
Deployment & Operations Expert responsible for securely, rollbackable, and observably deploying builds that pass Reviewer and QA gates to servers (PM2 3-process cluster + Nginx reverse proxy + BT Panel). Adheres to engineering baselines including zero-downtime deployment, health checks, rollback within ≤3 minutes, and post-release smoke testing. Handles deployment orchestration, configuration management, traffic management, and monitoring & alerting. Applicable when receiving task cards from the Deploy department or needing to release to production.
Cloud infrastructure design and deployment patterns for AWS, Azure, and GCP. Use when designing cloud architectures, implementing IaC with Terraform, optimizing costs, or setting up multi-region deployments.
Expert knowledge for Azure Databricks development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when using Unity Catalog, Lakeflow, Lakebase, Delta Sharing, Databricks SQL, or Model Serving workloads, and other Azure Databricks related development tasks. Not for Azure Synapse Analytics (use azure-synapse-analytics), Azure HDInsight (use azure-hdinsight), Azure Machine Learning (use azure-machine-learning), Azure Data Factory (use azure-data-factory).
Phoenix operations and deployment: releases, runtime configuration, clustering, libcluster, telemetry/logging, secrets, assets, background jobs, and production hardening on the BEAM.
Use when the user asks about the Alpic CLI (`alpic`) — deploying MCP servers, viewing logs, debugging deployments, managing environment variables, configuring the playground, connecting git, and publishing to the MCP Registry.
VP of Engineering advisory for startups: delivery throughput (DORA 4 metrics + bottleneck identification), engineering hiring funnel (sourcing → screen → onsite → offer conversion + time-to-fill + pipeline gap), engineering team structure (squad/tribe/chapter design + tech-lead manager-trigger thresholds), and production discipline (on-call, deployment cadence, postmortem culture). Use when sprint velocity is dropping, eng hiring is broken, team structure is unclear, or deciding when to add a tech-lead manager. NOT a CTO skill (which owns architecture) — VPE owns delivery operations and how the team ships.
Deliver repeatable MotherDuck architectures across multiple clients. Use when standardizing isolation, provisioning, regional deployment, sharing boundaries, and client-specific exceptions for a consultancy or partner delivery model.
RT-DETR (Real-Time DEtection TRansformer) for 2D object detection. Designed for real-time inference with competitive accuracy and supports distillation and quantization for deployment optimization. Use when training, evaluating, distilling, quantizing, exporting, or running inference for a TAO RT-DETR model. Trigger phrases include "train RT-DETR", "real-time DETR", "low-latency object detection", "RT-DETR distillation / quantization".
One-click deployment of JiuwenSwarm multi-Agent collaboration platform on Huawei Cloud Flexus L instances. Usage scenarios: When users need to quickly deploy JiuwenSwarm/JiuwenClaw on Huawei Cloud Flexus L instances, when they need to automatically create cloud instances and deploy AI Agent platforms, when they need to configure model APIs and message channels (Xiaoyi/Feishu/DingTalk). Automatically create instances, deploy applications via COC, configure models and message channels. Trigger keywords: JiuwenSwarm deployment, JiuwenClaw deployment, 九问Swarm部署, 九问Claw部署, 一键部署JiuwenSwarm, AI智能体平台部署, 部署九问Swarm, 部署九问Claw,云服务器部署AI平台.
AWS CloudFormation patterns for IAM users, roles, policies, and managed policies. Use when creating IAM resources with CloudFormation, implementing least privilege access, configuring cross-account access, setting up identity centers, managing permissions boundaries, and organizing template structure with Parameters, Outputs, Mappings, Conditions for secure infrastructure deployments.
React/TypeScript frontend implementation patterns. Use during the implementation phase when creating or modifying React components, custom hooks, pages, data fetching logic with TanStack Query, forms, or routing. Covers component structure, hooks rules, custom hook design (useAuth, useDebounce, usePagination), TypeScript strict-mode conventions, form handling, accessibility requirements, and project structure. Does NOT cover testing (use react-testing-patterns), E2E testing (use e2e-testing), or deployment.
This skill should be used when containerizing applications with Docker, creating Dockerfiles, docker-compose configurations, or deploying containers to various platforms. Ideal for Next.js, React, Node.js applications requiring containerization for development, production, or CI/CD pipelines. Use this skill when users need Docker configurations, multi-stage builds, container orchestration, or deployment to Kubernetes, ECS, Cloud Run, etc.